Financial_Stock_Analysis_&_Clustering_2023.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ykg6yYKFLXv6"
      },
      "source": [
        "**Title**: Financial Stock Analysis and Clustering\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "**Version**: 5.0\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "**Authors**: Raza Mehar\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "**Course**: Hawardware and Software for Big Data\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "**Initiation date**: 15th Dec, 2023"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5APiyKr8s1Bz",
        "outputId": "64cfae4e-da63-4743-de9e-03873d67f6ad"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting kafka-python\n",
            "  Downloading kafka_python-2.0.2-py2.py3-none-any.whl (246 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m246.5/246.5 kB\u001b[0m \u001b[31m1.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: kafka-python\n",
            "Successfully installed kafka-python-2.0.2\n",
            "Requirement already satisfied: yfinance in /usr/local/lib/python3.10/dist-packages (0.2.36)\n",
            "Requirement already satisfied: pandas>=1.3.0 in /usr/local/lib/python3.10/dist-packages (from yfinance) (1.5.3)\n",
            "Requirement already satisfied: numpy>=1.16.5 in /usr/local/lib/python3.10/dist-packages (from yfinance) (1.23.5)\n",
            "Requirement already satisfied: requests>=2.31 in /usr/local/lib/python3.10/dist-packages (from yfinance) (2.31.0)\n",
            "Requirement already satisfied: multitasking>=0.0.7 in /usr/local/lib/python3.10/dist-packages (from yfinance) (0.0.11)\n",
            "Requirement already satisfied: lxml>=4.9.1 in /usr/local/lib/python3.10/dist-packages (from yfinance) (4.9.4)\n",
            "Requirement already satisfied: appdirs>=1.4.4 in /usr/local/lib/python3.10/dist-packages (from yfinance) (1.4.4)\n",
            "Requirement already satisfied: pytz>=2022.5 in /usr/local/lib/python3.10/dist-packages (from yfinance) (2023.3.post1)\n",
            "Requirement already satisfied: frozendict>=2.3.4 in /usr/local/lib/python3.10/dist-packages (from yfinance) (2.4.0)\n",
            "Requirement already satisfied: peewee>=3.16.2 in /usr/local/lib/python3.10/dist-packages (from yfinance) (3.17.0)\n",
            "Requirement already satisfied: beautifulsoup4>=4.11.1 in /usr/local/lib/python3.10/dist-packages (from yfinance) (4.11.2)\n",
            "Requirement already satisfied: html5lib>=1.1 in /usr/local/lib/python3.10/dist-packages (from yfinance) (1.1)\n",
            "Requirement already satisfied: soupsieve>1.2 in /usr/local/lib/python3.10/dist-packages (from beautifulsoup4>=4.11.1->yfinance) (2.5)\n",
            "Requirement already satisfied: six>=1.9 in /usr/local/lib/python3.10/dist-packages (from html5lib>=1.1->yfinance) (1.16.0)\n",
            "Requirement already satisfied: webencodings in /usr/local/lib/python3.10/dist-packages (from html5lib>=1.1->yfinance) (0.5.1)\n",
            "Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.3.0->yfinance) (2.8.2)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.31->yfinance) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.31->yfinance) (3.6)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.31->yfinance) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.31->yfinance) (2023.11.17)\n",
            "Collecting pyspark\n",
            "  Downloading pyspark-3.5.0.tar.gz (316.9 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m316.9/316.9 MB\u001b[0m \u001b[31m2.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: py4j==0.10.9.7 in /usr/local/lib/python3.10/dist-packages (from pyspark) (0.10.9.7)\n",
            "Building wheels for collected packages: pyspark\n",
            "  Building wheel for pyspark (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pyspark: filename=pyspark-3.5.0-py2.py3-none-any.whl size=317425345 sha256=9060c70fc8eadfd25a078b3d6acb1b50d673c8e055f682235d7fbc839a823364\n",
            "  Stored in directory: /root/.cache/pip/wheels/41/4e/10/c2cf2467f71c678cfc8a6b9ac9241e5e44a01940da8fbb17fc\n",
            "Successfully built pyspark\n",
            "Installing collected packages: pyspark\n",
            "Successfully installed pyspark-3.5.0\n",
            "--2024-01-26 08:09:05--  http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz\n",
            "Resolving prdownloads.sourceforge.net (prdownloads.sourceforge.net)... 204.68.111.105\n",
            "Connecting to prdownloads.sourceforge.net (prdownloads.sourceforge.net)|204.68.111.105|:80... connected.\n",
            "HTTP request sent, awaiting response... 301 Moved Permanently\n",
            "Location: http://downloads.sourceforge.net/project/ta-lib/ta-lib/0.4.0/ta-lib-0.4.0-src.tar.gz [following]\n",
            "--2024-01-26 08:09:05--  http://downloads.sourceforge.net/project/ta-lib/ta-lib/0.4.0/ta-lib-0.4.0-src.tar.gz\n",
            "Resolving downloads.sourceforge.net (downloads.sourceforge.net)... 204.68.111.105\n",
            "Reusing existing connection to prdownloads.sourceforge.net:80.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: http://versaweb.dl.sourceforge.net/project/ta-lib/ta-lib/0.4.0/ta-lib-0.4.0-src.tar.gz [following]\n",
            "--2024-01-26 08:09:05--  http://versaweb.dl.sourceforge.net/project/ta-lib/ta-lib/0.4.0/ta-lib-0.4.0-src.tar.gz\n",
            "Resolving versaweb.dl.sourceforge.net (versaweb.dl.sourceforge.net)... 162.251.232.173\n",
            "Connecting to versaweb.dl.sourceforge.net (versaweb.dl.sourceforge.net)|162.251.232.173|:80... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 1330299 (1.3M) [application/x-gzip]\n",
            "Saving to: ‘ta-lib-0.4.0-src.tar.gz’\n",
            "\n",
            "ta-lib-0.4.0-src.ta 100%[===================>]   1.27M  4.58MB/s    in 0.3s    \n",
            "\n",
            "2024-01-26 08:09:05 (4.58 MB/s) - ‘ta-lib-0.4.0-src.tar.gz’ saved [1330299/1330299]\n",
            "\n",
            "ta-lib/\n",
            "ta-lib/config.sub\n",
            "ta-lib/aclocal.m4\n",
            "ta-lib/CHANGELOG.TXT\n",
            "ta-lib/include/\n",
            "ta-lib/include/ta_abstract.h\n",
            "ta-lib/include/ta_func.h\n",
            "ta-lib/include/ta_common.h\n",
            "ta-lib/include/ta_config.h.in\n",
            "ta-lib/include/Makefile.am\n",
            "ta-lib/include/ta_libc.h\n",
            "ta-lib/include/ta_defs.h\n",
            "ta-lib/missing\n",
            "ta-lib/ta-lib.spec.in\n",
            "ta-lib/config.guess\n",
            "ta-lib/Makefile.in\n",
            "ta-lib/ta-lib.dpkg.in\n",
            "ta-lib/Makefile.am\n",
            "ta-lib/autogen.sh\n",
            "ta-lib/install-sh\n",
            "ta-lib/configure\n",
            "ta-lib/depcomp\n",
            "ta-lib/HISTORY.TXT\n",
            "ta-lib/configure.in\n",
            "ta-lib/autom4te.cache/\n",
            "ta-lib/autom4te.cache/output.0\n",
            "ta-lib/autom4te.cache/requests\n",
            "ta-lib/autom4te.cache/output.1\n",
            "ta-lib/autom4te.cache/traces.0\n",
            "ta-lib/autom4te.cache/traces.1\n",
            "ta-lib/ltmain.sh\n",
            "ta-lib/ta-lib-config.in\n",
            "ta-lib/src/\n",
            "ta-lib/src/ta_func/\n",
            "ta-lib/src/ta_func/ta_MACDFIX.c\n",
            "ta-lib/src/ta_func/ta_CDLPIERCING.c\n",
            "ta-lib/src/ta_func/ta_DIV.c\n",
            "ta-lib/src/ta_func/ta_ROCR100.c\n",
            "ta-lib/src/ta_func/ta_ADXR.c\n",
            "ta-lib/src/ta_func/ta_MAVP.c\n",
            "ta-lib/src/ta_func/ta_CDLCLOSINGMARUBOZU.c\n",
            "ta-lib/src/ta_func/ta_COSH.c\n",
            "ta-lib/src/ta_func/ta_EXP.c\n",
            "ta-lib/src/ta_func/ta_MINMAXINDEX.c\n",
            "ta-lib/src/ta_func/ta_SQRT.c\n",
            "ta-lib/src/ta_func/ta_FLOOR.c\n",
            "ta-lib/src/ta_func/ta_CDLCONCEALBABYSWALL.c\n",
            "ta-lib/src/ta_func/ta_NATR.c\n",
            "ta-lib/src/ta_func/ta_CDLHARAMICROSS.c\n",
            "ta-lib/src/ta_func/ta_MINUS_DM.c\n",
            "ta-lib/src/ta_func/ta_LOG10.c\n",
            "ta-lib/src/ta_func/ta_LINEARREG_ANGLE.c\n",
            "ta-lib/src/ta_func/ta_RSI.c\n",
            "ta-lib/src/ta_func/ta_CDLABANDONEDBABY.c\n",
            "ta-lib/src/ta_func/ta_SAR.c\n",
            "ta-lib/src/ta_func/ta_CDLBREAKAWAY.c\n",
            "ta-lib/src/ta_func/ta_CDLDRAGONFLYDOJI.c\n",
            "ta-lib/src/ta_func/ta_CDLHIGHWAVE.c\n",
            "ta-lib/src/ta_func/ta_CDLKICKING.c\n",
            "ta-lib/src/ta_func/ta_CDLDOJISTAR.c\n",
            "ta-lib/src/ta_func/ta_VAR.c\n",
            "ta-lib/src/ta_func/ta_CDLMATCHINGLOW.c\n",
            "ta-lib/src/ta_func/ta_CDLGAPSIDESIDEWHITE.c\n",
            "ta-lib/src/ta_func/ta_CDLMARUBOZU.c\n",
            "ta-lib/src/ta_func/ta_AROONOSC.c\n",
            "ta-lib/src/ta_func/ta_WCLPRICE.c\n",
            "ta-lib/src/ta_func/ta_CDLEVENINGDOJISTAR.c\n",
            "ta-lib/src/ta_func/ta_CDL3INSIDE.c\n",
            "ta-lib/src/ta_func/ta_OBV.c\n",
            "ta-lib/src/ta_func/ta_AROON.c\n",
            "ta-lib/src/ta_func/ta_CDLBELTHOLD.c\n",
            "ta-lib/src/ta_func/ta_CDLSPINNINGTOP.c\n",
            "ta-lib/src/ta_func/ta_AD.c\n",
            "ta-lib/src/ta_func/ta_MAX.c\n",
            "ta-lib/src/ta_func/ta_CDLENGULFING.c\n",
            "ta-lib/src/ta_func/ta_MINMAX.c\n",
            "ta-lib/src/ta_func/ta_CDLINNECK.c\n",
            "ta-lib/src/ta_func/ta_STDDEV.c\n",
            "ta-lib/src/ta_func/ta_NVI.c\n",
            "ta-lib/src/ta_func/ta_CDLHAMMER.c\n",
            "ta-lib/src/ta_func/ta_ASIN.c\n",
            "ta-lib/src/ta_func/ta_SUM.c\n",
            "ta-lib/src/ta_func/ta_STOCH.c\n",
            "ta-lib/src/ta_func/ta_CDLLONGLEGGEDDOJI.c\n",
            "ta-lib/src/ta_func/ta_MEDPRICE.c\n",
            "ta-lib/src/ta_func/ta_CDL3STARSINSOUTH.c\n",
            "ta-lib/src/ta_func/ta_HT_TRENDMODE.c\n",
            "ta-lib/src/ta_func/ta_BBANDS.c\n",
            "ta-lib/src/ta_func/ta_CDLMORNINGSTAR.c\n",
            "ta-lib/src/ta_func/ta_HT_DCPHASE.c\n",
            "ta-lib/src/ta_func/ta_CDLLONGLINE.c\n",
            "ta-lib/src/ta_func/ta_TAN.c\n",
            "ta-lib/src/ta_func/ta_SMA.c\n",
            "ta-lib/src/ta_func/ta_DX.c\n",
            "ta-lib/src/ta_func/ta_MIDPOINT.c\n",
            "ta-lib/src/ta_func/ta_CDL2CROWS.c\n",
            "ta-lib/src/ta_func/ta_CORREL.c\n",
            "ta-lib/src/ta_func/ta_CDL3BLACKCROWS.c\n",
            "ta-lib/src/ta_func/ta_ADD.c\n",
            "ta-lib/src/ta_func/Makefile.in\n",
            "ta-lib/src/ta_func/ta_CDLTHRUSTING.c\n",
            "ta-lib/src/ta_func/ta_SUB.c\n",
            "ta-lib/src/ta_func/ta_CDLSTALLEDPATTERN.c\n",
            "ta-lib/src/ta_func/ta_CDLTRISTAR.c\n",
            "ta-lib/src/ta_func/ta_MA.c\n",
            "ta-lib/src/ta_func/ta_HT_SINE.c\n",
            "ta-lib/src/ta_func/ta_ACOS.c\n",
            "ta-lib/src/ta_func/ta_CDLSTICKSANDWICH.c\n",
            "ta-lib/src/ta_func/ta_SINH.c\n",
            "ta-lib/src/ta_func/ta_utility.h\n",
            "ta-lib/src/ta_func/ta_CDLSHORTLINE.c\n",
            "ta-lib/src/ta_func/ta_ATAN.c\n",
            "ta-lib/src/ta_func/ta_CDLADVANCEBLOCK.c\n",
            "ta-lib/src/ta_func/ta_CDLKICKINGBYLENGTH.c\n",
            "ta-lib/src/ta_func/ta_CDLSHOOTINGSTAR.c\n",
            "ta-lib/src/ta_func/ta_ROCR.c\n",
            "ta-lib/src/ta_func/ta_WMA.c\n",
            "ta-lib/src/ta_func/ta_CDLDARKCLOUDCOVER.c\n",
            "ta-lib/src/ta_func/ta_CDLXSIDEGAP3METHODS.c\n",
            "ta-lib/src/ta_func/ta_TYPPRICE.c\n",
            "ta-lib/src/ta_func/ta_CDL3WHITESOLDIERS.c\n",
            "ta-lib/src/ta_func/Makefile.am\n",
            "ta-lib/src/ta_func/ta_MACDEXT.c\n",
            "ta-lib/src/ta_func/ta_ADX.c\n",
            "ta-lib/src/ta_func/ta_PLUS_DM.c\n",
            "ta-lib/src/ta_func/ta_CDLUPSIDEGAP2CROWS.c\n",
            "ta-lib/src/ta_func/ta_LN.c\n",
            "ta-lib/src/ta_func/ta_DEMA.c\n",
            "ta-lib/src/ta_func/ta_CDL3OUTSIDE.c\n",
            "ta-lib/src/ta_func/ta_CDLTASUKIGAP.c\n",
            "ta-lib/src/ta_func/ta_MAMA.c\n",
            "ta-lib/src/ta_func/ta_CDLMORNINGDOJISTAR.c\n",
            "ta-lib/src/ta_func/ta_PLUS_DI.c\n",
            "ta-lib/src/ta_func/ta_MININDEX.c\n",
            "ta-lib/src/ta_func/ta_COS.c\n",
            "ta-lib/src/ta_func/ta_HT_TRENDLINE.c\n",
            "ta-lib/src/ta_func/ta_MIDPRICE.c\n",
            "ta-lib/src/ta_func/ta_CEIL.c\n",
            "ta-lib/src/ta_func/ta_TRIMA.c\n",
            "ta-lib/src/ta_func/ta_CDLSEPARATINGLINES.c\n",
            "ta-lib/src/ta_func/ta_ROCP.c\n",
            "ta-lib/src/ta_func/ta_CDLHOMINGPIGEON.c\n",
            "ta-lib/src/ta_func/ta_CDLHANGINGMAN.c\n",
            "ta-lib/src/ta_func/ta_AVGPRICE.c\n",
            "ta-lib/src/ta_func/ta_APO.c\n",
            "ta-lib/src/ta_func/ta_CDLRISEFALL3METHODS.c\n",
            "ta-lib/src/ta_func/ta_TRANGE.c\n",
            "ta-lib/src/ta_func/ta_TSF.c\n",
            "ta-lib/src/ta_func/ta_LINEARREG.c\n",
            "ta-lib/src/ta_func/ta_PVI.c\n",
            "ta-lib/src/ta_func/ta_CDLHIKKAKEMOD.c\n",
            "ta-lib/src/ta_func/ta_MFI.c\n",
            "ta-lib/src/ta_func/ta_CDLHARAMI.c\n",
            "ta-lib/src/ta_func/ta_MACD.c\n",
            "ta-lib/src/ta_func/ta_BETA.c\n",
            "ta-lib/src/ta_func/ta_CDLINVERTEDHAMMER.c\n",
            "ta-lib/src/ta_func/ta_LINEARREG_SLOPE.c\n",
            "ta-lib/src/ta_func/ta_STOCHF.c\n",
            "ta-lib/src/ta_func/ta_MIN.c\n",
            "ta-lib/src/ta_func/ta_CDLIDENTICAL3CROWS.c\n",
            "ta-lib/src/ta_func/ta_CDLRICKSHAWMAN.c\n",
            "ta-lib/src/ta_func/ta_T3.c\n",
            "ta-lib/src/ta_func/ta_CDLMATHOLD.c\n",
            "ta-lib/src/ta_func/ta_CDLUNIQUE3RIVER.c\n",
            "ta-lib/src/ta_func/ta_ADOSC.c\n",
            "ta-lib/src/ta_func/ta_MAXINDEX.c\n",
            "ta-lib/src/ta_func/ta_ULTOSC.c\n",
            "ta-lib/src/ta_func/ta_TRIX.c\n",
            "ta-lib/src/ta_func/ta_MOM.c\n",
            "ta-lib/src/ta_func/ta_CDLDOJI.c\n",
            "ta-lib/src/ta_func/ta_EMA.c\n",
            "ta-lib/src/ta_func/ta_STOCHRSI.c\n",
            "ta-lib/src/ta_func/ta_ROC.c\n",
            "ta-lib/src/ta_func/ta_CDLEVENINGSTAR.c\n",
            "ta-lib/src/ta_func/ta_CDLCOUNTERATTACK.c\n",
            "ta-lib/src/ta_func/ta_LINEARREG_INTERCEPT.c\n",
            "ta-lib/src/ta_func/ta_SAREXT.c\n",
            "ta-lib/src/ta_func/ta_WILLR.c\n",
            "ta-lib/src/ta_func/ta_MULT.c\n",
            "ta-lib/src/ta_func/ta_ATR.c\n",
            "ta-lib/src/ta_func/ta_BOP.c\n",
            "ta-lib/src/ta_func/ta_CMO.c\n",
            "ta-lib/src/ta_func/ta_CDLONNECK.c\n",
            "ta-lib/src/ta_func/ta_CCI.c\n",
            "ta-lib/src/ta_func/ta_CDLLADDERBOTTOM.c\n",
            "ta-lib/src/ta_func/ta_HT_PHASOR.c\n",
            "ta-lib/src/ta_func/ta_utility.c\n",
            "ta-lib/src/ta_func/ta_PPO.c\n",
            "ta-lib/src/ta_func/ta_CDLHIKKAKE.c\n",
            "ta-lib/src/ta_func/ta_HT_DCPERIOD.c\n",
            "ta-lib/src/ta_func/ta_CDL3LINESTRIKE.c\n",
            "ta-lib/src/ta_func/ta_TEMA.c\n",
            "ta-lib/src/ta_func/ta_SIN.c\n",
            "ta-lib/src/ta_func/ta_MINUS_DI.c\n",
            "ta-lib/src/ta_func/ta_KAMA.c\n",
            "ta-lib/src/ta_func/ta_TANH.c\n",
            "ta-lib/src/ta_func/ta_CDLTAKURI.c\n",
            "ta-lib/src/ta_func/ta_CDLGRAVESTONEDOJI.c\n",
            "ta-lib/src/ta_common/\n",
            "ta-lib/src/ta_common/ta_pragma.h\n",
            "ta-lib/src/ta_common/ta_magic_nb.h\n",
            "ta-lib/src/ta_common/ta_retcode.csv\n",
            "ta-lib/src/ta_common/Makefile.in\n",
            "ta-lib/src/ta_common/Makefile.am\n",
            "ta-lib/src/ta_common/ta_memory.h\n",
            "ta-lib/src/ta_common/ta_version.c\n",
            "ta-lib/src/ta_common/ta_global.h\n",
            "ta-lib/src/ta_common/ta_global.c\n",
            "ta-lib/src/ta_common/ta_retcode.c\n",
            "ta-lib/src/Makefile.in\n",
            "ta-lib/src/ta_abstract/\n",
            "ta-lib/src/ta_abstract/frames/\n",
            "ta-lib/src/ta_abstract/frames/ta_frame.c\n",
            "ta-lib/src/ta_abstract/frames/ta_frame.h\n",
            "ta-lib/src/ta_abstract/excel_glue.c\n",
            "ta-lib/src/ta_abstract/ta_frame_priv.h\n",
            "ta-lib/src/ta_abstract/ta_func_api.c\n",
            "ta-lib/src/ta_abstract/Makefile.in\n",
            "ta-lib/src/ta_abstract/ta_def_ui.h\n",
            "ta-lib/src/ta_abstract/Makefile.am\n",
            "ta-lib/src/ta_abstract/ta_abstract.c\n",
            "ta-lib/src/ta_abstract/ta_group_idx.c\n",
            "ta-lib/src/ta_abstract/tables/\n",
            "ta-lib/src/ta_abstract/tables/table_u.c\n",
            "ta-lib/src/ta_abstract/tables/table_x.c\n",
            "ta-lib/src/ta_abstract/tables/table_r.c\n",
            "ta-lib/src/ta_abstract/tables/table_f.c\n",
            "ta-lib/src/ta_abstract/tables/table_j.c\n",
            "ta-lib/src/ta_abstract/tables/table_e.c\n",
            "ta-lib/src/ta_abstract/tables/table_t.c\n",
            "ta-lib/src/ta_abstract/tables/table_n.c\n",
            "ta-lib/src/ta_abstract/tables/table_i.c\n",
            "ta-lib/src/ta_abstract/tables/table_c.c\n",
            "ta-lib/src/ta_abstract/tables/table_l.c\n",
            "ta-lib/src/ta_abstract/tables/table_k.c\n",
            "ta-lib/src/ta_abstract/tables/table_g.c\n",
            "ta-lib/src/ta_abstract/tables/table_d.c\n",
            "ta-lib/src/ta_abstract/tables/table_h.c\n",
            "ta-lib/src/ta_abstract/tables/table_o.c\n",
            "ta-lib/src/ta_abstract/tables/table_b.c\n",
            "ta-lib/src/ta_abstract/tables/table_q.c\n",
            "ta-lib/src/ta_abstract/tables/table_v.c\n",
            "ta-lib/src/ta_abstract/tables/table_m.c\n",
            "ta-lib/src/ta_abstract/tables/table_s.c\n",
            "ta-lib/src/ta_abstract/tables/table_y.c\n",
            "ta-lib/src/ta_abstract/tables/table_p.c\n",
            "ta-lib/src/ta_abstract/tables/table_z.c\n",
            "ta-lib/src/ta_abstract/tables/table_a.c\n",
            "ta-lib/src/ta_abstract/tables/table_w.c\n",
            "ta-lib/src/ta_abstract/ta_def_ui.c\n",
            "ta-lib/src/ta_abstract/templates/\n",
            "ta-lib/src/ta_abstract/templates/ta_x.c.template\n",
            "ta-lib/src/ta_abstract/templates/ta_java_defs.h.template\n",
            "ta-lib/src/ta_abstract/templates/excel_glue.c.template\n",
            "ta-lib/src/ta_abstract/templates/ta_group_idx.c.template\n",
            "ta-lib/src/ta_abstract/templates/ta_frame.c.template\n",
            "ta-lib/src/ta_abstract/templates/CoreAnnotated.java.template\n",
            "ta-lib/src/ta_abstract/templates/ta_func.h.template\n",
            "ta-lib/src/ta_abstract/templates/ta_frame.h.template\n",
            "ta-lib/src/ta_abstract/templates/Makefile.am.template\n",
            "ta-lib/src/ta_abstract/templates/ta_func_api.c.template\n",
            "ta-lib/src/ta_abstract/templates/ta_func.swg.template\n",
            "ta-lib/src/ta_abstract/templates/ta_retcode.c.template\n",
            "ta-lib/src/ta_abstract/ta_java_defs.h\n",
            "ta-lib/src/Makefile.am\n",
            "ta-lib/src/tools/\n",
            "ta-lib/src/tools/ta_regtest/\n",
            "ta-lib/src/tools/ta_regtest/test_util.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func.h\n",
            "ta-lib/src/tools/ta_regtest/test_data.c\n",
            "ta-lib/src/tools/ta_regtest/ta_gDataHigh.c\n",
            "ta-lib/src/tools/ta_regtest/Makefile.in\n",
            "ta-lib/src/tools/ta_regtest/test_internals.c\n",
            "ta-lib/src/tools/ta_regtest/Makefile.am\n",
            "ta-lib/src/tools/ta_regtest/ta_regtest.c\n",
            "ta-lib/src/tools/ta_regtest/ta_gDataOpen.c\n",
            "ta-lib/src/tools/ta_regtest/ta_gDataClose.c\n",
            "ta-lib/src/tools/ta_regtest/test_abstract.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_bbands.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_stddev.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_1in_2out.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_sar.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_1in_1out.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_trange.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_macd.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_po.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_per_hlc.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_mom.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_per_ohlc.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_adx.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_candlestick.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_rsi.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_per_ema.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_minmax.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_per_hlcv.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_per_hl.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_stoch.c\n",
            "ta-lib/src/tools/ta_regtest/ta_test_func/test_ma.c\n",
            "ta-lib/src/tools/ta_regtest/ta_error_number.h\n",
            "ta-lib/src/tools/ta_regtest/ta_test_priv.h\n",
            "ta-lib/src/tools/ta_regtest/ReadMe.txt\n",
            "ta-lib/src/tools/ta_regtest/ta_gDataLow.c\n",
            "ta-lib/src/tools/Makefile.in\n",
            "ta-lib/src/tools/Makefile.am\n",
            "ta-lib/src/tools/gen_code/\n",
            "ta-lib/src/tools/gen_code/java/\n",
            "ta-lib/src/tools/gen_code/java/PrettyCode.java\n",
            "ta-lib/src/tools/gen_code/java/Main.java\n",
            "ta-lib/src/tools/gen_code/gen_code.c\n",
            "ta-lib/src/tools/gen_code/Makefile.in\n",
            "ta-lib/src/tools/gen_code/Makefile.am\n",
            "ta-lib/src/tools/gen_code/mcpp.exe\n",
            "/content/ta-lib\n",
            "checking for a BSD-compatible install... /usr/bin/install -c\n",
            "checking whether build environment is sane... yes\n",
            "checking for a thread-safe mkdir -p... /usr/bin/mkdir -p\n",
            "checking for gawk... no\n",
            "checking for mawk... mawk\n",
            "checking whether make sets $(MAKE)... yes\n",
            "checking for gcc... gcc\n",
            "checking for C compiler default output file name... a.out\n",
            "checking whether the C compiler works... yes\n",
            "checking whether we are cross compiling... no\n",
            "checking for suffix of executables... \n",
            "checking for suffix of object files... o\n",
            "checking whether we are using the GNU C compiler... yes\n",
            "checking whether gcc accepts -g... yes\n",
            "checking for gcc option to accept ISO C89... none needed\n",
            "checking for style of include used by make... GNU\n",
            "checking dependency style of gcc... gcc3\n",
            "checking build system type... x86_64-unknown-linux-gnu\n",
            "checking host system type... x86_64-unknown-linux-gnu\n",
            "checking for a sed that does not truncate output... /usr/bin/sed\n",
            "checking for grep that handles long lines and -e... /usr/bin/grep\n",
            "checking for egrep... /usr/bin/grep -E\n",
            "checking for ld used by gcc... /usr/bin/ld\n",
            "checking if the linker (/usr/bin/ld) is GNU ld... yes\n",
            "checking for /usr/bin/ld option to reload object files... -r\n",
            "checking for BSD-compatible nm... /usr/bin/nm -B\n",
            "checking whether ln -s works... yes\n",
            "checking how to recognise dependent libraries... pass_all\n",
            "checking how to run the C preprocessor... gcc -E\n",
            "checking for ANSI C header files... yes\n",
            "checking for sys/types.h... yes\n",
            "checking for sys/stat.h... yes\n",
            "checking for stdlib.h... yes\n",
            "checking for string.h... yes\n",
            "checking for memory.h... yes\n",
            "checking for strings.h... yes\n",
            "checking for inttypes.h... yes\n",
            "checking for stdint.h... yes\n",
            "checking for unistd.h... yes\n",
            "checking dlfcn.h usability... yes\n",
            "checking dlfcn.h presence... yes\n",
            "checking for dlfcn.h... yes\n",
            "checking for g++... g++\n",
            "checking whether we are using the GNU C++ compiler... yes\n",
            "checking whether g++ accepts -g... yes\n",
            "checking dependency style of g++... gcc3\n",
            "checking how to run the C++ preprocessor... g++ -E\n",
            "checking for g77... no\n",
            "checking for xlf... no\n",
            "checking for f77... f77\n",
            "checking whether we are using the GNU Fortran 77 compiler... yes\n",
            "checking whether f77 accepts -g... yes\n",
            "checking the maximum length of command line arguments... 32768\n",
            "checking command to parse /usr/bin/nm -B output from gcc object... ok\n",
            "checking for objdir... .libs\n",
            "checking for ar... ar\n",
            "checking for ranlib... ranlib\n",
            "checking for strip... strip\n",
            "checking if gcc supports -fno-rtti -fno-exceptions... no\n",
            "checking for gcc option to produce PIC... -fPIC\n",
            "checking if gcc PIC flag -fPIC works... yes\n",
            "checking if gcc static flag -static works... yes\n",
            "checking if gcc supports -c -o file.o... yes\n",
            "checking whether the gcc linker (/usr/bin/ld -m elf_x86_64) supports shared libraries... yes\n",
            "checking whether -lc should be explicitly linked in... no\n",
            "checking dynamic linker characteristics... GNU/Linux ld.so\n",
            "checking how to hardcode library paths into programs... immediate\n",
            "checking whether stripping libraries is possible... yes\n",
            "checking if libtool supports shared libraries... yes\n",
            "checking whether to build shared libraries... yes\n",
            "checking whether to build static libraries... yes\n",
            "configure: creating libtool\n",
            "appending configuration tag \"CXX\" to libtool\n",
            "checking for ld used by g++... /usr/bin/ld -m elf_x86_64\n",
            "checking if the linker (/usr/bin/ld -m elf_x86_64) is GNU ld... yes\n",
            "checking whether the g++ linker (/usr/bin/ld -m elf_x86_64) supports shared libraries... yes\n",
            "checking for g++ option to produce PIC... -fPIC\n",
            "checking if g++ PIC flag -fPIC works... yes\n",
            "checking if g++ static flag -static works... yes\n",
            "checking if g++ supports -c -o file.o... yes\n",
            "checking whether the g++ linker (/usr/bin/ld -m elf_x86_64) supports shared libraries... yes\n",
            "checking dynamic linker characteristics... GNU/Linux ld.so\n",
            "checking how to hardcode library paths into programs... immediate\n",
            "appending configuration tag \"F77\" to libtool\n",
            "checking if libtool supports shared libraries... yes\n",
            "checking whether to build shared libraries... yes\n",
            "checking whether to build static libraries... yes\n",
            "checking for f77 option to produce PIC... -fPIC\n",
            "checking if f77 PIC flag -fPIC works... yes\n",
            "checking if f77 static flag -static works... yes\n",
            "checking if f77 supports -c -o file.o... yes\n",
            "checking whether the f77 linker (/usr/bin/ld -m elf_x86_64) supports shared libraries... yes\n",
            "checking dynamic linker characteristics... GNU/Linux ld.so\n",
            "checking how to hardcode library paths into programs... immediate\n",
            "checking for dlopen in -ldl... yes\n",
            "checking for pthread_create in -lpthread... yes\n",
            "checking for ANSI C header files... (cached) yes\n",
            "checking float.h usability... yes\n",
            "checking float.h presence... yes\n",
            "checking for float.h... yes\n",
            "checking for inttypes.h... (cached) yes\n",
            "checking limits.h usability... yes\n",
            "checking limits.h presence... yes\n",
            "checking for limits.h... yes\n",
            "checking locale.h usability... yes\n",
            "checking locale.h presence... yes\n",
            "checking for locale.h... yes\n",
            "checking stddef.h usability... yes\n",
            "checking stddef.h presence... yes\n",
            "checking for stddef.h... yes\n",
            "checking for stdint.h... (cached) yes\n",
            "checking for stdlib.h... (cached) yes\n",
            "checking for string.h... (cached) yes\n",
            "checking for unistd.h... (cached) yes\n",
            "checking wchar.h usability... yes\n",
            "checking wchar.h presence... yes\n",
            "checking for wchar.h... yes\n",
            "checking wctype.h usability... yes\n",
            "checking wctype.h presence... yes\n",
            "checking for wctype.h... yes\n",
            "checking for an ANSI C-conforming const... yes\n",
            "checking for size_t... yes\n",
            "checking whether struct tm is in sys/time.h or time.h... time.h\n",
            "checking for working volatile... yes\n",
            "checking for ptrdiff_t... yes\n",
            "checking return type of signal handlers... void\n",
            "checking for working strcoll... yes\n",
            "checking for strftime... yes\n",
            "checking for working strtod... yes\n",
            "checking for vprintf... yes\n",
            "checking for _doprnt... no\n",
            "checking for floor... no\n",
            "checking for isascii... yes\n",
            "checking for localeconv... yes\n",
            "checking for mblen... yes\n",
            "checking for memmove... yes\n",
            "checking for memset... yes\n",
            "checking for modf... yes\n",
            "checking for pow... no\n",
            "checking for sqrt... no\n",
            "checking for strcasecmp... yes\n",
            "checking for strchr... yes\n",
            "checking for strerror... yes\n",
            "checking for strncasecmp... yes\n",
            "checking for strrchr... yes\n",
            "checking for strstr... yes\n",
            "checking for strtol... yes\n",
            "checking for strtoul... yes\n",
            "configure: creating ./config.status\n",
            "config.status: creating Makefile\n",
            "config.status: creating src/Makefile\n",
            "config.status: creating src/ta_abstract/Makefile\n",
            "config.status: creating src/ta_common/Makefile\n",
            "config.status: creating src/ta_func/Makefile\n",
            "config.status: creating src/tools/Makefile\n",
            "config.status: creating src/tools/gen_code/Makefile\n",
            "config.status: creating src/tools/ta_regtest/Makefile\n",
            "config.status: creating ta-lib-config\n",
            "config.status: creating ta-lib.spec\n",
            "config.status: creating ta-lib.dpkg\n",
            "config.status: creating include/ta_config.h\n",
            "config.status: executing depfiles commands\n",
            "Making all in src\n",
            "make[1]: Entering directory '/content/ta-lib/src'\n",
            "Making all in ta_abstract\n",
            "make[2]: Entering directory '/content/ta-lib/src/ta_abstract'\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-ta_group_idx.lo -MD -MP -MF .deps/libta_abstract_la-ta_group_idx.Tpo -c -o libta_abstract_la-ta_group_idx.lo `test -f 'ta_group_idx.c' || echo './'`ta_group_idx.c\n",
            "mkdir .libs\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-ta_group_idx.lo -MD -MP -MF .deps/libta_abstract_la-ta_group_idx.Tpo -c ta_group_idx.c  -fPIC -DPIC -o .libs/libta_abstract_la-ta_group_idx.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-ta_group_idx.lo -MD -MP -MF .deps/libta_abstract_la-ta_group_idx.Tpo -c ta_group_idx.c -o libta_abstract_la-ta_group_idx.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-ta_group_idx.Tpo .deps/libta_abstract_la-ta_group_idx.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-ta_def_ui.lo -MD -MP -MF .deps/libta_abstract_la-ta_def_ui.Tpo -c -o libta_abstract_la-ta_def_ui.lo `test -f 'ta_def_ui.c' || echo './'`ta_def_ui.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-ta_def_ui.lo -MD -MP -MF .deps/libta_abstract_la-ta_def_ui.Tpo -c ta_def_ui.c  -fPIC -DPIC -o .libs/libta_abstract_la-ta_def_ui.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-ta_def_ui.lo -MD -MP -MF .deps/libta_abstract_la-ta_def_ui.Tpo -c ta_def_ui.c -o libta_abstract_la-ta_def_ui.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-ta_def_ui.Tpo .deps/libta_abstract_la-ta_def_ui.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-ta_abstract.lo -MD -MP -MF .deps/libta_abstract_la-ta_abstract.Tpo -c -o libta_abstract_la-ta_abstract.lo `test -f 'ta_abstract.c' || echo './'`ta_abstract.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-ta_abstract.lo -MD -MP -MF .deps/libta_abstract_la-ta_abstract.Tpo -c ta_abstract.c  -fPIC -DPIC -o .libs/libta_abstract_la-ta_abstract.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-ta_abstract.lo -MD -MP -MF .deps/libta_abstract_la-ta_abstract.Tpo -c ta_abstract.c -o libta_abstract_la-ta_abstract.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-ta_abstract.Tpo .deps/libta_abstract_la-ta_abstract.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-ta_func_api.lo -MD -MP -MF .deps/libta_abstract_la-ta_func_api.Tpo -c -o libta_abstract_la-ta_func_api.lo `test -f 'ta_func_api.c' || echo './'`ta_func_api.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-ta_func_api.lo -MD -MP -MF .deps/libta_abstract_la-ta_func_api.Tpo -c ta_func_api.c  -fPIC -DPIC -o .libs/libta_abstract_la-ta_func_api.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-ta_func_api.lo -MD -MP -MF .deps/libta_abstract_la-ta_func_api.Tpo -c ta_func_api.c -o libta_abstract_la-ta_func_api.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-ta_func_api.Tpo .deps/libta_abstract_la-ta_func_api.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-ta_frame.lo -MD -MP -MF .deps/libta_abstract_la-ta_frame.Tpo -c -o libta_abstract_la-ta_frame.lo `test -f 'frames/ta_frame.c' || echo './'`frames/ta_frame.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-ta_frame.lo -MD -MP -MF .deps/libta_abstract_la-ta_frame.Tpo -c frames/ta_frame.c  -fPIC -DPIC -o .libs/libta_abstract_la-ta_frame.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-ta_frame.lo -MD -MP -MF .deps/libta_abstract_la-ta_frame.Tpo -c frames/ta_frame.c -o libta_abstract_la-ta_frame.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-ta_frame.Tpo .deps/libta_abstract_la-ta_frame.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_a.lo -MD -MP -MF .deps/libta_abstract_la-table_a.Tpo -c -o libta_abstract_la-table_a.lo `test -f 'tables/table_a.c' || echo './'`tables/table_a.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_a.lo -MD -MP -MF .deps/libta_abstract_la-table_a.Tpo -c tables/table_a.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_a.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_a.lo -MD -MP -MF .deps/libta_abstract_la-table_a.Tpo -c tables/table_a.c -o libta_abstract_la-table_a.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_a.Tpo .deps/libta_abstract_la-table_a.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_b.lo -MD -MP -MF .deps/libta_abstract_la-table_b.Tpo -c -o libta_abstract_la-table_b.lo `test -f 'tables/table_b.c' || echo './'`tables/table_b.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_b.lo -MD -MP -MF .deps/libta_abstract_la-table_b.Tpo -c tables/table_b.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_b.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_b.lo -MD -MP -MF .deps/libta_abstract_la-table_b.Tpo -c tables/table_b.c -o libta_abstract_la-table_b.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_b.Tpo .deps/libta_abstract_la-table_b.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_c.lo -MD -MP -MF .deps/libta_abstract_la-table_c.Tpo -c -o libta_abstract_la-table_c.lo `test -f 'tables/table_c.c' || echo './'`tables/table_c.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_c.lo -MD -MP -MF .deps/libta_abstract_la-table_c.Tpo -c tables/table_c.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_c.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_c.lo -MD -MP -MF .deps/libta_abstract_la-table_c.Tpo -c tables/table_c.c -o libta_abstract_la-table_c.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_c.Tpo .deps/libta_abstract_la-table_c.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_d.lo -MD -MP -MF .deps/libta_abstract_la-table_d.Tpo -c -o libta_abstract_la-table_d.lo `test -f 'tables/table_d.c' || echo './'`tables/table_d.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_d.lo -MD -MP -MF .deps/libta_abstract_la-table_d.Tpo -c tables/table_d.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_d.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_d.lo -MD -MP -MF .deps/libta_abstract_la-table_d.Tpo -c tables/table_d.c -o libta_abstract_la-table_d.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_d.Tpo .deps/libta_abstract_la-table_d.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_e.lo -MD -MP -MF .deps/libta_abstract_la-table_e.Tpo -c -o libta_abstract_la-table_e.lo `test -f 'tables/table_e.c' || echo './'`tables/table_e.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_e.lo -MD -MP -MF .deps/libta_abstract_la-table_e.Tpo -c tables/table_e.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_e.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_e.lo -MD -MP -MF .deps/libta_abstract_la-table_e.Tpo -c tables/table_e.c -o libta_abstract_la-table_e.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_e.Tpo .deps/libta_abstract_la-table_e.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_f.lo -MD -MP -MF .deps/libta_abstract_la-table_f.Tpo -c -o libta_abstract_la-table_f.lo `test -f 'tables/table_f.c' || echo './'`tables/table_f.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_f.lo -MD -MP -MF .deps/libta_abstract_la-table_f.Tpo -c tables/table_f.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_f.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_f.lo -MD -MP -MF .deps/libta_abstract_la-table_f.Tpo -c tables/table_f.c -o libta_abstract_la-table_f.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_f.Tpo .deps/libta_abstract_la-table_f.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_g.lo -MD -MP -MF .deps/libta_abstract_la-table_g.Tpo -c -o libta_abstract_la-table_g.lo `test -f 'tables/table_g.c' || echo './'`tables/table_g.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_g.lo -MD -MP -MF .deps/libta_abstract_la-table_g.Tpo -c tables/table_g.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_g.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_g.lo -MD -MP -MF .deps/libta_abstract_la-table_g.Tpo -c tables/table_g.c -o libta_abstract_la-table_g.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_g.Tpo .deps/libta_abstract_la-table_g.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_h.lo -MD -MP -MF .deps/libta_abstract_la-table_h.Tpo -c -o libta_abstract_la-table_h.lo `test -f 'tables/table_h.c' || echo './'`tables/table_h.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_h.lo -MD -MP -MF .deps/libta_abstract_la-table_h.Tpo -c tables/table_h.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_h.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_h.lo -MD -MP -MF .deps/libta_abstract_la-table_h.Tpo -c tables/table_h.c -o libta_abstract_la-table_h.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_h.Tpo .deps/libta_abstract_la-table_h.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_i.lo -MD -MP -MF .deps/libta_abstract_la-table_i.Tpo -c -o libta_abstract_la-table_i.lo `test -f 'tables/table_i.c' || echo './'`tables/table_i.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_i.lo -MD -MP -MF .deps/libta_abstract_la-table_i.Tpo -c tables/table_i.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_i.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_i.lo -MD -MP -MF .deps/libta_abstract_la-table_i.Tpo -c tables/table_i.c -o libta_abstract_la-table_i.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_i.Tpo .deps/libta_abstract_la-table_i.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_j.lo -MD -MP -MF .deps/libta_abstract_la-table_j.Tpo -c -o libta_abstract_la-table_j.lo `test -f 'tables/table_j.c' || echo './'`tables/table_j.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_j.lo -MD -MP -MF .deps/libta_abstract_la-table_j.Tpo -c tables/table_j.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_j.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_j.lo -MD -MP -MF .deps/libta_abstract_la-table_j.Tpo -c tables/table_j.c -o libta_abstract_la-table_j.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_j.Tpo .deps/libta_abstract_la-table_j.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_k.lo -MD -MP -MF .deps/libta_abstract_la-table_k.Tpo -c -o libta_abstract_la-table_k.lo `test -f 'tables/table_k.c' || echo './'`tables/table_k.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_k.lo -MD -MP -MF .deps/libta_abstract_la-table_k.Tpo -c tables/table_k.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_k.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_k.lo -MD -MP -MF .deps/libta_abstract_la-table_k.Tpo -c tables/table_k.c -o libta_abstract_la-table_k.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_k.Tpo .deps/libta_abstract_la-table_k.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_l.lo -MD -MP -MF .deps/libta_abstract_la-table_l.Tpo -c -o libta_abstract_la-table_l.lo `test -f 'tables/table_l.c' || echo './'`tables/table_l.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_l.lo -MD -MP -MF .deps/libta_abstract_la-table_l.Tpo -c tables/table_l.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_l.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_l.lo -MD -MP -MF .deps/libta_abstract_la-table_l.Tpo -c tables/table_l.c -o libta_abstract_la-table_l.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_l.Tpo .deps/libta_abstract_la-table_l.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_m.lo -MD -MP -MF .deps/libta_abstract_la-table_m.Tpo -c -o libta_abstract_la-table_m.lo `test -f 'tables/table_m.c' || echo './'`tables/table_m.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_m.lo -MD -MP -MF .deps/libta_abstract_la-table_m.Tpo -c tables/table_m.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_m.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_m.lo -MD -MP -MF .deps/libta_abstract_la-table_m.Tpo -c tables/table_m.c -o libta_abstract_la-table_m.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_m.Tpo .deps/libta_abstract_la-table_m.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_n.lo -MD -MP -MF .deps/libta_abstract_la-table_n.Tpo -c -o libta_abstract_la-table_n.lo `test -f 'tables/table_n.c' || echo './'`tables/table_n.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_n.lo -MD -MP -MF .deps/libta_abstract_la-table_n.Tpo -c tables/table_n.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_n.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_n.lo -MD -MP -MF .deps/libta_abstract_la-table_n.Tpo -c tables/table_n.c -o libta_abstract_la-table_n.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_n.Tpo .deps/libta_abstract_la-table_n.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_o.lo -MD -MP -MF .deps/libta_abstract_la-table_o.Tpo -c -o libta_abstract_la-table_o.lo `test -f 'tables/table_o.c' || echo './'`tables/table_o.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_o.lo -MD -MP -MF .deps/libta_abstract_la-table_o.Tpo -c tables/table_o.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_o.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_o.lo -MD -MP -MF .deps/libta_abstract_la-table_o.Tpo -c tables/table_o.c -o libta_abstract_la-table_o.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_o.Tpo .deps/libta_abstract_la-table_o.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_p.lo -MD -MP -MF .deps/libta_abstract_la-table_p.Tpo -c -o libta_abstract_la-table_p.lo `test -f 'tables/table_p.c' || echo './'`tables/table_p.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_p.lo -MD -MP -MF .deps/libta_abstract_la-table_p.Tpo -c tables/table_p.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_p.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_p.lo -MD -MP -MF .deps/libta_abstract_la-table_p.Tpo -c tables/table_p.c -o libta_abstract_la-table_p.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_p.Tpo .deps/libta_abstract_la-table_p.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_q.lo -MD -MP -MF .deps/libta_abstract_la-table_q.Tpo -c -o libta_abstract_la-table_q.lo `test -f 'tables/table_q.c' || echo './'`tables/table_q.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_q.lo -MD -MP -MF .deps/libta_abstract_la-table_q.Tpo -c tables/table_q.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_q.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_q.lo -MD -MP -MF .deps/libta_abstract_la-table_q.Tpo -c tables/table_q.c -o libta_abstract_la-table_q.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_q.Tpo .deps/libta_abstract_la-table_q.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_r.lo -MD -MP -MF .deps/libta_abstract_la-table_r.Tpo -c -o libta_abstract_la-table_r.lo `test -f 'tables/table_r.c' || echo './'`tables/table_r.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_r.lo -MD -MP -MF .deps/libta_abstract_la-table_r.Tpo -c tables/table_r.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_r.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_r.lo -MD -MP -MF .deps/libta_abstract_la-table_r.Tpo -c tables/table_r.c -o libta_abstract_la-table_r.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_r.Tpo .deps/libta_abstract_la-table_r.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_s.lo -MD -MP -MF .deps/libta_abstract_la-table_s.Tpo -c -o libta_abstract_la-table_s.lo `test -f 'tables/table_s.c' || echo './'`tables/table_s.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_s.lo -MD -MP -MF .deps/libta_abstract_la-table_s.Tpo -c tables/table_s.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_s.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_s.lo -MD -MP -MF .deps/libta_abstract_la-table_s.Tpo -c tables/table_s.c -o libta_abstract_la-table_s.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_s.Tpo .deps/libta_abstract_la-table_s.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_t.lo -MD -MP -MF .deps/libta_abstract_la-table_t.Tpo -c -o libta_abstract_la-table_t.lo `test -f 'tables/table_t.c' || echo './'`tables/table_t.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_t.lo -MD -MP -MF .deps/libta_abstract_la-table_t.Tpo -c tables/table_t.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_t.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_t.lo -MD -MP -MF .deps/libta_abstract_la-table_t.Tpo -c tables/table_t.c -o libta_abstract_la-table_t.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_t.Tpo .deps/libta_abstract_la-table_t.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_u.lo -MD -MP -MF .deps/libta_abstract_la-table_u.Tpo -c -o libta_abstract_la-table_u.lo `test -f 'tables/table_u.c' || echo './'`tables/table_u.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_u.lo -MD -MP -MF .deps/libta_abstract_la-table_u.Tpo -c tables/table_u.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_u.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_u.lo -MD -MP -MF .deps/libta_abstract_la-table_u.Tpo -c tables/table_u.c -o libta_abstract_la-table_u.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_u.Tpo .deps/libta_abstract_la-table_u.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_v.lo -MD -MP -MF .deps/libta_abstract_la-table_v.Tpo -c -o libta_abstract_la-table_v.lo `test -f 'tables/table_v.c' || echo './'`tables/table_v.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_v.lo -MD -MP -MF .deps/libta_abstract_la-table_v.Tpo -c tables/table_v.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_v.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_v.lo -MD -MP -MF .deps/libta_abstract_la-table_v.Tpo -c tables/table_v.c -o libta_abstract_la-table_v.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_v.Tpo .deps/libta_abstract_la-table_v.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_w.lo -MD -MP -MF .deps/libta_abstract_la-table_w.Tpo -c -o libta_abstract_la-table_w.lo `test -f 'tables/table_w.c' || echo './'`tables/table_w.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_w.lo -MD -MP -MF .deps/libta_abstract_la-table_w.Tpo -c tables/table_w.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_w.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_w.lo -MD -MP -MF .deps/libta_abstract_la-table_w.Tpo -c tables/table_w.c -o libta_abstract_la-table_w.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_w.Tpo .deps/libta_abstract_la-table_w.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_x.lo -MD -MP -MF .deps/libta_abstract_la-table_x.Tpo -c -o libta_abstract_la-table_x.lo `test -f 'tables/table_x.c' || echo './'`tables/table_x.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_x.lo -MD -MP -MF .deps/libta_abstract_la-table_x.Tpo -c tables/table_x.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_x.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_x.lo -MD -MP -MF .deps/libta_abstract_la-table_x.Tpo -c tables/table_x.c -o libta_abstract_la-table_x.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_x.Tpo .deps/libta_abstract_la-table_x.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_y.lo -MD -MP -MF .deps/libta_abstract_la-table_y.Tpo -c -o libta_abstract_la-table_y.lo `test -f 'tables/table_y.c' || echo './'`tables/table_y.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_y.lo -MD -MP -MF .deps/libta_abstract_la-table_y.Tpo -c tables/table_y.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_y.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_y.lo -MD -MP -MF .deps/libta_abstract_la-table_y.Tpo -c tables/table_y.c -o libta_abstract_la-table_y.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_y.Tpo .deps/libta_abstract_la-table_y.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_la-table_z.lo -MD -MP -MF .deps/libta_abstract_la-table_z.Tpo -c -o libta_abstract_la-table_z.lo `test -f 'tables/table_z.c' || echo './'`tables/table_z.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_z.lo -MD -MP -MF .deps/libta_abstract_la-table_z.Tpo -c tables/table_z.c  -fPIC -DPIC -o .libs/libta_abstract_la-table_z.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_la-table_z.lo -MD -MP -MF .deps/libta_abstract_la-table_z.Tpo -c tables/table_z.c -o libta_abstract_la-table_z.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_la-table_z.Tpo .deps/libta_abstract_la-table_z.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=link gcc  -g -O2 -version-info 0:0:0  -o libta_abstract.la  libta_abstract_la-ta_group_idx.lo libta_abstract_la-ta_def_ui.lo libta_abstract_la-ta_abstract.lo libta_abstract_la-ta_func_api.lo libta_abstract_la-ta_frame.lo libta_abstract_la-table_a.lo libta_abstract_la-table_b.lo libta_abstract_la-table_c.lo libta_abstract_la-table_d.lo libta_abstract_la-table_e.lo libta_abstract_la-table_f.lo libta_abstract_la-table_g.lo libta_abstract_la-table_h.lo libta_abstract_la-table_i.lo libta_abstract_la-table_j.lo libta_abstract_la-table_k.lo libta_abstract_la-table_l.lo libta_abstract_la-table_m.lo libta_abstract_la-table_n.lo libta_abstract_la-table_o.lo libta_abstract_la-table_p.lo libta_abstract_la-table_q.lo libta_abstract_la-table_r.lo libta_abstract_la-table_s.lo libta_abstract_la-table_t.lo libta_abstract_la-table_u.lo libta_abstract_la-table_v.lo libta_abstract_la-table_w.lo libta_abstract_la-table_x.lo libta_abstract_la-table_y.lo libta_abstract_la-table_z.lo  -lpthread -ldl \n",
            "libtool: link: warning: `-version-info/-version-number' is ignored for convenience libraries\n",
            "ar cru .libs/libta_abstract.a .libs/libta_abstract_la-ta_group_idx.o .libs/libta_abstract_la-ta_def_ui.o .libs/libta_abstract_la-ta_abstract.o .libs/libta_abstract_la-ta_func_api.o .libs/libta_abstract_la-ta_frame.o .libs/libta_abstract_la-table_a.o .libs/libta_abstract_la-table_b.o .libs/libta_abstract_la-table_c.o .libs/libta_abstract_la-table_d.o .libs/libta_abstract_la-table_e.o .libs/libta_abstract_la-table_f.o .libs/libta_abstract_la-table_g.o .libs/libta_abstract_la-table_h.o .libs/libta_abstract_la-table_i.o .libs/libta_abstract_la-table_j.o .libs/libta_abstract_la-table_k.o .libs/libta_abstract_la-table_l.o .libs/libta_abstract_la-table_m.o .libs/libta_abstract_la-table_n.o .libs/libta_abstract_la-table_o.o .libs/libta_abstract_la-table_p.o .libs/libta_abstract_la-table_q.o .libs/libta_abstract_la-table_r.o .libs/libta_abstract_la-table_s.o .libs/libta_abstract_la-table_t.o .libs/libta_abstract_la-table_u.o .libs/libta_abstract_la-table_v.o .libs/libta_abstract_la-table_w.o .libs/libta_abstract_la-table_x.o .libs/libta_abstract_la-table_y.o .libs/libta_abstract_la-table_z.o\n",
            "ar: `u' modifier ignored since `D' is the default (see `U')\n",
            "ranlib .libs/libta_abstract.a\n",
            "creating libta_abstract.la\n",
            "(cd .libs && rm -f libta_abstract.la && ln -s ../libta_abstract.la libta_abstract.la)\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-ta_group_idx.lo -MD -MP -MF .deps/libta_abstract_gc_la-ta_group_idx.Tpo -c -o libta_abstract_gc_la-ta_group_idx.lo `test -f 'ta_group_idx.c' || echo './'`ta_group_idx.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-ta_group_idx.lo -MD -MP -MF .deps/libta_abstract_gc_la-ta_group_idx.Tpo -c ta_group_idx.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-ta_group_idx.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-ta_group_idx.lo -MD -MP -MF .deps/libta_abstract_gc_la-ta_group_idx.Tpo -c ta_group_idx.c -o libta_abstract_gc_la-ta_group_idx.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-ta_group_idx.Tpo .deps/libta_abstract_gc_la-ta_group_idx.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-ta_def_ui.lo -MD -MP -MF .deps/libta_abstract_gc_la-ta_def_ui.Tpo -c -o libta_abstract_gc_la-ta_def_ui.lo `test -f 'ta_def_ui.c' || echo './'`ta_def_ui.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-ta_def_ui.lo -MD -MP -MF .deps/libta_abstract_gc_la-ta_def_ui.Tpo -c ta_def_ui.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-ta_def_ui.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-ta_def_ui.lo -MD -MP -MF .deps/libta_abstract_gc_la-ta_def_ui.Tpo -c ta_def_ui.c -o libta_abstract_gc_la-ta_def_ui.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-ta_def_ui.Tpo .deps/libta_abstract_gc_la-ta_def_ui.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-ta_abstract.lo -MD -MP -MF .deps/libta_abstract_gc_la-ta_abstract.Tpo -c -o libta_abstract_gc_la-ta_abstract.lo `test -f 'ta_abstract.c' || echo './'`ta_abstract.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-ta_abstract.lo -MD -MP -MF .deps/libta_abstract_gc_la-ta_abstract.Tpo -c ta_abstract.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-ta_abstract.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-ta_abstract.lo -MD -MP -MF .deps/libta_abstract_gc_la-ta_abstract.Tpo -c ta_abstract.c -o libta_abstract_gc_la-ta_abstract.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-ta_abstract.Tpo .deps/libta_abstract_gc_la-ta_abstract.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-ta_func_api.lo -MD -MP -MF .deps/libta_abstract_gc_la-ta_func_api.Tpo -c -o libta_abstract_gc_la-ta_func_api.lo `test -f 'ta_func_api.c' || echo './'`ta_func_api.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-ta_func_api.lo -MD -MP -MF .deps/libta_abstract_gc_la-ta_func_api.Tpo -c ta_func_api.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-ta_func_api.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-ta_func_api.lo -MD -MP -MF .deps/libta_abstract_gc_la-ta_func_api.Tpo -c ta_func_api.c -o libta_abstract_gc_la-ta_func_api.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-ta_func_api.Tpo .deps/libta_abstract_gc_la-ta_func_api.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-ta_frame.lo -MD -MP -MF .deps/libta_abstract_gc_la-ta_frame.Tpo -c -o libta_abstract_gc_la-ta_frame.lo `test -f 'frames/ta_frame.c' || echo './'`frames/ta_frame.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-ta_frame.lo -MD -MP -MF .deps/libta_abstract_gc_la-ta_frame.Tpo -c frames/ta_frame.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-ta_frame.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-ta_frame.lo -MD -MP -MF .deps/libta_abstract_gc_la-ta_frame.Tpo -c frames/ta_frame.c -o libta_abstract_gc_la-ta_frame.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-ta_frame.Tpo .deps/libta_abstract_gc_la-ta_frame.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_a.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_a.Tpo -c -o libta_abstract_gc_la-table_a.lo `test -f 'tables/table_a.c' || echo './'`tables/table_a.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_a.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_a.Tpo -c tables/table_a.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_a.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_a.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_a.Tpo -c tables/table_a.c -o libta_abstract_gc_la-table_a.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_a.Tpo .deps/libta_abstract_gc_la-table_a.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_b.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_b.Tpo -c -o libta_abstract_gc_la-table_b.lo `test -f 'tables/table_b.c' || echo './'`tables/table_b.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_b.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_b.Tpo -c tables/table_b.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_b.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_b.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_b.Tpo -c tables/table_b.c -o libta_abstract_gc_la-table_b.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_b.Tpo .deps/libta_abstract_gc_la-table_b.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_c.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_c.Tpo -c -o libta_abstract_gc_la-table_c.lo `test -f 'tables/table_c.c' || echo './'`tables/table_c.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_c.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_c.Tpo -c tables/table_c.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_c.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_c.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_c.Tpo -c tables/table_c.c -o libta_abstract_gc_la-table_c.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_c.Tpo .deps/libta_abstract_gc_la-table_c.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_d.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_d.Tpo -c -o libta_abstract_gc_la-table_d.lo `test -f 'tables/table_d.c' || echo './'`tables/table_d.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_d.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_d.Tpo -c tables/table_d.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_d.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_d.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_d.Tpo -c tables/table_d.c -o libta_abstract_gc_la-table_d.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_d.Tpo .deps/libta_abstract_gc_la-table_d.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_e.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_e.Tpo -c -o libta_abstract_gc_la-table_e.lo `test -f 'tables/table_e.c' || echo './'`tables/table_e.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_e.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_e.Tpo -c tables/table_e.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_e.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_e.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_e.Tpo -c tables/table_e.c -o libta_abstract_gc_la-table_e.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_e.Tpo .deps/libta_abstract_gc_la-table_e.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_f.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_f.Tpo -c -o libta_abstract_gc_la-table_f.lo `test -f 'tables/table_f.c' || echo './'`tables/table_f.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_f.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_f.Tpo -c tables/table_f.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_f.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_f.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_f.Tpo -c tables/table_f.c -o libta_abstract_gc_la-table_f.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_f.Tpo .deps/libta_abstract_gc_la-table_f.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_g.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_g.Tpo -c -o libta_abstract_gc_la-table_g.lo `test -f 'tables/table_g.c' || echo './'`tables/table_g.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_g.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_g.Tpo -c tables/table_g.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_g.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_g.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_g.Tpo -c tables/table_g.c -o libta_abstract_gc_la-table_g.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_g.Tpo .deps/libta_abstract_gc_la-table_g.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_h.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_h.Tpo -c -o libta_abstract_gc_la-table_h.lo `test -f 'tables/table_h.c' || echo './'`tables/table_h.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_h.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_h.Tpo -c tables/table_h.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_h.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_h.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_h.Tpo -c tables/table_h.c -o libta_abstract_gc_la-table_h.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_h.Tpo .deps/libta_abstract_gc_la-table_h.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_i.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_i.Tpo -c -o libta_abstract_gc_la-table_i.lo `test -f 'tables/table_i.c' || echo './'`tables/table_i.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_i.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_i.Tpo -c tables/table_i.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_i.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_i.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_i.Tpo -c tables/table_i.c -o libta_abstract_gc_la-table_i.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_i.Tpo .deps/libta_abstract_gc_la-table_i.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_j.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_j.Tpo -c -o libta_abstract_gc_la-table_j.lo `test -f 'tables/table_j.c' || echo './'`tables/table_j.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_j.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_j.Tpo -c tables/table_j.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_j.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_j.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_j.Tpo -c tables/table_j.c -o libta_abstract_gc_la-table_j.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_j.Tpo .deps/libta_abstract_gc_la-table_j.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_k.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_k.Tpo -c -o libta_abstract_gc_la-table_k.lo `test -f 'tables/table_k.c' || echo './'`tables/table_k.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_k.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_k.Tpo -c tables/table_k.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_k.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_k.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_k.Tpo -c tables/table_k.c -o libta_abstract_gc_la-table_k.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_k.Tpo .deps/libta_abstract_gc_la-table_k.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_l.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_l.Tpo -c -o libta_abstract_gc_la-table_l.lo `test -f 'tables/table_l.c' || echo './'`tables/table_l.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_l.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_l.Tpo -c tables/table_l.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_l.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_l.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_l.Tpo -c tables/table_l.c -o libta_abstract_gc_la-table_l.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_l.Tpo .deps/libta_abstract_gc_la-table_l.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_m.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_m.Tpo -c -o libta_abstract_gc_la-table_m.lo `test -f 'tables/table_m.c' || echo './'`tables/table_m.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_m.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_m.Tpo -c tables/table_m.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_m.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_m.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_m.Tpo -c tables/table_m.c -o libta_abstract_gc_la-table_m.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_m.Tpo .deps/libta_abstract_gc_la-table_m.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_n.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_n.Tpo -c -o libta_abstract_gc_la-table_n.lo `test -f 'tables/table_n.c' || echo './'`tables/table_n.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_n.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_n.Tpo -c tables/table_n.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_n.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_n.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_n.Tpo -c tables/table_n.c -o libta_abstract_gc_la-table_n.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_n.Tpo .deps/libta_abstract_gc_la-table_n.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_o.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_o.Tpo -c -o libta_abstract_gc_la-table_o.lo `test -f 'tables/table_o.c' || echo './'`tables/table_o.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_o.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_o.Tpo -c tables/table_o.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_o.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_o.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_o.Tpo -c tables/table_o.c -o libta_abstract_gc_la-table_o.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_o.Tpo .deps/libta_abstract_gc_la-table_o.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_p.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_p.Tpo -c -o libta_abstract_gc_la-table_p.lo `test -f 'tables/table_p.c' || echo './'`tables/table_p.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_p.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_p.Tpo -c tables/table_p.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_p.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_p.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_p.Tpo -c tables/table_p.c -o libta_abstract_gc_la-table_p.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_p.Tpo .deps/libta_abstract_gc_la-table_p.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_q.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_q.Tpo -c -o libta_abstract_gc_la-table_q.lo `test -f 'tables/table_q.c' || echo './'`tables/table_q.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_q.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_q.Tpo -c tables/table_q.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_q.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_q.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_q.Tpo -c tables/table_q.c -o libta_abstract_gc_la-table_q.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_q.Tpo .deps/libta_abstract_gc_la-table_q.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_r.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_r.Tpo -c -o libta_abstract_gc_la-table_r.lo `test -f 'tables/table_r.c' || echo './'`tables/table_r.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_r.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_r.Tpo -c tables/table_r.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_r.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_r.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_r.Tpo -c tables/table_r.c -o libta_abstract_gc_la-table_r.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_r.Tpo .deps/libta_abstract_gc_la-table_r.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_s.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_s.Tpo -c -o libta_abstract_gc_la-table_s.lo `test -f 'tables/table_s.c' || echo './'`tables/table_s.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_s.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_s.Tpo -c tables/table_s.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_s.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_s.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_s.Tpo -c tables/table_s.c -o libta_abstract_gc_la-table_s.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_s.Tpo .deps/libta_abstract_gc_la-table_s.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_t.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_t.Tpo -c -o libta_abstract_gc_la-table_t.lo `test -f 'tables/table_t.c' || echo './'`tables/table_t.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_t.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_t.Tpo -c tables/table_t.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_t.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_t.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_t.Tpo -c tables/table_t.c -o libta_abstract_gc_la-table_t.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_t.Tpo .deps/libta_abstract_gc_la-table_t.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_u.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_u.Tpo -c -o libta_abstract_gc_la-table_u.lo `test -f 'tables/table_u.c' || echo './'`tables/table_u.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_u.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_u.Tpo -c tables/table_u.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_u.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_u.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_u.Tpo -c tables/table_u.c -o libta_abstract_gc_la-table_u.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_u.Tpo .deps/libta_abstract_gc_la-table_u.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_v.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_v.Tpo -c -o libta_abstract_gc_la-table_v.lo `test -f 'tables/table_v.c' || echo './'`tables/table_v.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_v.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_v.Tpo -c tables/table_v.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_v.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_v.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_v.Tpo -c tables/table_v.c -o libta_abstract_gc_la-table_v.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_v.Tpo .deps/libta_abstract_gc_la-table_v.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_w.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_w.Tpo -c -o libta_abstract_gc_la-table_w.lo `test -f 'tables/table_w.c' || echo './'`tables/table_w.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_w.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_w.Tpo -c tables/table_w.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_w.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_w.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_w.Tpo -c tables/table_w.c -o libta_abstract_gc_la-table_w.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_w.Tpo .deps/libta_abstract_gc_la-table_w.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_x.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_x.Tpo -c -o libta_abstract_gc_la-table_x.lo `test -f 'tables/table_x.c' || echo './'`tables/table_x.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_x.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_x.Tpo -c tables/table_x.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_x.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_x.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_x.Tpo -c tables/table_x.c -o libta_abstract_gc_la-table_x.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_x.Tpo .deps/libta_abstract_gc_la-table_x.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_y.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_y.Tpo -c -o libta_abstract_gc_la-table_y.lo `test -f 'tables/table_y.c' || echo './'`tables/table_y.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_y.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_y.Tpo -c tables/table_y.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_y.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_y.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_y.Tpo -c tables/table_y.c -o libta_abstract_gc_la-table_y.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_y.Tpo .deps/libta_abstract_gc_la-table_y.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -DTA_GEN_CODE -I../ta_common/ -Iframes/   -g -O2 -MT libta_abstract_gc_la-table_z.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_z.Tpo -c -o libta_abstract_gc_la-table_z.lo `test -f 'tables/table_z.c' || echo './'`tables/table_z.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_z.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_z.Tpo -c tables/table_z.c  -fPIC -DPIC -o .libs/libta_abstract_gc_la-table_z.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -DTA_GEN_CODE -I../ta_common/ -Iframes/ -g -O2 -MT libta_abstract_gc_la-table_z.lo -MD -MP -MF .deps/libta_abstract_gc_la-table_z.Tpo -c tables/table_z.c -o libta_abstract_gc_la-table_z.o >/dev/null 2>&1\n",
            "mv -f .deps/libta_abstract_gc_la-table_z.Tpo .deps/libta_abstract_gc_la-table_z.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=link gcc  -g -O2 -version-info 0:0:0  -o libta_abstract_gc.la  libta_abstract_gc_la-ta_group_idx.lo libta_abstract_gc_la-ta_def_ui.lo libta_abstract_gc_la-ta_abstract.lo libta_abstract_gc_la-ta_func_api.lo libta_abstract_gc_la-ta_frame.lo libta_abstract_gc_la-table_a.lo libta_abstract_gc_la-table_b.lo libta_abstract_gc_la-table_c.lo libta_abstract_gc_la-table_d.lo libta_abstract_gc_la-table_e.lo libta_abstract_gc_la-table_f.lo libta_abstract_gc_la-table_g.lo libta_abstract_gc_la-table_h.lo libta_abstract_gc_la-table_i.lo libta_abstract_gc_la-table_j.lo libta_abstract_gc_la-table_k.lo libta_abstract_gc_la-table_l.lo libta_abstract_gc_la-table_m.lo libta_abstract_gc_la-table_n.lo libta_abstract_gc_la-table_o.lo libta_abstract_gc_la-table_p.lo libta_abstract_gc_la-table_q.lo libta_abstract_gc_la-table_r.lo libta_abstract_gc_la-table_s.lo libta_abstract_gc_la-table_t.lo libta_abstract_gc_la-table_u.lo libta_abstract_gc_la-table_v.lo libta_abstract_gc_la-table_w.lo libta_abstract_gc_la-table_x.lo libta_abstract_gc_la-table_y.lo libta_abstract_gc_la-table_z.lo  -lpthread -ldl \n",
            "libtool: link: warning: `-version-info/-version-number' is ignored for convenience libraries\n",
            "ar cru .libs/libta_abstract_gc.a .libs/libta_abstract_gc_la-ta_group_idx.o .libs/libta_abstract_gc_la-ta_def_ui.o .libs/libta_abstract_gc_la-ta_abstract.o .libs/libta_abstract_gc_la-ta_func_api.o .libs/libta_abstract_gc_la-ta_frame.o .libs/libta_abstract_gc_la-table_a.o .libs/libta_abstract_gc_la-table_b.o .libs/libta_abstract_gc_la-table_c.o .libs/libta_abstract_gc_la-table_d.o .libs/libta_abstract_gc_la-table_e.o .libs/libta_abstract_gc_la-table_f.o .libs/libta_abstract_gc_la-table_g.o .libs/libta_abstract_gc_la-table_h.o .libs/libta_abstract_gc_la-table_i.o .libs/libta_abstract_gc_la-table_j.o .libs/libta_abstract_gc_la-table_k.o .libs/libta_abstract_gc_la-table_l.o .libs/libta_abstract_gc_la-table_m.o .libs/libta_abstract_gc_la-table_n.o .libs/libta_abstract_gc_la-table_o.o .libs/libta_abstract_gc_la-table_p.o .libs/libta_abstract_gc_la-table_q.o .libs/libta_abstract_gc_la-table_r.o .libs/libta_abstract_gc_la-table_s.o .libs/libta_abstract_gc_la-table_t.o .libs/libta_abstract_gc_la-table_u.o .libs/libta_abstract_gc_la-table_v.o .libs/libta_abstract_gc_la-table_w.o .libs/libta_abstract_gc_la-table_x.o .libs/libta_abstract_gc_la-table_y.o .libs/libta_abstract_gc_la-table_z.o\n",
            "ar: `u' modifier ignored since `D' is the default (see `U')\n",
            "ranlib .libs/libta_abstract_gc.a\n",
            "creating libta_abstract_gc.la\n",
            "(cd .libs && rm -f libta_abstract_gc.la && ln -s ../libta_abstract_gc.la libta_abstract_gc.la)\n",
            "make[2]: Leaving directory '/content/ta-lib/src/ta_abstract'\n",
            "Making all in ta_common\n",
            "make[2]: Entering directory '/content/ta-lib/src/ta_common'\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_global.lo -MD -MP -MF .deps/ta_global.Tpo -c -o ta_global.lo ta_global.c\n",
            "mkdir .libs\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_global.lo -MD -MP -MF .deps/ta_global.Tpo -c ta_global.c  -fPIC -DPIC -o .libs/ta_global.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_global.lo -MD -MP -MF .deps/ta_global.Tpo -c ta_global.c -o ta_global.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_global.Tpo .deps/ta_global.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_retcode.lo -MD -MP -MF .deps/ta_retcode.Tpo -c -o ta_retcode.lo ta_retcode.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_retcode.lo -MD -MP -MF .deps/ta_retcode.Tpo -c ta_retcode.c  -fPIC -DPIC -o .libs/ta_retcode.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_retcode.lo -MD -MP -MF .deps/ta_retcode.Tpo -c ta_retcode.c -o ta_retcode.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_retcode.Tpo .deps/ta_retcode.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_version.lo -MD -MP -MF .deps/ta_version.Tpo -c -o ta_version.lo ta_version.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_version.lo -MD -MP -MF .deps/ta_version.Tpo -c ta_version.c  -fPIC -DPIC -o .libs/ta_version.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_version.lo -MD -MP -MF .deps/ta_version.Tpo -c ta_version.c -o ta_version.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_version.Tpo .deps/ta_version.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=link gcc  -g -O2 -version-info 0:0:0  -o libta_common.la  ta_global.lo ta_retcode.lo ta_version.lo  -lpthread -ldl \n",
            "libtool: link: warning: `-version-info/-version-number' is ignored for convenience libraries\n",
            "ar cru .libs/libta_common.a .libs/ta_global.o .libs/ta_retcode.o .libs/ta_version.o\n",
            "ar: `u' modifier ignored since `D' is the default (see `U')\n",
            "ranlib .libs/libta_common.a\n",
            "creating libta_common.la\n",
            "(cd .libs && rm -f libta_common.la && ln -s ../libta_common.la libta_common.la)\n",
            "make[2]: Leaving directory '/content/ta-lib/src/ta_common'\n",
            "Making all in ta_func\n",
            "make[2]: Entering directory '/content/ta-lib/src/ta_func'\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_utility.lo -MD -MP -MF .deps/ta_utility.Tpo -c -o ta_utility.lo ta_utility.c\n",
            "mkdir .libs\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_utility.lo -MD -MP -MF .deps/ta_utility.Tpo -c ta_utility.c  -fPIC -DPIC -o .libs/ta_utility.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_utility.lo -MD -MP -MF .deps/ta_utility.Tpo -c ta_utility.c -o ta_utility.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_utility.Tpo .deps/ta_utility.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_ACOS.lo -MD -MP -MF .deps/ta_ACOS.Tpo -c -o ta_ACOS.lo ta_ACOS.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ACOS.lo -MD -MP -MF .deps/ta_ACOS.Tpo -c ta_ACOS.c  -fPIC -DPIC -o .libs/ta_ACOS.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ACOS.lo -MD -MP -MF .deps/ta_ACOS.Tpo -c ta_ACOS.c -o ta_ACOS.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_ACOS.Tpo .deps/ta_ACOS.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_AD.lo -MD -MP -MF .deps/ta_AD.Tpo -c -o ta_AD.lo ta_AD.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_AD.lo -MD -MP -MF .deps/ta_AD.Tpo -c ta_AD.c  -fPIC -DPIC -o .libs/ta_AD.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_AD.lo -MD -MP -MF .deps/ta_AD.Tpo -c ta_AD.c -o ta_AD.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_AD.Tpo .deps/ta_AD.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_ADD.lo -MD -MP -MF .deps/ta_ADD.Tpo -c -o ta_ADD.lo ta_ADD.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ADD.lo -MD -MP -MF .deps/ta_ADD.Tpo -c ta_ADD.c  -fPIC -DPIC -o .libs/ta_ADD.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ADD.lo -MD -MP -MF .deps/ta_ADD.Tpo -c ta_ADD.c -o ta_ADD.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_ADD.Tpo .deps/ta_ADD.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_ADOSC.lo -MD -MP -MF .deps/ta_ADOSC.Tpo -c -o ta_ADOSC.lo ta_ADOSC.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ADOSC.lo -MD -MP -MF .deps/ta_ADOSC.Tpo -c ta_ADOSC.c  -fPIC -DPIC -o .libs/ta_ADOSC.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ADOSC.lo -MD -MP -MF .deps/ta_ADOSC.Tpo -c ta_ADOSC.c -o ta_ADOSC.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_ADOSC.Tpo .deps/ta_ADOSC.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_ADX.lo -MD -MP -MF .deps/ta_ADX.Tpo -c -o ta_ADX.lo ta_ADX.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ADX.lo -MD -MP -MF .deps/ta_ADX.Tpo -c ta_ADX.c  -fPIC -DPIC -o .libs/ta_ADX.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ADX.lo -MD -MP -MF .deps/ta_ADX.Tpo -c ta_ADX.c -o ta_ADX.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_ADX.Tpo .deps/ta_ADX.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_ADXR.lo -MD -MP -MF .deps/ta_ADXR.Tpo -c -o ta_ADXR.lo ta_ADXR.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ADXR.lo -MD -MP -MF .deps/ta_ADXR.Tpo -c ta_ADXR.c  -fPIC -DPIC -o .libs/ta_ADXR.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ADXR.lo -MD -MP -MF .deps/ta_ADXR.Tpo -c ta_ADXR.c -o ta_ADXR.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_ADXR.Tpo .deps/ta_ADXR.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_APO.lo -MD -MP -MF .deps/ta_APO.Tpo -c -o ta_APO.lo ta_APO.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_APO.lo -MD -MP -MF .deps/ta_APO.Tpo -c ta_APO.c  -fPIC -DPIC -o .libs/ta_APO.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_APO.lo -MD -MP -MF .deps/ta_APO.Tpo -c ta_APO.c -o ta_APO.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_APO.Tpo .deps/ta_APO.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_AROON.lo -MD -MP -MF .deps/ta_AROON.Tpo -c -o ta_AROON.lo ta_AROON.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_AROON.lo -MD -MP -MF .deps/ta_AROON.Tpo -c ta_AROON.c  -fPIC -DPIC -o .libs/ta_AROON.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_AROON.lo -MD -MP -MF .deps/ta_AROON.Tpo -c ta_AROON.c -o ta_AROON.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_AROON.Tpo .deps/ta_AROON.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_AROONOSC.lo -MD -MP -MF .deps/ta_AROONOSC.Tpo -c -o ta_AROONOSC.lo ta_AROONOSC.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_AROONOSC.lo -MD -MP -MF .deps/ta_AROONOSC.Tpo -c ta_AROONOSC.c  -fPIC -DPIC -o .libs/ta_AROONOSC.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_AROONOSC.lo -MD -MP -MF .deps/ta_AROONOSC.Tpo -c ta_AROONOSC.c -o ta_AROONOSC.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_AROONOSC.Tpo .deps/ta_AROONOSC.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_ASIN.lo -MD -MP -MF .deps/ta_ASIN.Tpo -c -o ta_ASIN.lo ta_ASIN.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ASIN.lo -MD -MP -MF .deps/ta_ASIN.Tpo -c ta_ASIN.c  -fPIC -DPIC -o .libs/ta_ASIN.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ASIN.lo -MD -MP -MF .deps/ta_ASIN.Tpo -c ta_ASIN.c -o ta_ASIN.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_ASIN.Tpo .deps/ta_ASIN.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_ATAN.lo -MD -MP -MF .deps/ta_ATAN.Tpo -c -o ta_ATAN.lo ta_ATAN.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ATAN.lo -MD -MP -MF .deps/ta_ATAN.Tpo -c ta_ATAN.c  -fPIC -DPIC -o .libs/ta_ATAN.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ATAN.lo -MD -MP -MF .deps/ta_ATAN.Tpo -c ta_ATAN.c -o ta_ATAN.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_ATAN.Tpo .deps/ta_ATAN.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_ATR.lo -MD -MP -MF .deps/ta_ATR.Tpo -c -o ta_ATR.lo ta_ATR.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ATR.lo -MD -MP -MF .deps/ta_ATR.Tpo -c ta_ATR.c  -fPIC -DPIC -o .libs/ta_ATR.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ATR.lo -MD -MP -MF .deps/ta_ATR.Tpo -c ta_ATR.c -o ta_ATR.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_ATR.Tpo .deps/ta_ATR.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_AVGPRICE.lo -MD -MP -MF .deps/ta_AVGPRICE.Tpo -c -o ta_AVGPRICE.lo ta_AVGPRICE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_AVGPRICE.lo -MD -MP -MF .deps/ta_AVGPRICE.Tpo -c ta_AVGPRICE.c  -fPIC -DPIC -o .libs/ta_AVGPRICE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_AVGPRICE.lo -MD -MP -MF .deps/ta_AVGPRICE.Tpo -c ta_AVGPRICE.c -o ta_AVGPRICE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_AVGPRICE.Tpo .deps/ta_AVGPRICE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_BBANDS.lo -MD -MP -MF .deps/ta_BBANDS.Tpo -c -o ta_BBANDS.lo ta_BBANDS.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_BBANDS.lo -MD -MP -MF .deps/ta_BBANDS.Tpo -c ta_BBANDS.c  -fPIC -DPIC -o .libs/ta_BBANDS.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_BBANDS.lo -MD -MP -MF .deps/ta_BBANDS.Tpo -c ta_BBANDS.c -o ta_BBANDS.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_BBANDS.Tpo .deps/ta_BBANDS.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_BETA.lo -MD -MP -MF .deps/ta_BETA.Tpo -c -o ta_BETA.lo ta_BETA.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_BETA.lo -MD -MP -MF .deps/ta_BETA.Tpo -c ta_BETA.c  -fPIC -DPIC -o .libs/ta_BETA.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_BETA.lo -MD -MP -MF .deps/ta_BETA.Tpo -c ta_BETA.c -o ta_BETA.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_BETA.Tpo .deps/ta_BETA.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_BOP.lo -MD -MP -MF .deps/ta_BOP.Tpo -c -o ta_BOP.lo ta_BOP.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_BOP.lo -MD -MP -MF .deps/ta_BOP.Tpo -c ta_BOP.c  -fPIC -DPIC -o .libs/ta_BOP.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_BOP.lo -MD -MP -MF .deps/ta_BOP.Tpo -c ta_BOP.c -o ta_BOP.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_BOP.Tpo .deps/ta_BOP.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CCI.lo -MD -MP -MF .deps/ta_CCI.Tpo -c -o ta_CCI.lo ta_CCI.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CCI.lo -MD -MP -MF .deps/ta_CCI.Tpo -c ta_CCI.c  -fPIC -DPIC -o .libs/ta_CCI.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CCI.lo -MD -MP -MF .deps/ta_CCI.Tpo -c ta_CCI.c -o ta_CCI.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CCI.Tpo .deps/ta_CCI.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDL2CROWS.lo -MD -MP -MF .deps/ta_CDL2CROWS.Tpo -c -o ta_CDL2CROWS.lo ta_CDL2CROWS.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDL2CROWS.lo -MD -MP -MF .deps/ta_CDL2CROWS.Tpo -c ta_CDL2CROWS.c  -fPIC -DPIC -o .libs/ta_CDL2CROWS.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDL2CROWS.lo -MD -MP -MF .deps/ta_CDL2CROWS.Tpo -c ta_CDL2CROWS.c -o ta_CDL2CROWS.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDL2CROWS.Tpo .deps/ta_CDL2CROWS.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDL3BLACKCROWS.lo -MD -MP -MF .deps/ta_CDL3BLACKCROWS.Tpo -c -o ta_CDL3BLACKCROWS.lo ta_CDL3BLACKCROWS.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDL3BLACKCROWS.lo -MD -MP -MF .deps/ta_CDL3BLACKCROWS.Tpo -c ta_CDL3BLACKCROWS.c  -fPIC -DPIC -o .libs/ta_CDL3BLACKCROWS.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDL3BLACKCROWS.lo -MD -MP -MF .deps/ta_CDL3BLACKCROWS.Tpo -c ta_CDL3BLACKCROWS.c -o ta_CDL3BLACKCROWS.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDL3BLACKCROWS.Tpo .deps/ta_CDL3BLACKCROWS.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDL3INSIDE.lo -MD -MP -MF .deps/ta_CDL3INSIDE.Tpo -c -o ta_CDL3INSIDE.lo ta_CDL3INSIDE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDL3INSIDE.lo -MD -MP -MF .deps/ta_CDL3INSIDE.Tpo -c ta_CDL3INSIDE.c  -fPIC -DPIC -o .libs/ta_CDL3INSIDE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDL3INSIDE.lo -MD -MP -MF .deps/ta_CDL3INSIDE.Tpo -c ta_CDL3INSIDE.c -o ta_CDL3INSIDE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDL3INSIDE.Tpo .deps/ta_CDL3INSIDE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDL3LINESTRIKE.lo -MD -MP -MF .deps/ta_CDL3LINESTRIKE.Tpo -c -o ta_CDL3LINESTRIKE.lo ta_CDL3LINESTRIKE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDL3LINESTRIKE.lo -MD -MP -MF .deps/ta_CDL3LINESTRIKE.Tpo -c ta_CDL3LINESTRIKE.c  -fPIC -DPIC -o .libs/ta_CDL3LINESTRIKE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDL3LINESTRIKE.lo -MD -MP -MF .deps/ta_CDL3LINESTRIKE.Tpo -c ta_CDL3LINESTRIKE.c -o ta_CDL3LINESTRIKE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDL3LINESTRIKE.Tpo .deps/ta_CDL3LINESTRIKE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDL3OUTSIDE.lo -MD -MP -MF .deps/ta_CDL3OUTSIDE.Tpo -c -o ta_CDL3OUTSIDE.lo ta_CDL3OUTSIDE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDL3OUTSIDE.lo -MD -MP -MF .deps/ta_CDL3OUTSIDE.Tpo -c ta_CDL3OUTSIDE.c  -fPIC -DPIC -o .libs/ta_CDL3OUTSIDE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDL3OUTSIDE.lo -MD -MP -MF .deps/ta_CDL3OUTSIDE.Tpo -c ta_CDL3OUTSIDE.c -o ta_CDL3OUTSIDE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDL3OUTSIDE.Tpo .deps/ta_CDL3OUTSIDE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDL3STARSINSOUTH.lo -MD -MP -MF .deps/ta_CDL3STARSINSOUTH.Tpo -c -o ta_CDL3STARSINSOUTH.lo ta_CDL3STARSINSOUTH.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDL3STARSINSOUTH.lo -MD -MP -MF .deps/ta_CDL3STARSINSOUTH.Tpo -c ta_CDL3STARSINSOUTH.c  -fPIC -DPIC -o .libs/ta_CDL3STARSINSOUTH.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDL3STARSINSOUTH.lo -MD -MP -MF .deps/ta_CDL3STARSINSOUTH.Tpo -c ta_CDL3STARSINSOUTH.c -o ta_CDL3STARSINSOUTH.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDL3STARSINSOUTH.Tpo .deps/ta_CDL3STARSINSOUTH.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDL3WHITESOLDIERS.lo -MD -MP -MF .deps/ta_CDL3WHITESOLDIERS.Tpo -c -o ta_CDL3WHITESOLDIERS.lo ta_CDL3WHITESOLDIERS.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDL3WHITESOLDIERS.lo -MD -MP -MF .deps/ta_CDL3WHITESOLDIERS.Tpo -c ta_CDL3WHITESOLDIERS.c  -fPIC -DPIC -o .libs/ta_CDL3WHITESOLDIERS.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDL3WHITESOLDIERS.lo -MD -MP -MF .deps/ta_CDL3WHITESOLDIERS.Tpo -c ta_CDL3WHITESOLDIERS.c -o ta_CDL3WHITESOLDIERS.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDL3WHITESOLDIERS.Tpo .deps/ta_CDL3WHITESOLDIERS.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLABANDONEDBABY.lo -MD -MP -MF .deps/ta_CDLABANDONEDBABY.Tpo -c -o ta_CDLABANDONEDBABY.lo ta_CDLABANDONEDBABY.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLABANDONEDBABY.lo -MD -MP -MF .deps/ta_CDLABANDONEDBABY.Tpo -c ta_CDLABANDONEDBABY.c  -fPIC -DPIC -o .libs/ta_CDLABANDONEDBABY.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLABANDONEDBABY.lo -MD -MP -MF .deps/ta_CDLABANDONEDBABY.Tpo -c ta_CDLABANDONEDBABY.c -o ta_CDLABANDONEDBABY.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLABANDONEDBABY.Tpo .deps/ta_CDLABANDONEDBABY.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLADVANCEBLOCK.lo -MD -MP -MF .deps/ta_CDLADVANCEBLOCK.Tpo -c -o ta_CDLADVANCEBLOCK.lo ta_CDLADVANCEBLOCK.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLADVANCEBLOCK.lo -MD -MP -MF .deps/ta_CDLADVANCEBLOCK.Tpo -c ta_CDLADVANCEBLOCK.c  -fPIC -DPIC -o .libs/ta_CDLADVANCEBLOCK.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLADVANCEBLOCK.lo -MD -MP -MF .deps/ta_CDLADVANCEBLOCK.Tpo -c ta_CDLADVANCEBLOCK.c -o ta_CDLADVANCEBLOCK.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLADVANCEBLOCK.Tpo .deps/ta_CDLADVANCEBLOCK.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLBELTHOLD.lo -MD -MP -MF .deps/ta_CDLBELTHOLD.Tpo -c -o ta_CDLBELTHOLD.lo ta_CDLBELTHOLD.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLBELTHOLD.lo -MD -MP -MF .deps/ta_CDLBELTHOLD.Tpo -c ta_CDLBELTHOLD.c  -fPIC -DPIC -o .libs/ta_CDLBELTHOLD.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLBELTHOLD.lo -MD -MP -MF .deps/ta_CDLBELTHOLD.Tpo -c ta_CDLBELTHOLD.c -o ta_CDLBELTHOLD.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLBELTHOLD.Tpo .deps/ta_CDLBELTHOLD.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLBREAKAWAY.lo -MD -MP -MF .deps/ta_CDLBREAKAWAY.Tpo -c -o ta_CDLBREAKAWAY.lo ta_CDLBREAKAWAY.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLBREAKAWAY.lo -MD -MP -MF .deps/ta_CDLBREAKAWAY.Tpo -c ta_CDLBREAKAWAY.c  -fPIC -DPIC -o .libs/ta_CDLBREAKAWAY.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLBREAKAWAY.lo -MD -MP -MF .deps/ta_CDLBREAKAWAY.Tpo -c ta_CDLBREAKAWAY.c -o ta_CDLBREAKAWAY.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLBREAKAWAY.Tpo .deps/ta_CDLBREAKAWAY.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLCLOSINGMARUBOZU.lo -MD -MP -MF .deps/ta_CDLCLOSINGMARUBOZU.Tpo -c -o ta_CDLCLOSINGMARUBOZU.lo ta_CDLCLOSINGMARUBOZU.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLCLOSINGMARUBOZU.lo -MD -MP -MF .deps/ta_CDLCLOSINGMARUBOZU.Tpo -c ta_CDLCLOSINGMARUBOZU.c  -fPIC -DPIC -o .libs/ta_CDLCLOSINGMARUBOZU.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLCLOSINGMARUBOZU.lo -MD -MP -MF .deps/ta_CDLCLOSINGMARUBOZU.Tpo -c ta_CDLCLOSINGMARUBOZU.c -o ta_CDLCLOSINGMARUBOZU.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLCLOSINGMARUBOZU.Tpo .deps/ta_CDLCLOSINGMARUBOZU.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLCONCEALBABYSWALL.lo -MD -MP -MF .deps/ta_CDLCONCEALBABYSWALL.Tpo -c -o ta_CDLCONCEALBABYSWALL.lo ta_CDLCONCEALBABYSWALL.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLCONCEALBABYSWALL.lo -MD -MP -MF .deps/ta_CDLCONCEALBABYSWALL.Tpo -c ta_CDLCONCEALBABYSWALL.c  -fPIC -DPIC -o .libs/ta_CDLCONCEALBABYSWALL.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLCONCEALBABYSWALL.lo -MD -MP -MF .deps/ta_CDLCONCEALBABYSWALL.Tpo -c ta_CDLCONCEALBABYSWALL.c -o ta_CDLCONCEALBABYSWALL.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLCONCEALBABYSWALL.Tpo .deps/ta_CDLCONCEALBABYSWALL.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLCOUNTERATTACK.lo -MD -MP -MF .deps/ta_CDLCOUNTERATTACK.Tpo -c -o ta_CDLCOUNTERATTACK.lo ta_CDLCOUNTERATTACK.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLCOUNTERATTACK.lo -MD -MP -MF .deps/ta_CDLCOUNTERATTACK.Tpo -c ta_CDLCOUNTERATTACK.c  -fPIC -DPIC -o .libs/ta_CDLCOUNTERATTACK.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLCOUNTERATTACK.lo -MD -MP -MF .deps/ta_CDLCOUNTERATTACK.Tpo -c ta_CDLCOUNTERATTACK.c -o ta_CDLCOUNTERATTACK.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLCOUNTERATTACK.Tpo .deps/ta_CDLCOUNTERATTACK.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLDARKCLOUDCOVER.lo -MD -MP -MF .deps/ta_CDLDARKCLOUDCOVER.Tpo -c -o ta_CDLDARKCLOUDCOVER.lo ta_CDLDARKCLOUDCOVER.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLDARKCLOUDCOVER.lo -MD -MP -MF .deps/ta_CDLDARKCLOUDCOVER.Tpo -c ta_CDLDARKCLOUDCOVER.c  -fPIC -DPIC -o .libs/ta_CDLDARKCLOUDCOVER.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLDARKCLOUDCOVER.lo -MD -MP -MF .deps/ta_CDLDARKCLOUDCOVER.Tpo -c ta_CDLDARKCLOUDCOVER.c -o ta_CDLDARKCLOUDCOVER.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLDARKCLOUDCOVER.Tpo .deps/ta_CDLDARKCLOUDCOVER.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLDOJI.lo -MD -MP -MF .deps/ta_CDLDOJI.Tpo -c -o ta_CDLDOJI.lo ta_CDLDOJI.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLDOJI.lo -MD -MP -MF .deps/ta_CDLDOJI.Tpo -c ta_CDLDOJI.c  -fPIC -DPIC -o .libs/ta_CDLDOJI.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLDOJI.lo -MD -MP -MF .deps/ta_CDLDOJI.Tpo -c ta_CDLDOJI.c -o ta_CDLDOJI.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLDOJI.Tpo .deps/ta_CDLDOJI.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLDOJISTAR.lo -MD -MP -MF .deps/ta_CDLDOJISTAR.Tpo -c -o ta_CDLDOJISTAR.lo ta_CDLDOJISTAR.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLDOJISTAR.lo -MD -MP -MF .deps/ta_CDLDOJISTAR.Tpo -c ta_CDLDOJISTAR.c  -fPIC -DPIC -o .libs/ta_CDLDOJISTAR.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLDOJISTAR.lo -MD -MP -MF .deps/ta_CDLDOJISTAR.Tpo -c ta_CDLDOJISTAR.c -o ta_CDLDOJISTAR.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLDOJISTAR.Tpo .deps/ta_CDLDOJISTAR.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLDRAGONFLYDOJI.lo -MD -MP -MF .deps/ta_CDLDRAGONFLYDOJI.Tpo -c -o ta_CDLDRAGONFLYDOJI.lo ta_CDLDRAGONFLYDOJI.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLDRAGONFLYDOJI.lo -MD -MP -MF .deps/ta_CDLDRAGONFLYDOJI.Tpo -c ta_CDLDRAGONFLYDOJI.c  -fPIC -DPIC -o .libs/ta_CDLDRAGONFLYDOJI.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLDRAGONFLYDOJI.lo -MD -MP -MF .deps/ta_CDLDRAGONFLYDOJI.Tpo -c ta_CDLDRAGONFLYDOJI.c -o ta_CDLDRAGONFLYDOJI.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLDRAGONFLYDOJI.Tpo .deps/ta_CDLDRAGONFLYDOJI.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLENGULFING.lo -MD -MP -MF .deps/ta_CDLENGULFING.Tpo -c -o ta_CDLENGULFING.lo ta_CDLENGULFING.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLENGULFING.lo -MD -MP -MF .deps/ta_CDLENGULFING.Tpo -c ta_CDLENGULFING.c  -fPIC -DPIC -o .libs/ta_CDLENGULFING.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLENGULFING.lo -MD -MP -MF .deps/ta_CDLENGULFING.Tpo -c ta_CDLENGULFING.c -o ta_CDLENGULFING.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLENGULFING.Tpo .deps/ta_CDLENGULFING.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLEVENINGDOJISTAR.lo -MD -MP -MF .deps/ta_CDLEVENINGDOJISTAR.Tpo -c -o ta_CDLEVENINGDOJISTAR.lo ta_CDLEVENINGDOJISTAR.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLEVENINGDOJISTAR.lo -MD -MP -MF .deps/ta_CDLEVENINGDOJISTAR.Tpo -c ta_CDLEVENINGDOJISTAR.c  -fPIC -DPIC -o .libs/ta_CDLEVENINGDOJISTAR.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLEVENINGDOJISTAR.lo -MD -MP -MF .deps/ta_CDLEVENINGDOJISTAR.Tpo -c ta_CDLEVENINGDOJISTAR.c -o ta_CDLEVENINGDOJISTAR.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLEVENINGDOJISTAR.Tpo .deps/ta_CDLEVENINGDOJISTAR.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLEVENINGSTAR.lo -MD -MP -MF .deps/ta_CDLEVENINGSTAR.Tpo -c -o ta_CDLEVENINGSTAR.lo ta_CDLEVENINGSTAR.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLEVENINGSTAR.lo -MD -MP -MF .deps/ta_CDLEVENINGSTAR.Tpo -c ta_CDLEVENINGSTAR.c  -fPIC -DPIC -o .libs/ta_CDLEVENINGSTAR.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLEVENINGSTAR.lo -MD -MP -MF .deps/ta_CDLEVENINGSTAR.Tpo -c ta_CDLEVENINGSTAR.c -o ta_CDLEVENINGSTAR.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLEVENINGSTAR.Tpo .deps/ta_CDLEVENINGSTAR.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLGAPSIDESIDEWHITE.lo -MD -MP -MF .deps/ta_CDLGAPSIDESIDEWHITE.Tpo -c -o ta_CDLGAPSIDESIDEWHITE.lo ta_CDLGAPSIDESIDEWHITE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLGAPSIDESIDEWHITE.lo -MD -MP -MF .deps/ta_CDLGAPSIDESIDEWHITE.Tpo -c ta_CDLGAPSIDESIDEWHITE.c  -fPIC -DPIC -o .libs/ta_CDLGAPSIDESIDEWHITE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLGAPSIDESIDEWHITE.lo -MD -MP -MF .deps/ta_CDLGAPSIDESIDEWHITE.Tpo -c ta_CDLGAPSIDESIDEWHITE.c -o ta_CDLGAPSIDESIDEWHITE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLGAPSIDESIDEWHITE.Tpo .deps/ta_CDLGAPSIDESIDEWHITE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLGRAVESTONEDOJI.lo -MD -MP -MF .deps/ta_CDLGRAVESTONEDOJI.Tpo -c -o ta_CDLGRAVESTONEDOJI.lo ta_CDLGRAVESTONEDOJI.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLGRAVESTONEDOJI.lo -MD -MP -MF .deps/ta_CDLGRAVESTONEDOJI.Tpo -c ta_CDLGRAVESTONEDOJI.c  -fPIC -DPIC -o .libs/ta_CDLGRAVESTONEDOJI.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLGRAVESTONEDOJI.lo -MD -MP -MF .deps/ta_CDLGRAVESTONEDOJI.Tpo -c ta_CDLGRAVESTONEDOJI.c -o ta_CDLGRAVESTONEDOJI.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLGRAVESTONEDOJI.Tpo .deps/ta_CDLGRAVESTONEDOJI.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLHAMMER.lo -MD -MP -MF .deps/ta_CDLHAMMER.Tpo -c -o ta_CDLHAMMER.lo ta_CDLHAMMER.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLHAMMER.lo -MD -MP -MF .deps/ta_CDLHAMMER.Tpo -c ta_CDLHAMMER.c  -fPIC -DPIC -o .libs/ta_CDLHAMMER.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLHAMMER.lo -MD -MP -MF .deps/ta_CDLHAMMER.Tpo -c ta_CDLHAMMER.c -o ta_CDLHAMMER.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLHAMMER.Tpo .deps/ta_CDLHAMMER.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLHANGINGMAN.lo -MD -MP -MF .deps/ta_CDLHANGINGMAN.Tpo -c -o ta_CDLHANGINGMAN.lo ta_CDLHANGINGMAN.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLHANGINGMAN.lo -MD -MP -MF .deps/ta_CDLHANGINGMAN.Tpo -c ta_CDLHANGINGMAN.c  -fPIC -DPIC -o .libs/ta_CDLHANGINGMAN.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLHANGINGMAN.lo -MD -MP -MF .deps/ta_CDLHANGINGMAN.Tpo -c ta_CDLHANGINGMAN.c -o ta_CDLHANGINGMAN.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLHANGINGMAN.Tpo .deps/ta_CDLHANGINGMAN.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLHARAMI.lo -MD -MP -MF .deps/ta_CDLHARAMI.Tpo -c -o ta_CDLHARAMI.lo ta_CDLHARAMI.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLHARAMI.lo -MD -MP -MF .deps/ta_CDLHARAMI.Tpo -c ta_CDLHARAMI.c  -fPIC -DPIC -o .libs/ta_CDLHARAMI.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLHARAMI.lo -MD -MP -MF .deps/ta_CDLHARAMI.Tpo -c ta_CDLHARAMI.c -o ta_CDLHARAMI.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLHARAMI.Tpo .deps/ta_CDLHARAMI.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLHARAMICROSS.lo -MD -MP -MF .deps/ta_CDLHARAMICROSS.Tpo -c -o ta_CDLHARAMICROSS.lo ta_CDLHARAMICROSS.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLHARAMICROSS.lo -MD -MP -MF .deps/ta_CDLHARAMICROSS.Tpo -c ta_CDLHARAMICROSS.c  -fPIC -DPIC -o .libs/ta_CDLHARAMICROSS.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLHARAMICROSS.lo -MD -MP -MF .deps/ta_CDLHARAMICROSS.Tpo -c ta_CDLHARAMICROSS.c -o ta_CDLHARAMICROSS.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLHARAMICROSS.Tpo .deps/ta_CDLHARAMICROSS.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLHIGHWAVE.lo -MD -MP -MF .deps/ta_CDLHIGHWAVE.Tpo -c -o ta_CDLHIGHWAVE.lo ta_CDLHIGHWAVE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLHIGHWAVE.lo -MD -MP -MF .deps/ta_CDLHIGHWAVE.Tpo -c ta_CDLHIGHWAVE.c  -fPIC -DPIC -o .libs/ta_CDLHIGHWAVE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLHIGHWAVE.lo -MD -MP -MF .deps/ta_CDLHIGHWAVE.Tpo -c ta_CDLHIGHWAVE.c -o ta_CDLHIGHWAVE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLHIGHWAVE.Tpo .deps/ta_CDLHIGHWAVE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLHIKKAKE.lo -MD -MP -MF .deps/ta_CDLHIKKAKE.Tpo -c -o ta_CDLHIKKAKE.lo ta_CDLHIKKAKE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLHIKKAKE.lo -MD -MP -MF .deps/ta_CDLHIKKAKE.Tpo -c ta_CDLHIKKAKE.c  -fPIC -DPIC -o .libs/ta_CDLHIKKAKE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLHIKKAKE.lo -MD -MP -MF .deps/ta_CDLHIKKAKE.Tpo -c ta_CDLHIKKAKE.c -o ta_CDLHIKKAKE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLHIKKAKE.Tpo .deps/ta_CDLHIKKAKE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLHIKKAKEMOD.lo -MD -MP -MF .deps/ta_CDLHIKKAKEMOD.Tpo -c -o ta_CDLHIKKAKEMOD.lo ta_CDLHIKKAKEMOD.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLHIKKAKEMOD.lo -MD -MP -MF .deps/ta_CDLHIKKAKEMOD.Tpo -c ta_CDLHIKKAKEMOD.c  -fPIC -DPIC -o .libs/ta_CDLHIKKAKEMOD.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLHIKKAKEMOD.lo -MD -MP -MF .deps/ta_CDLHIKKAKEMOD.Tpo -c ta_CDLHIKKAKEMOD.c -o ta_CDLHIKKAKEMOD.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLHIKKAKEMOD.Tpo .deps/ta_CDLHIKKAKEMOD.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLHOMINGPIGEON.lo -MD -MP -MF .deps/ta_CDLHOMINGPIGEON.Tpo -c -o ta_CDLHOMINGPIGEON.lo ta_CDLHOMINGPIGEON.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLHOMINGPIGEON.lo -MD -MP -MF .deps/ta_CDLHOMINGPIGEON.Tpo -c ta_CDLHOMINGPIGEON.c  -fPIC -DPIC -o .libs/ta_CDLHOMINGPIGEON.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLHOMINGPIGEON.lo -MD -MP -MF .deps/ta_CDLHOMINGPIGEON.Tpo -c ta_CDLHOMINGPIGEON.c -o ta_CDLHOMINGPIGEON.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLHOMINGPIGEON.Tpo .deps/ta_CDLHOMINGPIGEON.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLIDENTICAL3CROWS.lo -MD -MP -MF .deps/ta_CDLIDENTICAL3CROWS.Tpo -c -o ta_CDLIDENTICAL3CROWS.lo ta_CDLIDENTICAL3CROWS.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLIDENTICAL3CROWS.lo -MD -MP -MF .deps/ta_CDLIDENTICAL3CROWS.Tpo -c ta_CDLIDENTICAL3CROWS.c  -fPIC -DPIC -o .libs/ta_CDLIDENTICAL3CROWS.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLIDENTICAL3CROWS.lo -MD -MP -MF .deps/ta_CDLIDENTICAL3CROWS.Tpo -c ta_CDLIDENTICAL3CROWS.c -o ta_CDLIDENTICAL3CROWS.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLIDENTICAL3CROWS.Tpo .deps/ta_CDLIDENTICAL3CROWS.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLINNECK.lo -MD -MP -MF .deps/ta_CDLINNECK.Tpo -c -o ta_CDLINNECK.lo ta_CDLINNECK.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLINNECK.lo -MD -MP -MF .deps/ta_CDLINNECK.Tpo -c ta_CDLINNECK.c  -fPIC -DPIC -o .libs/ta_CDLINNECK.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLINNECK.lo -MD -MP -MF .deps/ta_CDLINNECK.Tpo -c ta_CDLINNECK.c -o ta_CDLINNECK.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLINNECK.Tpo .deps/ta_CDLINNECK.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLINVERTEDHAMMER.lo -MD -MP -MF .deps/ta_CDLINVERTEDHAMMER.Tpo -c -o ta_CDLINVERTEDHAMMER.lo ta_CDLINVERTEDHAMMER.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLINVERTEDHAMMER.lo -MD -MP -MF .deps/ta_CDLINVERTEDHAMMER.Tpo -c ta_CDLINVERTEDHAMMER.c  -fPIC -DPIC -o .libs/ta_CDLINVERTEDHAMMER.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLINVERTEDHAMMER.lo -MD -MP -MF .deps/ta_CDLINVERTEDHAMMER.Tpo -c ta_CDLINVERTEDHAMMER.c -o ta_CDLINVERTEDHAMMER.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLINVERTEDHAMMER.Tpo .deps/ta_CDLINVERTEDHAMMER.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLKICKING.lo -MD -MP -MF .deps/ta_CDLKICKING.Tpo -c -o ta_CDLKICKING.lo ta_CDLKICKING.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLKICKING.lo -MD -MP -MF .deps/ta_CDLKICKING.Tpo -c ta_CDLKICKING.c  -fPIC -DPIC -o .libs/ta_CDLKICKING.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLKICKING.lo -MD -MP -MF .deps/ta_CDLKICKING.Tpo -c ta_CDLKICKING.c -o ta_CDLKICKING.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLKICKING.Tpo .deps/ta_CDLKICKING.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLKICKINGBYLENGTH.lo -MD -MP -MF .deps/ta_CDLKICKINGBYLENGTH.Tpo -c -o ta_CDLKICKINGBYLENGTH.lo ta_CDLKICKINGBYLENGTH.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLKICKINGBYLENGTH.lo -MD -MP -MF .deps/ta_CDLKICKINGBYLENGTH.Tpo -c ta_CDLKICKINGBYLENGTH.c  -fPIC -DPIC -o .libs/ta_CDLKICKINGBYLENGTH.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLKICKINGBYLENGTH.lo -MD -MP -MF .deps/ta_CDLKICKINGBYLENGTH.Tpo -c ta_CDLKICKINGBYLENGTH.c -o ta_CDLKICKINGBYLENGTH.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLKICKINGBYLENGTH.Tpo .deps/ta_CDLKICKINGBYLENGTH.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLLADDERBOTTOM.lo -MD -MP -MF .deps/ta_CDLLADDERBOTTOM.Tpo -c -o ta_CDLLADDERBOTTOM.lo ta_CDLLADDERBOTTOM.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLLADDERBOTTOM.lo -MD -MP -MF .deps/ta_CDLLADDERBOTTOM.Tpo -c ta_CDLLADDERBOTTOM.c  -fPIC -DPIC -o .libs/ta_CDLLADDERBOTTOM.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLLADDERBOTTOM.lo -MD -MP -MF .deps/ta_CDLLADDERBOTTOM.Tpo -c ta_CDLLADDERBOTTOM.c -o ta_CDLLADDERBOTTOM.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLLADDERBOTTOM.Tpo .deps/ta_CDLLADDERBOTTOM.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLLONGLEGGEDDOJI.lo -MD -MP -MF .deps/ta_CDLLONGLEGGEDDOJI.Tpo -c -o ta_CDLLONGLEGGEDDOJI.lo ta_CDLLONGLEGGEDDOJI.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLLONGLEGGEDDOJI.lo -MD -MP -MF .deps/ta_CDLLONGLEGGEDDOJI.Tpo -c ta_CDLLONGLEGGEDDOJI.c  -fPIC -DPIC -o .libs/ta_CDLLONGLEGGEDDOJI.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLLONGLEGGEDDOJI.lo -MD -MP -MF .deps/ta_CDLLONGLEGGEDDOJI.Tpo -c ta_CDLLONGLEGGEDDOJI.c -o ta_CDLLONGLEGGEDDOJI.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLLONGLEGGEDDOJI.Tpo .deps/ta_CDLLONGLEGGEDDOJI.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLLONGLINE.lo -MD -MP -MF .deps/ta_CDLLONGLINE.Tpo -c -o ta_CDLLONGLINE.lo ta_CDLLONGLINE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLLONGLINE.lo -MD -MP -MF .deps/ta_CDLLONGLINE.Tpo -c ta_CDLLONGLINE.c  -fPIC -DPIC -o .libs/ta_CDLLONGLINE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLLONGLINE.lo -MD -MP -MF .deps/ta_CDLLONGLINE.Tpo -c ta_CDLLONGLINE.c -o ta_CDLLONGLINE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLLONGLINE.Tpo .deps/ta_CDLLONGLINE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLMARUBOZU.lo -MD -MP -MF .deps/ta_CDLMARUBOZU.Tpo -c -o ta_CDLMARUBOZU.lo ta_CDLMARUBOZU.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLMARUBOZU.lo -MD -MP -MF .deps/ta_CDLMARUBOZU.Tpo -c ta_CDLMARUBOZU.c  -fPIC -DPIC -o .libs/ta_CDLMARUBOZU.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLMARUBOZU.lo -MD -MP -MF .deps/ta_CDLMARUBOZU.Tpo -c ta_CDLMARUBOZU.c -o ta_CDLMARUBOZU.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLMARUBOZU.Tpo .deps/ta_CDLMARUBOZU.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLMATCHINGLOW.lo -MD -MP -MF .deps/ta_CDLMATCHINGLOW.Tpo -c -o ta_CDLMATCHINGLOW.lo ta_CDLMATCHINGLOW.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLMATCHINGLOW.lo -MD -MP -MF .deps/ta_CDLMATCHINGLOW.Tpo -c ta_CDLMATCHINGLOW.c  -fPIC -DPIC -o .libs/ta_CDLMATCHINGLOW.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLMATCHINGLOW.lo -MD -MP -MF .deps/ta_CDLMATCHINGLOW.Tpo -c ta_CDLMATCHINGLOW.c -o ta_CDLMATCHINGLOW.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLMATCHINGLOW.Tpo .deps/ta_CDLMATCHINGLOW.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLMATHOLD.lo -MD -MP -MF .deps/ta_CDLMATHOLD.Tpo -c -o ta_CDLMATHOLD.lo ta_CDLMATHOLD.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLMATHOLD.lo -MD -MP -MF .deps/ta_CDLMATHOLD.Tpo -c ta_CDLMATHOLD.c  -fPIC -DPIC -o .libs/ta_CDLMATHOLD.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLMATHOLD.lo -MD -MP -MF .deps/ta_CDLMATHOLD.Tpo -c ta_CDLMATHOLD.c -o ta_CDLMATHOLD.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLMATHOLD.Tpo .deps/ta_CDLMATHOLD.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLMORNINGDOJISTAR.lo -MD -MP -MF .deps/ta_CDLMORNINGDOJISTAR.Tpo -c -o ta_CDLMORNINGDOJISTAR.lo ta_CDLMORNINGDOJISTAR.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLMORNINGDOJISTAR.lo -MD -MP -MF .deps/ta_CDLMORNINGDOJISTAR.Tpo -c ta_CDLMORNINGDOJISTAR.c  -fPIC -DPIC -o .libs/ta_CDLMORNINGDOJISTAR.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLMORNINGDOJISTAR.lo -MD -MP -MF .deps/ta_CDLMORNINGDOJISTAR.Tpo -c ta_CDLMORNINGDOJISTAR.c -o ta_CDLMORNINGDOJISTAR.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLMORNINGDOJISTAR.Tpo .deps/ta_CDLMORNINGDOJISTAR.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLMORNINGSTAR.lo -MD -MP -MF .deps/ta_CDLMORNINGSTAR.Tpo -c -o ta_CDLMORNINGSTAR.lo ta_CDLMORNINGSTAR.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLMORNINGSTAR.lo -MD -MP -MF .deps/ta_CDLMORNINGSTAR.Tpo -c ta_CDLMORNINGSTAR.c  -fPIC -DPIC -o .libs/ta_CDLMORNINGSTAR.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLMORNINGSTAR.lo -MD -MP -MF .deps/ta_CDLMORNINGSTAR.Tpo -c ta_CDLMORNINGSTAR.c -o ta_CDLMORNINGSTAR.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLMORNINGSTAR.Tpo .deps/ta_CDLMORNINGSTAR.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLONNECK.lo -MD -MP -MF .deps/ta_CDLONNECK.Tpo -c -o ta_CDLONNECK.lo ta_CDLONNECK.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLONNECK.lo -MD -MP -MF .deps/ta_CDLONNECK.Tpo -c ta_CDLONNECK.c  -fPIC -DPIC -o .libs/ta_CDLONNECK.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLONNECK.lo -MD -MP -MF .deps/ta_CDLONNECK.Tpo -c ta_CDLONNECK.c -o ta_CDLONNECK.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLONNECK.Tpo .deps/ta_CDLONNECK.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLPIERCING.lo -MD -MP -MF .deps/ta_CDLPIERCING.Tpo -c -o ta_CDLPIERCING.lo ta_CDLPIERCING.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLPIERCING.lo -MD -MP -MF .deps/ta_CDLPIERCING.Tpo -c ta_CDLPIERCING.c  -fPIC -DPIC -o .libs/ta_CDLPIERCING.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLPIERCING.lo -MD -MP -MF .deps/ta_CDLPIERCING.Tpo -c ta_CDLPIERCING.c -o ta_CDLPIERCING.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLPIERCING.Tpo .deps/ta_CDLPIERCING.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLRICKSHAWMAN.lo -MD -MP -MF .deps/ta_CDLRICKSHAWMAN.Tpo -c -o ta_CDLRICKSHAWMAN.lo ta_CDLRICKSHAWMAN.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLRICKSHAWMAN.lo -MD -MP -MF .deps/ta_CDLRICKSHAWMAN.Tpo -c ta_CDLRICKSHAWMAN.c  -fPIC -DPIC -o .libs/ta_CDLRICKSHAWMAN.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLRICKSHAWMAN.lo -MD -MP -MF .deps/ta_CDLRICKSHAWMAN.Tpo -c ta_CDLRICKSHAWMAN.c -o ta_CDLRICKSHAWMAN.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLRICKSHAWMAN.Tpo .deps/ta_CDLRICKSHAWMAN.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLRISEFALL3METHODS.lo -MD -MP -MF .deps/ta_CDLRISEFALL3METHODS.Tpo -c -o ta_CDLRISEFALL3METHODS.lo ta_CDLRISEFALL3METHODS.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLRISEFALL3METHODS.lo -MD -MP -MF .deps/ta_CDLRISEFALL3METHODS.Tpo -c ta_CDLRISEFALL3METHODS.c  -fPIC -DPIC -o .libs/ta_CDLRISEFALL3METHODS.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLRISEFALL3METHODS.lo -MD -MP -MF .deps/ta_CDLRISEFALL3METHODS.Tpo -c ta_CDLRISEFALL3METHODS.c -o ta_CDLRISEFALL3METHODS.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLRISEFALL3METHODS.Tpo .deps/ta_CDLRISEFALL3METHODS.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLSEPARATINGLINES.lo -MD -MP -MF .deps/ta_CDLSEPARATINGLINES.Tpo -c -o ta_CDLSEPARATINGLINES.lo ta_CDLSEPARATINGLINES.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLSEPARATINGLINES.lo -MD -MP -MF .deps/ta_CDLSEPARATINGLINES.Tpo -c ta_CDLSEPARATINGLINES.c  -fPIC -DPIC -o .libs/ta_CDLSEPARATINGLINES.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLSEPARATINGLINES.lo -MD -MP -MF .deps/ta_CDLSEPARATINGLINES.Tpo -c ta_CDLSEPARATINGLINES.c -o ta_CDLSEPARATINGLINES.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLSEPARATINGLINES.Tpo .deps/ta_CDLSEPARATINGLINES.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLSHOOTINGSTAR.lo -MD -MP -MF .deps/ta_CDLSHOOTINGSTAR.Tpo -c -o ta_CDLSHOOTINGSTAR.lo ta_CDLSHOOTINGSTAR.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLSHOOTINGSTAR.lo -MD -MP -MF .deps/ta_CDLSHOOTINGSTAR.Tpo -c ta_CDLSHOOTINGSTAR.c  -fPIC -DPIC -o .libs/ta_CDLSHOOTINGSTAR.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLSHOOTINGSTAR.lo -MD -MP -MF .deps/ta_CDLSHOOTINGSTAR.Tpo -c ta_CDLSHOOTINGSTAR.c -o ta_CDLSHOOTINGSTAR.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLSHOOTINGSTAR.Tpo .deps/ta_CDLSHOOTINGSTAR.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLSHORTLINE.lo -MD -MP -MF .deps/ta_CDLSHORTLINE.Tpo -c -o ta_CDLSHORTLINE.lo ta_CDLSHORTLINE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLSHORTLINE.lo -MD -MP -MF .deps/ta_CDLSHORTLINE.Tpo -c ta_CDLSHORTLINE.c  -fPIC -DPIC -o .libs/ta_CDLSHORTLINE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLSHORTLINE.lo -MD -MP -MF .deps/ta_CDLSHORTLINE.Tpo -c ta_CDLSHORTLINE.c -o ta_CDLSHORTLINE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLSHORTLINE.Tpo .deps/ta_CDLSHORTLINE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLSPINNINGTOP.lo -MD -MP -MF .deps/ta_CDLSPINNINGTOP.Tpo -c -o ta_CDLSPINNINGTOP.lo ta_CDLSPINNINGTOP.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLSPINNINGTOP.lo -MD -MP -MF .deps/ta_CDLSPINNINGTOP.Tpo -c ta_CDLSPINNINGTOP.c  -fPIC -DPIC -o .libs/ta_CDLSPINNINGTOP.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLSPINNINGTOP.lo -MD -MP -MF .deps/ta_CDLSPINNINGTOP.Tpo -c ta_CDLSPINNINGTOP.c -o ta_CDLSPINNINGTOP.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLSPINNINGTOP.Tpo .deps/ta_CDLSPINNINGTOP.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLSTALLEDPATTERN.lo -MD -MP -MF .deps/ta_CDLSTALLEDPATTERN.Tpo -c -o ta_CDLSTALLEDPATTERN.lo ta_CDLSTALLEDPATTERN.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLSTALLEDPATTERN.lo -MD -MP -MF .deps/ta_CDLSTALLEDPATTERN.Tpo -c ta_CDLSTALLEDPATTERN.c  -fPIC -DPIC -o .libs/ta_CDLSTALLEDPATTERN.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLSTALLEDPATTERN.lo -MD -MP -MF .deps/ta_CDLSTALLEDPATTERN.Tpo -c ta_CDLSTALLEDPATTERN.c -o ta_CDLSTALLEDPATTERN.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLSTALLEDPATTERN.Tpo .deps/ta_CDLSTALLEDPATTERN.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLSTICKSANDWICH.lo -MD -MP -MF .deps/ta_CDLSTICKSANDWICH.Tpo -c -o ta_CDLSTICKSANDWICH.lo ta_CDLSTICKSANDWICH.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLSTICKSANDWICH.lo -MD -MP -MF .deps/ta_CDLSTICKSANDWICH.Tpo -c ta_CDLSTICKSANDWICH.c  -fPIC -DPIC -o .libs/ta_CDLSTICKSANDWICH.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLSTICKSANDWICH.lo -MD -MP -MF .deps/ta_CDLSTICKSANDWICH.Tpo -c ta_CDLSTICKSANDWICH.c -o ta_CDLSTICKSANDWICH.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLSTICKSANDWICH.Tpo .deps/ta_CDLSTICKSANDWICH.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLTAKURI.lo -MD -MP -MF .deps/ta_CDLTAKURI.Tpo -c -o ta_CDLTAKURI.lo ta_CDLTAKURI.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLTAKURI.lo -MD -MP -MF .deps/ta_CDLTAKURI.Tpo -c ta_CDLTAKURI.c  -fPIC -DPIC -o .libs/ta_CDLTAKURI.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLTAKURI.lo -MD -MP -MF .deps/ta_CDLTAKURI.Tpo -c ta_CDLTAKURI.c -o ta_CDLTAKURI.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLTAKURI.Tpo .deps/ta_CDLTAKURI.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLTASUKIGAP.lo -MD -MP -MF .deps/ta_CDLTASUKIGAP.Tpo -c -o ta_CDLTASUKIGAP.lo ta_CDLTASUKIGAP.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLTASUKIGAP.lo -MD -MP -MF .deps/ta_CDLTASUKIGAP.Tpo -c ta_CDLTASUKIGAP.c  -fPIC -DPIC -o .libs/ta_CDLTASUKIGAP.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLTASUKIGAP.lo -MD -MP -MF .deps/ta_CDLTASUKIGAP.Tpo -c ta_CDLTASUKIGAP.c -o ta_CDLTASUKIGAP.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLTASUKIGAP.Tpo .deps/ta_CDLTASUKIGAP.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLTHRUSTING.lo -MD -MP -MF .deps/ta_CDLTHRUSTING.Tpo -c -o ta_CDLTHRUSTING.lo ta_CDLTHRUSTING.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLTHRUSTING.lo -MD -MP -MF .deps/ta_CDLTHRUSTING.Tpo -c ta_CDLTHRUSTING.c  -fPIC -DPIC -o .libs/ta_CDLTHRUSTING.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLTHRUSTING.lo -MD -MP -MF .deps/ta_CDLTHRUSTING.Tpo -c ta_CDLTHRUSTING.c -o ta_CDLTHRUSTING.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLTHRUSTING.Tpo .deps/ta_CDLTHRUSTING.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLTRISTAR.lo -MD -MP -MF .deps/ta_CDLTRISTAR.Tpo -c -o ta_CDLTRISTAR.lo ta_CDLTRISTAR.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLTRISTAR.lo -MD -MP -MF .deps/ta_CDLTRISTAR.Tpo -c ta_CDLTRISTAR.c  -fPIC -DPIC -o .libs/ta_CDLTRISTAR.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLTRISTAR.lo -MD -MP -MF .deps/ta_CDLTRISTAR.Tpo -c ta_CDLTRISTAR.c -o ta_CDLTRISTAR.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLTRISTAR.Tpo .deps/ta_CDLTRISTAR.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLUNIQUE3RIVER.lo -MD -MP -MF .deps/ta_CDLUNIQUE3RIVER.Tpo -c -o ta_CDLUNIQUE3RIVER.lo ta_CDLUNIQUE3RIVER.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLUNIQUE3RIVER.lo -MD -MP -MF .deps/ta_CDLUNIQUE3RIVER.Tpo -c ta_CDLUNIQUE3RIVER.c  -fPIC -DPIC -o .libs/ta_CDLUNIQUE3RIVER.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLUNIQUE3RIVER.lo -MD -MP -MF .deps/ta_CDLUNIQUE3RIVER.Tpo -c ta_CDLUNIQUE3RIVER.c -o ta_CDLUNIQUE3RIVER.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLUNIQUE3RIVER.Tpo .deps/ta_CDLUNIQUE3RIVER.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLUPSIDEGAP2CROWS.lo -MD -MP -MF .deps/ta_CDLUPSIDEGAP2CROWS.Tpo -c -o ta_CDLUPSIDEGAP2CROWS.lo ta_CDLUPSIDEGAP2CROWS.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLUPSIDEGAP2CROWS.lo -MD -MP -MF .deps/ta_CDLUPSIDEGAP2CROWS.Tpo -c ta_CDLUPSIDEGAP2CROWS.c  -fPIC -DPIC -o .libs/ta_CDLUPSIDEGAP2CROWS.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLUPSIDEGAP2CROWS.lo -MD -MP -MF .deps/ta_CDLUPSIDEGAP2CROWS.Tpo -c ta_CDLUPSIDEGAP2CROWS.c -o ta_CDLUPSIDEGAP2CROWS.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLUPSIDEGAP2CROWS.Tpo .deps/ta_CDLUPSIDEGAP2CROWS.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CDLXSIDEGAP3METHODS.lo -MD -MP -MF .deps/ta_CDLXSIDEGAP3METHODS.Tpo -c -o ta_CDLXSIDEGAP3METHODS.lo ta_CDLXSIDEGAP3METHODS.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLXSIDEGAP3METHODS.lo -MD -MP -MF .deps/ta_CDLXSIDEGAP3METHODS.Tpo -c ta_CDLXSIDEGAP3METHODS.c  -fPIC -DPIC -o .libs/ta_CDLXSIDEGAP3METHODS.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CDLXSIDEGAP3METHODS.lo -MD -MP -MF .deps/ta_CDLXSIDEGAP3METHODS.Tpo -c ta_CDLXSIDEGAP3METHODS.c -o ta_CDLXSIDEGAP3METHODS.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CDLXSIDEGAP3METHODS.Tpo .deps/ta_CDLXSIDEGAP3METHODS.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CEIL.lo -MD -MP -MF .deps/ta_CEIL.Tpo -c -o ta_CEIL.lo ta_CEIL.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CEIL.lo -MD -MP -MF .deps/ta_CEIL.Tpo -c ta_CEIL.c  -fPIC -DPIC -o .libs/ta_CEIL.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CEIL.lo -MD -MP -MF .deps/ta_CEIL.Tpo -c ta_CEIL.c -o ta_CEIL.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CEIL.Tpo .deps/ta_CEIL.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CMO.lo -MD -MP -MF .deps/ta_CMO.Tpo -c -o ta_CMO.lo ta_CMO.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CMO.lo -MD -MP -MF .deps/ta_CMO.Tpo -c ta_CMO.c  -fPIC -DPIC -o .libs/ta_CMO.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CMO.lo -MD -MP -MF .deps/ta_CMO.Tpo -c ta_CMO.c -o ta_CMO.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CMO.Tpo .deps/ta_CMO.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_CORREL.lo -MD -MP -MF .deps/ta_CORREL.Tpo -c -o ta_CORREL.lo ta_CORREL.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CORREL.lo -MD -MP -MF .deps/ta_CORREL.Tpo -c ta_CORREL.c  -fPIC -DPIC -o .libs/ta_CORREL.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_CORREL.lo -MD -MP -MF .deps/ta_CORREL.Tpo -c ta_CORREL.c -o ta_CORREL.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_CORREL.Tpo .deps/ta_CORREL.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_COS.lo -MD -MP -MF .deps/ta_COS.Tpo -c -o ta_COS.lo ta_COS.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_COS.lo -MD -MP -MF .deps/ta_COS.Tpo -c ta_COS.c  -fPIC -DPIC -o .libs/ta_COS.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_COS.lo -MD -MP -MF .deps/ta_COS.Tpo -c ta_COS.c -o ta_COS.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_COS.Tpo .deps/ta_COS.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_COSH.lo -MD -MP -MF .deps/ta_COSH.Tpo -c -o ta_COSH.lo ta_COSH.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_COSH.lo -MD -MP -MF .deps/ta_COSH.Tpo -c ta_COSH.c  -fPIC -DPIC -o .libs/ta_COSH.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_COSH.lo -MD -MP -MF .deps/ta_COSH.Tpo -c ta_COSH.c -o ta_COSH.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_COSH.Tpo .deps/ta_COSH.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_DEMA.lo -MD -MP -MF .deps/ta_DEMA.Tpo -c -o ta_DEMA.lo ta_DEMA.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_DEMA.lo -MD -MP -MF .deps/ta_DEMA.Tpo -c ta_DEMA.c  -fPIC -DPIC -o .libs/ta_DEMA.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_DEMA.lo -MD -MP -MF .deps/ta_DEMA.Tpo -c ta_DEMA.c -o ta_DEMA.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_DEMA.Tpo .deps/ta_DEMA.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_DIV.lo -MD -MP -MF .deps/ta_DIV.Tpo -c -o ta_DIV.lo ta_DIV.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_DIV.lo -MD -MP -MF .deps/ta_DIV.Tpo -c ta_DIV.c  -fPIC -DPIC -o .libs/ta_DIV.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_DIV.lo -MD -MP -MF .deps/ta_DIV.Tpo -c ta_DIV.c -o ta_DIV.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_DIV.Tpo .deps/ta_DIV.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_DX.lo -MD -MP -MF .deps/ta_DX.Tpo -c -o ta_DX.lo ta_DX.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_DX.lo -MD -MP -MF .deps/ta_DX.Tpo -c ta_DX.c  -fPIC -DPIC -o .libs/ta_DX.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_DX.lo -MD -MP -MF .deps/ta_DX.Tpo -c ta_DX.c -o ta_DX.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_DX.Tpo .deps/ta_DX.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_EMA.lo -MD -MP -MF .deps/ta_EMA.Tpo -c -o ta_EMA.lo ta_EMA.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_EMA.lo -MD -MP -MF .deps/ta_EMA.Tpo -c ta_EMA.c  -fPIC -DPIC -o .libs/ta_EMA.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_EMA.lo -MD -MP -MF .deps/ta_EMA.Tpo -c ta_EMA.c -o ta_EMA.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_EMA.Tpo .deps/ta_EMA.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_EXP.lo -MD -MP -MF .deps/ta_EXP.Tpo -c -o ta_EXP.lo ta_EXP.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_EXP.lo -MD -MP -MF .deps/ta_EXP.Tpo -c ta_EXP.c  -fPIC -DPIC -o .libs/ta_EXP.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_EXP.lo -MD -MP -MF .deps/ta_EXP.Tpo -c ta_EXP.c -o ta_EXP.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_EXP.Tpo .deps/ta_EXP.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_FLOOR.lo -MD -MP -MF .deps/ta_FLOOR.Tpo -c -o ta_FLOOR.lo ta_FLOOR.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_FLOOR.lo -MD -MP -MF .deps/ta_FLOOR.Tpo -c ta_FLOOR.c  -fPIC -DPIC -o .libs/ta_FLOOR.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_FLOOR.lo -MD -MP -MF .deps/ta_FLOOR.Tpo -c ta_FLOOR.c -o ta_FLOOR.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_FLOOR.Tpo .deps/ta_FLOOR.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_HT_DCPERIOD.lo -MD -MP -MF .deps/ta_HT_DCPERIOD.Tpo -c -o ta_HT_DCPERIOD.lo ta_HT_DCPERIOD.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_HT_DCPERIOD.lo -MD -MP -MF .deps/ta_HT_DCPERIOD.Tpo -c ta_HT_DCPERIOD.c  -fPIC -DPIC -o .libs/ta_HT_DCPERIOD.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_HT_DCPERIOD.lo -MD -MP -MF .deps/ta_HT_DCPERIOD.Tpo -c ta_HT_DCPERIOD.c -o ta_HT_DCPERIOD.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_HT_DCPERIOD.Tpo .deps/ta_HT_DCPERIOD.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_HT_DCPHASE.lo -MD -MP -MF .deps/ta_HT_DCPHASE.Tpo -c -o ta_HT_DCPHASE.lo ta_HT_DCPHASE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_HT_DCPHASE.lo -MD -MP -MF .deps/ta_HT_DCPHASE.Tpo -c ta_HT_DCPHASE.c  -fPIC -DPIC -o .libs/ta_HT_DCPHASE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_HT_DCPHASE.lo -MD -MP -MF .deps/ta_HT_DCPHASE.Tpo -c ta_HT_DCPHASE.c -o ta_HT_DCPHASE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_HT_DCPHASE.Tpo .deps/ta_HT_DCPHASE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_HT_PHASOR.lo -MD -MP -MF .deps/ta_HT_PHASOR.Tpo -c -o ta_HT_PHASOR.lo ta_HT_PHASOR.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_HT_PHASOR.lo -MD -MP -MF .deps/ta_HT_PHASOR.Tpo -c ta_HT_PHASOR.c  -fPIC -DPIC -o .libs/ta_HT_PHASOR.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_HT_PHASOR.lo -MD -MP -MF .deps/ta_HT_PHASOR.Tpo -c ta_HT_PHASOR.c -o ta_HT_PHASOR.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_HT_PHASOR.Tpo .deps/ta_HT_PHASOR.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_HT_SINE.lo -MD -MP -MF .deps/ta_HT_SINE.Tpo -c -o ta_HT_SINE.lo ta_HT_SINE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_HT_SINE.lo -MD -MP -MF .deps/ta_HT_SINE.Tpo -c ta_HT_SINE.c  -fPIC -DPIC -o .libs/ta_HT_SINE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_HT_SINE.lo -MD -MP -MF .deps/ta_HT_SINE.Tpo -c ta_HT_SINE.c -o ta_HT_SINE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_HT_SINE.Tpo .deps/ta_HT_SINE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_HT_TRENDLINE.lo -MD -MP -MF .deps/ta_HT_TRENDLINE.Tpo -c -o ta_HT_TRENDLINE.lo ta_HT_TRENDLINE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_HT_TRENDLINE.lo -MD -MP -MF .deps/ta_HT_TRENDLINE.Tpo -c ta_HT_TRENDLINE.c  -fPIC -DPIC -o .libs/ta_HT_TRENDLINE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_HT_TRENDLINE.lo -MD -MP -MF .deps/ta_HT_TRENDLINE.Tpo -c ta_HT_TRENDLINE.c -o ta_HT_TRENDLINE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_HT_TRENDLINE.Tpo .deps/ta_HT_TRENDLINE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_HT_TRENDMODE.lo -MD -MP -MF .deps/ta_HT_TRENDMODE.Tpo -c -o ta_HT_TRENDMODE.lo ta_HT_TRENDMODE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_HT_TRENDMODE.lo -MD -MP -MF .deps/ta_HT_TRENDMODE.Tpo -c ta_HT_TRENDMODE.c  -fPIC -DPIC -o .libs/ta_HT_TRENDMODE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_HT_TRENDMODE.lo -MD -MP -MF .deps/ta_HT_TRENDMODE.Tpo -c ta_HT_TRENDMODE.c -o ta_HT_TRENDMODE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_HT_TRENDMODE.Tpo .deps/ta_HT_TRENDMODE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_KAMA.lo -MD -MP -MF .deps/ta_KAMA.Tpo -c -o ta_KAMA.lo ta_KAMA.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_KAMA.lo -MD -MP -MF .deps/ta_KAMA.Tpo -c ta_KAMA.c  -fPIC -DPIC -o .libs/ta_KAMA.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_KAMA.lo -MD -MP -MF .deps/ta_KAMA.Tpo -c ta_KAMA.c -o ta_KAMA.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_KAMA.Tpo .deps/ta_KAMA.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_LINEARREG.lo -MD -MP -MF .deps/ta_LINEARREG.Tpo -c -o ta_LINEARREG.lo ta_LINEARREG.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_LINEARREG.lo -MD -MP -MF .deps/ta_LINEARREG.Tpo -c ta_LINEARREG.c  -fPIC -DPIC -o .libs/ta_LINEARREG.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_LINEARREG.lo -MD -MP -MF .deps/ta_LINEARREG.Tpo -c ta_LINEARREG.c -o ta_LINEARREG.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_LINEARREG.Tpo .deps/ta_LINEARREG.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_LINEARREG_ANGLE.lo -MD -MP -MF .deps/ta_LINEARREG_ANGLE.Tpo -c -o ta_LINEARREG_ANGLE.lo ta_LINEARREG_ANGLE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_LINEARREG_ANGLE.lo -MD -MP -MF .deps/ta_LINEARREG_ANGLE.Tpo -c ta_LINEARREG_ANGLE.c  -fPIC -DPIC -o .libs/ta_LINEARREG_ANGLE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_LINEARREG_ANGLE.lo -MD -MP -MF .deps/ta_LINEARREG_ANGLE.Tpo -c ta_LINEARREG_ANGLE.c -o ta_LINEARREG_ANGLE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_LINEARREG_ANGLE.Tpo .deps/ta_LINEARREG_ANGLE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_LINEARREG_INTERCEPT.lo -MD -MP -MF .deps/ta_LINEARREG_INTERCEPT.Tpo -c -o ta_LINEARREG_INTERCEPT.lo ta_LINEARREG_INTERCEPT.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_LINEARREG_INTERCEPT.lo -MD -MP -MF .deps/ta_LINEARREG_INTERCEPT.Tpo -c ta_LINEARREG_INTERCEPT.c  -fPIC -DPIC -o .libs/ta_LINEARREG_INTERCEPT.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_LINEARREG_INTERCEPT.lo -MD -MP -MF .deps/ta_LINEARREG_INTERCEPT.Tpo -c ta_LINEARREG_INTERCEPT.c -o ta_LINEARREG_INTERCEPT.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_LINEARREG_INTERCEPT.Tpo .deps/ta_LINEARREG_INTERCEPT.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_LINEARREG_SLOPE.lo -MD -MP -MF .deps/ta_LINEARREG_SLOPE.Tpo -c -o ta_LINEARREG_SLOPE.lo ta_LINEARREG_SLOPE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_LINEARREG_SLOPE.lo -MD -MP -MF .deps/ta_LINEARREG_SLOPE.Tpo -c ta_LINEARREG_SLOPE.c  -fPIC -DPIC -o .libs/ta_LINEARREG_SLOPE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_LINEARREG_SLOPE.lo -MD -MP -MF .deps/ta_LINEARREG_SLOPE.Tpo -c ta_LINEARREG_SLOPE.c -o ta_LINEARREG_SLOPE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_LINEARREG_SLOPE.Tpo .deps/ta_LINEARREG_SLOPE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_LN.lo -MD -MP -MF .deps/ta_LN.Tpo -c -o ta_LN.lo ta_LN.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_LN.lo -MD -MP -MF .deps/ta_LN.Tpo -c ta_LN.c  -fPIC -DPIC -o .libs/ta_LN.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_LN.lo -MD -MP -MF .deps/ta_LN.Tpo -c ta_LN.c -o ta_LN.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_LN.Tpo .deps/ta_LN.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_LOG10.lo -MD -MP -MF .deps/ta_LOG10.Tpo -c -o ta_LOG10.lo ta_LOG10.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_LOG10.lo -MD -MP -MF .deps/ta_LOG10.Tpo -c ta_LOG10.c  -fPIC -DPIC -o .libs/ta_LOG10.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_LOG10.lo -MD -MP -MF .deps/ta_LOG10.Tpo -c ta_LOG10.c -o ta_LOG10.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_LOG10.Tpo .deps/ta_LOG10.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MA.lo -MD -MP -MF .deps/ta_MA.Tpo -c -o ta_MA.lo ta_MA.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MA.lo -MD -MP -MF .deps/ta_MA.Tpo -c ta_MA.c  -fPIC -DPIC -o .libs/ta_MA.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MA.lo -MD -MP -MF .deps/ta_MA.Tpo -c ta_MA.c -o ta_MA.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MA.Tpo .deps/ta_MA.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MACD.lo -MD -MP -MF .deps/ta_MACD.Tpo -c -o ta_MACD.lo ta_MACD.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MACD.lo -MD -MP -MF .deps/ta_MACD.Tpo -c ta_MACD.c  -fPIC -DPIC -o .libs/ta_MACD.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MACD.lo -MD -MP -MF .deps/ta_MACD.Tpo -c ta_MACD.c -o ta_MACD.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MACD.Tpo .deps/ta_MACD.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MACDEXT.lo -MD -MP -MF .deps/ta_MACDEXT.Tpo -c -o ta_MACDEXT.lo ta_MACDEXT.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MACDEXT.lo -MD -MP -MF .deps/ta_MACDEXT.Tpo -c ta_MACDEXT.c  -fPIC -DPIC -o .libs/ta_MACDEXT.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MACDEXT.lo -MD -MP -MF .deps/ta_MACDEXT.Tpo -c ta_MACDEXT.c -o ta_MACDEXT.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MACDEXT.Tpo .deps/ta_MACDEXT.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MACDFIX.lo -MD -MP -MF .deps/ta_MACDFIX.Tpo -c -o ta_MACDFIX.lo ta_MACDFIX.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MACDFIX.lo -MD -MP -MF .deps/ta_MACDFIX.Tpo -c ta_MACDFIX.c  -fPIC -DPIC -o .libs/ta_MACDFIX.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MACDFIX.lo -MD -MP -MF .deps/ta_MACDFIX.Tpo -c ta_MACDFIX.c -o ta_MACDFIX.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MACDFIX.Tpo .deps/ta_MACDFIX.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MAMA.lo -MD -MP -MF .deps/ta_MAMA.Tpo -c -o ta_MAMA.lo ta_MAMA.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MAMA.lo -MD -MP -MF .deps/ta_MAMA.Tpo -c ta_MAMA.c  -fPIC -DPIC -o .libs/ta_MAMA.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MAMA.lo -MD -MP -MF .deps/ta_MAMA.Tpo -c ta_MAMA.c -o ta_MAMA.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MAMA.Tpo .deps/ta_MAMA.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MAVP.lo -MD -MP -MF .deps/ta_MAVP.Tpo -c -o ta_MAVP.lo ta_MAVP.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MAVP.lo -MD -MP -MF .deps/ta_MAVP.Tpo -c ta_MAVP.c  -fPIC -DPIC -o .libs/ta_MAVP.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MAVP.lo -MD -MP -MF .deps/ta_MAVP.Tpo -c ta_MAVP.c -o ta_MAVP.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MAVP.Tpo .deps/ta_MAVP.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MAX.lo -MD -MP -MF .deps/ta_MAX.Tpo -c -o ta_MAX.lo ta_MAX.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MAX.lo -MD -MP -MF .deps/ta_MAX.Tpo -c ta_MAX.c  -fPIC -DPIC -o .libs/ta_MAX.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MAX.lo -MD -MP -MF .deps/ta_MAX.Tpo -c ta_MAX.c -o ta_MAX.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MAX.Tpo .deps/ta_MAX.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MAXINDEX.lo -MD -MP -MF .deps/ta_MAXINDEX.Tpo -c -o ta_MAXINDEX.lo ta_MAXINDEX.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MAXINDEX.lo -MD -MP -MF .deps/ta_MAXINDEX.Tpo -c ta_MAXINDEX.c  -fPIC -DPIC -o .libs/ta_MAXINDEX.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MAXINDEX.lo -MD -MP -MF .deps/ta_MAXINDEX.Tpo -c ta_MAXINDEX.c -o ta_MAXINDEX.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MAXINDEX.Tpo .deps/ta_MAXINDEX.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MEDPRICE.lo -MD -MP -MF .deps/ta_MEDPRICE.Tpo -c -o ta_MEDPRICE.lo ta_MEDPRICE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MEDPRICE.lo -MD -MP -MF .deps/ta_MEDPRICE.Tpo -c ta_MEDPRICE.c  -fPIC -DPIC -o .libs/ta_MEDPRICE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MEDPRICE.lo -MD -MP -MF .deps/ta_MEDPRICE.Tpo -c ta_MEDPRICE.c -o ta_MEDPRICE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MEDPRICE.Tpo .deps/ta_MEDPRICE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MFI.lo -MD -MP -MF .deps/ta_MFI.Tpo -c -o ta_MFI.lo ta_MFI.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MFI.lo -MD -MP -MF .deps/ta_MFI.Tpo -c ta_MFI.c  -fPIC -DPIC -o .libs/ta_MFI.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MFI.lo -MD -MP -MF .deps/ta_MFI.Tpo -c ta_MFI.c -o ta_MFI.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MFI.Tpo .deps/ta_MFI.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MIDPOINT.lo -MD -MP -MF .deps/ta_MIDPOINT.Tpo -c -o ta_MIDPOINT.lo ta_MIDPOINT.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MIDPOINT.lo -MD -MP -MF .deps/ta_MIDPOINT.Tpo -c ta_MIDPOINT.c  -fPIC -DPIC -o .libs/ta_MIDPOINT.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MIDPOINT.lo -MD -MP -MF .deps/ta_MIDPOINT.Tpo -c ta_MIDPOINT.c -o ta_MIDPOINT.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MIDPOINT.Tpo .deps/ta_MIDPOINT.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MIDPRICE.lo -MD -MP -MF .deps/ta_MIDPRICE.Tpo -c -o ta_MIDPRICE.lo ta_MIDPRICE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MIDPRICE.lo -MD -MP -MF .deps/ta_MIDPRICE.Tpo -c ta_MIDPRICE.c  -fPIC -DPIC -o .libs/ta_MIDPRICE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MIDPRICE.lo -MD -MP -MF .deps/ta_MIDPRICE.Tpo -c ta_MIDPRICE.c -o ta_MIDPRICE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MIDPRICE.Tpo .deps/ta_MIDPRICE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MIN.lo -MD -MP -MF .deps/ta_MIN.Tpo -c -o ta_MIN.lo ta_MIN.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MIN.lo -MD -MP -MF .deps/ta_MIN.Tpo -c ta_MIN.c  -fPIC -DPIC -o .libs/ta_MIN.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MIN.lo -MD -MP -MF .deps/ta_MIN.Tpo -c ta_MIN.c -o ta_MIN.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MIN.Tpo .deps/ta_MIN.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MININDEX.lo -MD -MP -MF .deps/ta_MININDEX.Tpo -c -o ta_MININDEX.lo ta_MININDEX.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MININDEX.lo -MD -MP -MF .deps/ta_MININDEX.Tpo -c ta_MININDEX.c  -fPIC -DPIC -o .libs/ta_MININDEX.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MININDEX.lo -MD -MP -MF .deps/ta_MININDEX.Tpo -c ta_MININDEX.c -o ta_MININDEX.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MININDEX.Tpo .deps/ta_MININDEX.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MINMAX.lo -MD -MP -MF .deps/ta_MINMAX.Tpo -c -o ta_MINMAX.lo ta_MINMAX.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MINMAX.lo -MD -MP -MF .deps/ta_MINMAX.Tpo -c ta_MINMAX.c  -fPIC -DPIC -o .libs/ta_MINMAX.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MINMAX.lo -MD -MP -MF .deps/ta_MINMAX.Tpo -c ta_MINMAX.c -o ta_MINMAX.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MINMAX.Tpo .deps/ta_MINMAX.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MINMAXINDEX.lo -MD -MP -MF .deps/ta_MINMAXINDEX.Tpo -c -o ta_MINMAXINDEX.lo ta_MINMAXINDEX.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MINMAXINDEX.lo -MD -MP -MF .deps/ta_MINMAXINDEX.Tpo -c ta_MINMAXINDEX.c  -fPIC -DPIC -o .libs/ta_MINMAXINDEX.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MINMAXINDEX.lo -MD -MP -MF .deps/ta_MINMAXINDEX.Tpo -c ta_MINMAXINDEX.c -o ta_MINMAXINDEX.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MINMAXINDEX.Tpo .deps/ta_MINMAXINDEX.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MINUS_DI.lo -MD -MP -MF .deps/ta_MINUS_DI.Tpo -c -o ta_MINUS_DI.lo ta_MINUS_DI.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MINUS_DI.lo -MD -MP -MF .deps/ta_MINUS_DI.Tpo -c ta_MINUS_DI.c  -fPIC -DPIC -o .libs/ta_MINUS_DI.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MINUS_DI.lo -MD -MP -MF .deps/ta_MINUS_DI.Tpo -c ta_MINUS_DI.c -o ta_MINUS_DI.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MINUS_DI.Tpo .deps/ta_MINUS_DI.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MINUS_DM.lo -MD -MP -MF .deps/ta_MINUS_DM.Tpo -c -o ta_MINUS_DM.lo ta_MINUS_DM.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MINUS_DM.lo -MD -MP -MF .deps/ta_MINUS_DM.Tpo -c ta_MINUS_DM.c  -fPIC -DPIC -o .libs/ta_MINUS_DM.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MINUS_DM.lo -MD -MP -MF .deps/ta_MINUS_DM.Tpo -c ta_MINUS_DM.c -o ta_MINUS_DM.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MINUS_DM.Tpo .deps/ta_MINUS_DM.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MOM.lo -MD -MP -MF .deps/ta_MOM.Tpo -c -o ta_MOM.lo ta_MOM.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MOM.lo -MD -MP -MF .deps/ta_MOM.Tpo -c ta_MOM.c  -fPIC -DPIC -o .libs/ta_MOM.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MOM.lo -MD -MP -MF .deps/ta_MOM.Tpo -c ta_MOM.c -o ta_MOM.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MOM.Tpo .deps/ta_MOM.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_MULT.lo -MD -MP -MF .deps/ta_MULT.Tpo -c -o ta_MULT.lo ta_MULT.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MULT.lo -MD -MP -MF .deps/ta_MULT.Tpo -c ta_MULT.c  -fPIC -DPIC -o .libs/ta_MULT.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_MULT.lo -MD -MP -MF .deps/ta_MULT.Tpo -c ta_MULT.c -o ta_MULT.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_MULT.Tpo .deps/ta_MULT.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_NATR.lo -MD -MP -MF .deps/ta_NATR.Tpo -c -o ta_NATR.lo ta_NATR.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_NATR.lo -MD -MP -MF .deps/ta_NATR.Tpo -c ta_NATR.c  -fPIC -DPIC -o .libs/ta_NATR.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_NATR.lo -MD -MP -MF .deps/ta_NATR.Tpo -c ta_NATR.c -o ta_NATR.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_NATR.Tpo .deps/ta_NATR.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_OBV.lo -MD -MP -MF .deps/ta_OBV.Tpo -c -o ta_OBV.lo ta_OBV.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_OBV.lo -MD -MP -MF .deps/ta_OBV.Tpo -c ta_OBV.c  -fPIC -DPIC -o .libs/ta_OBV.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_OBV.lo -MD -MP -MF .deps/ta_OBV.Tpo -c ta_OBV.c -o ta_OBV.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_OBV.Tpo .deps/ta_OBV.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_PLUS_DI.lo -MD -MP -MF .deps/ta_PLUS_DI.Tpo -c -o ta_PLUS_DI.lo ta_PLUS_DI.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_PLUS_DI.lo -MD -MP -MF .deps/ta_PLUS_DI.Tpo -c ta_PLUS_DI.c  -fPIC -DPIC -o .libs/ta_PLUS_DI.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_PLUS_DI.lo -MD -MP -MF .deps/ta_PLUS_DI.Tpo -c ta_PLUS_DI.c -o ta_PLUS_DI.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_PLUS_DI.Tpo .deps/ta_PLUS_DI.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_PLUS_DM.lo -MD -MP -MF .deps/ta_PLUS_DM.Tpo -c -o ta_PLUS_DM.lo ta_PLUS_DM.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_PLUS_DM.lo -MD -MP -MF .deps/ta_PLUS_DM.Tpo -c ta_PLUS_DM.c  -fPIC -DPIC -o .libs/ta_PLUS_DM.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_PLUS_DM.lo -MD -MP -MF .deps/ta_PLUS_DM.Tpo -c ta_PLUS_DM.c -o ta_PLUS_DM.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_PLUS_DM.Tpo .deps/ta_PLUS_DM.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_PPO.lo -MD -MP -MF .deps/ta_PPO.Tpo -c -o ta_PPO.lo ta_PPO.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_PPO.lo -MD -MP -MF .deps/ta_PPO.Tpo -c ta_PPO.c  -fPIC -DPIC -o .libs/ta_PPO.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_PPO.lo -MD -MP -MF .deps/ta_PPO.Tpo -c ta_PPO.c -o ta_PPO.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_PPO.Tpo .deps/ta_PPO.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_ROC.lo -MD -MP -MF .deps/ta_ROC.Tpo -c -o ta_ROC.lo ta_ROC.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ROC.lo -MD -MP -MF .deps/ta_ROC.Tpo -c ta_ROC.c  -fPIC -DPIC -o .libs/ta_ROC.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ROC.lo -MD -MP -MF .deps/ta_ROC.Tpo -c ta_ROC.c -o ta_ROC.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_ROC.Tpo .deps/ta_ROC.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_ROCP.lo -MD -MP -MF .deps/ta_ROCP.Tpo -c -o ta_ROCP.lo ta_ROCP.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ROCP.lo -MD -MP -MF .deps/ta_ROCP.Tpo -c ta_ROCP.c  -fPIC -DPIC -o .libs/ta_ROCP.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ROCP.lo -MD -MP -MF .deps/ta_ROCP.Tpo -c ta_ROCP.c -o ta_ROCP.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_ROCP.Tpo .deps/ta_ROCP.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_ROCR.lo -MD -MP -MF .deps/ta_ROCR.Tpo -c -o ta_ROCR.lo ta_ROCR.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ROCR.lo -MD -MP -MF .deps/ta_ROCR.Tpo -c ta_ROCR.c  -fPIC -DPIC -o .libs/ta_ROCR.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ROCR.lo -MD -MP -MF .deps/ta_ROCR.Tpo -c ta_ROCR.c -o ta_ROCR.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_ROCR.Tpo .deps/ta_ROCR.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_ROCR100.lo -MD -MP -MF .deps/ta_ROCR100.Tpo -c -o ta_ROCR100.lo ta_ROCR100.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ROCR100.lo -MD -MP -MF .deps/ta_ROCR100.Tpo -c ta_ROCR100.c  -fPIC -DPIC -o .libs/ta_ROCR100.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ROCR100.lo -MD -MP -MF .deps/ta_ROCR100.Tpo -c ta_ROCR100.c -o ta_ROCR100.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_ROCR100.Tpo .deps/ta_ROCR100.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_RSI.lo -MD -MP -MF .deps/ta_RSI.Tpo -c -o ta_RSI.lo ta_RSI.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_RSI.lo -MD -MP -MF .deps/ta_RSI.Tpo -c ta_RSI.c  -fPIC -DPIC -o .libs/ta_RSI.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_RSI.lo -MD -MP -MF .deps/ta_RSI.Tpo -c ta_RSI.c -o ta_RSI.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_RSI.Tpo .deps/ta_RSI.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_SAR.lo -MD -MP -MF .deps/ta_SAR.Tpo -c -o ta_SAR.lo ta_SAR.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_SAR.lo -MD -MP -MF .deps/ta_SAR.Tpo -c ta_SAR.c  -fPIC -DPIC -o .libs/ta_SAR.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_SAR.lo -MD -MP -MF .deps/ta_SAR.Tpo -c ta_SAR.c -o ta_SAR.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_SAR.Tpo .deps/ta_SAR.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_SAREXT.lo -MD -MP -MF .deps/ta_SAREXT.Tpo -c -o ta_SAREXT.lo ta_SAREXT.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_SAREXT.lo -MD -MP -MF .deps/ta_SAREXT.Tpo -c ta_SAREXT.c  -fPIC -DPIC -o .libs/ta_SAREXT.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_SAREXT.lo -MD -MP -MF .deps/ta_SAREXT.Tpo -c ta_SAREXT.c -o ta_SAREXT.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_SAREXT.Tpo .deps/ta_SAREXT.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_SIN.lo -MD -MP -MF .deps/ta_SIN.Tpo -c -o ta_SIN.lo ta_SIN.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_SIN.lo -MD -MP -MF .deps/ta_SIN.Tpo -c ta_SIN.c  -fPIC -DPIC -o .libs/ta_SIN.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_SIN.lo -MD -MP -MF .deps/ta_SIN.Tpo -c ta_SIN.c -o ta_SIN.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_SIN.Tpo .deps/ta_SIN.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_SINH.lo -MD -MP -MF .deps/ta_SINH.Tpo -c -o ta_SINH.lo ta_SINH.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_SINH.lo -MD -MP -MF .deps/ta_SINH.Tpo -c ta_SINH.c  -fPIC -DPIC -o .libs/ta_SINH.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_SINH.lo -MD -MP -MF .deps/ta_SINH.Tpo -c ta_SINH.c -o ta_SINH.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_SINH.Tpo .deps/ta_SINH.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_SMA.lo -MD -MP -MF .deps/ta_SMA.Tpo -c -o ta_SMA.lo ta_SMA.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_SMA.lo -MD -MP -MF .deps/ta_SMA.Tpo -c ta_SMA.c  -fPIC -DPIC -o .libs/ta_SMA.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_SMA.lo -MD -MP -MF .deps/ta_SMA.Tpo -c ta_SMA.c -o ta_SMA.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_SMA.Tpo .deps/ta_SMA.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_SQRT.lo -MD -MP -MF .deps/ta_SQRT.Tpo -c -o ta_SQRT.lo ta_SQRT.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_SQRT.lo -MD -MP -MF .deps/ta_SQRT.Tpo -c ta_SQRT.c  -fPIC -DPIC -o .libs/ta_SQRT.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_SQRT.lo -MD -MP -MF .deps/ta_SQRT.Tpo -c ta_SQRT.c -o ta_SQRT.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_SQRT.Tpo .deps/ta_SQRT.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_STDDEV.lo -MD -MP -MF .deps/ta_STDDEV.Tpo -c -o ta_STDDEV.lo ta_STDDEV.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_STDDEV.lo -MD -MP -MF .deps/ta_STDDEV.Tpo -c ta_STDDEV.c  -fPIC -DPIC -o .libs/ta_STDDEV.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_STDDEV.lo -MD -MP -MF .deps/ta_STDDEV.Tpo -c ta_STDDEV.c -o ta_STDDEV.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_STDDEV.Tpo .deps/ta_STDDEV.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_STOCH.lo -MD -MP -MF .deps/ta_STOCH.Tpo -c -o ta_STOCH.lo ta_STOCH.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_STOCH.lo -MD -MP -MF .deps/ta_STOCH.Tpo -c ta_STOCH.c  -fPIC -DPIC -o .libs/ta_STOCH.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_STOCH.lo -MD -MP -MF .deps/ta_STOCH.Tpo -c ta_STOCH.c -o ta_STOCH.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_STOCH.Tpo .deps/ta_STOCH.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_STOCHF.lo -MD -MP -MF .deps/ta_STOCHF.Tpo -c -o ta_STOCHF.lo ta_STOCHF.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_STOCHF.lo -MD -MP -MF .deps/ta_STOCHF.Tpo -c ta_STOCHF.c  -fPIC -DPIC -o .libs/ta_STOCHF.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_STOCHF.lo -MD -MP -MF .deps/ta_STOCHF.Tpo -c ta_STOCHF.c -o ta_STOCHF.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_STOCHF.Tpo .deps/ta_STOCHF.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_STOCHRSI.lo -MD -MP -MF .deps/ta_STOCHRSI.Tpo -c -o ta_STOCHRSI.lo ta_STOCHRSI.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_STOCHRSI.lo -MD -MP -MF .deps/ta_STOCHRSI.Tpo -c ta_STOCHRSI.c  -fPIC -DPIC -o .libs/ta_STOCHRSI.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_STOCHRSI.lo -MD -MP -MF .deps/ta_STOCHRSI.Tpo -c ta_STOCHRSI.c -o ta_STOCHRSI.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_STOCHRSI.Tpo .deps/ta_STOCHRSI.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_SUB.lo -MD -MP -MF .deps/ta_SUB.Tpo -c -o ta_SUB.lo ta_SUB.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_SUB.lo -MD -MP -MF .deps/ta_SUB.Tpo -c ta_SUB.c  -fPIC -DPIC -o .libs/ta_SUB.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_SUB.lo -MD -MP -MF .deps/ta_SUB.Tpo -c ta_SUB.c -o ta_SUB.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_SUB.Tpo .deps/ta_SUB.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_SUM.lo -MD -MP -MF .deps/ta_SUM.Tpo -c -o ta_SUM.lo ta_SUM.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_SUM.lo -MD -MP -MF .deps/ta_SUM.Tpo -c ta_SUM.c  -fPIC -DPIC -o .libs/ta_SUM.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_SUM.lo -MD -MP -MF .deps/ta_SUM.Tpo -c ta_SUM.c -o ta_SUM.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_SUM.Tpo .deps/ta_SUM.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_T3.lo -MD -MP -MF .deps/ta_T3.Tpo -c -o ta_T3.lo ta_T3.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_T3.lo -MD -MP -MF .deps/ta_T3.Tpo -c ta_T3.c  -fPIC -DPIC -o .libs/ta_T3.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_T3.lo -MD -MP -MF .deps/ta_T3.Tpo -c ta_T3.c -o ta_T3.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_T3.Tpo .deps/ta_T3.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_TAN.lo -MD -MP -MF .deps/ta_TAN.Tpo -c -o ta_TAN.lo ta_TAN.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_TAN.lo -MD -MP -MF .deps/ta_TAN.Tpo -c ta_TAN.c  -fPIC -DPIC -o .libs/ta_TAN.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_TAN.lo -MD -MP -MF .deps/ta_TAN.Tpo -c ta_TAN.c -o ta_TAN.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_TAN.Tpo .deps/ta_TAN.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_TANH.lo -MD -MP -MF .deps/ta_TANH.Tpo -c -o ta_TANH.lo ta_TANH.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_TANH.lo -MD -MP -MF .deps/ta_TANH.Tpo -c ta_TANH.c  -fPIC -DPIC -o .libs/ta_TANH.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_TANH.lo -MD -MP -MF .deps/ta_TANH.Tpo -c ta_TANH.c -o ta_TANH.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_TANH.Tpo .deps/ta_TANH.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_TEMA.lo -MD -MP -MF .deps/ta_TEMA.Tpo -c -o ta_TEMA.lo ta_TEMA.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_TEMA.lo -MD -MP -MF .deps/ta_TEMA.Tpo -c ta_TEMA.c  -fPIC -DPIC -o .libs/ta_TEMA.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_TEMA.lo -MD -MP -MF .deps/ta_TEMA.Tpo -c ta_TEMA.c -o ta_TEMA.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_TEMA.Tpo .deps/ta_TEMA.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_TRANGE.lo -MD -MP -MF .deps/ta_TRANGE.Tpo -c -o ta_TRANGE.lo ta_TRANGE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_TRANGE.lo -MD -MP -MF .deps/ta_TRANGE.Tpo -c ta_TRANGE.c  -fPIC -DPIC -o .libs/ta_TRANGE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_TRANGE.lo -MD -MP -MF .deps/ta_TRANGE.Tpo -c ta_TRANGE.c -o ta_TRANGE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_TRANGE.Tpo .deps/ta_TRANGE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_TRIMA.lo -MD -MP -MF .deps/ta_TRIMA.Tpo -c -o ta_TRIMA.lo ta_TRIMA.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_TRIMA.lo -MD -MP -MF .deps/ta_TRIMA.Tpo -c ta_TRIMA.c  -fPIC -DPIC -o .libs/ta_TRIMA.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_TRIMA.lo -MD -MP -MF .deps/ta_TRIMA.Tpo -c ta_TRIMA.c -o ta_TRIMA.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_TRIMA.Tpo .deps/ta_TRIMA.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_TRIX.lo -MD -MP -MF .deps/ta_TRIX.Tpo -c -o ta_TRIX.lo ta_TRIX.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_TRIX.lo -MD -MP -MF .deps/ta_TRIX.Tpo -c ta_TRIX.c  -fPIC -DPIC -o .libs/ta_TRIX.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_TRIX.lo -MD -MP -MF .deps/ta_TRIX.Tpo -c ta_TRIX.c -o ta_TRIX.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_TRIX.Tpo .deps/ta_TRIX.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_TSF.lo -MD -MP -MF .deps/ta_TSF.Tpo -c -o ta_TSF.lo ta_TSF.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_TSF.lo -MD -MP -MF .deps/ta_TSF.Tpo -c ta_TSF.c  -fPIC -DPIC -o .libs/ta_TSF.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_TSF.lo -MD -MP -MF .deps/ta_TSF.Tpo -c ta_TSF.c -o ta_TSF.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_TSF.Tpo .deps/ta_TSF.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_TYPPRICE.lo -MD -MP -MF .deps/ta_TYPPRICE.Tpo -c -o ta_TYPPRICE.lo ta_TYPPRICE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_TYPPRICE.lo -MD -MP -MF .deps/ta_TYPPRICE.Tpo -c ta_TYPPRICE.c  -fPIC -DPIC -o .libs/ta_TYPPRICE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_TYPPRICE.lo -MD -MP -MF .deps/ta_TYPPRICE.Tpo -c ta_TYPPRICE.c -o ta_TYPPRICE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_TYPPRICE.Tpo .deps/ta_TYPPRICE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_ULTOSC.lo -MD -MP -MF .deps/ta_ULTOSC.Tpo -c -o ta_ULTOSC.lo ta_ULTOSC.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ULTOSC.lo -MD -MP -MF .deps/ta_ULTOSC.Tpo -c ta_ULTOSC.c  -fPIC -DPIC -o .libs/ta_ULTOSC.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_ULTOSC.lo -MD -MP -MF .deps/ta_ULTOSC.Tpo -c ta_ULTOSC.c -o ta_ULTOSC.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_ULTOSC.Tpo .deps/ta_ULTOSC.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_VAR.lo -MD -MP -MF .deps/ta_VAR.Tpo -c -o ta_VAR.lo ta_VAR.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_VAR.lo -MD -MP -MF .deps/ta_VAR.Tpo -c ta_VAR.c  -fPIC -DPIC -o .libs/ta_VAR.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_VAR.lo -MD -MP -MF .deps/ta_VAR.Tpo -c ta_VAR.c -o ta_VAR.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_VAR.Tpo .deps/ta_VAR.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_WCLPRICE.lo -MD -MP -MF .deps/ta_WCLPRICE.Tpo -c -o ta_WCLPRICE.lo ta_WCLPRICE.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_WCLPRICE.lo -MD -MP -MF .deps/ta_WCLPRICE.Tpo -c ta_WCLPRICE.c  -fPIC -DPIC -o .libs/ta_WCLPRICE.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_WCLPRICE.lo -MD -MP -MF .deps/ta_WCLPRICE.Tpo -c ta_WCLPRICE.c -o ta_WCLPRICE.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_WCLPRICE.Tpo .deps/ta_WCLPRICE.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_WILLR.lo -MD -MP -MF .deps/ta_WILLR.Tpo -c -o ta_WILLR.lo ta_WILLR.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_WILLR.lo -MD -MP -MF .deps/ta_WILLR.Tpo -c ta_WILLR.c  -fPIC -DPIC -o .libs/ta_WILLR.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_WILLR.lo -MD -MP -MF .deps/ta_WILLR.Tpo -c ta_WILLR.c -o ta_WILLR.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_WILLR.Tpo .deps/ta_WILLR.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=compile gcc -DHAVE_CONFIG_H -I. -I../../include  -I../ta_common/   -g -O2 -MT ta_WMA.lo -MD -MP -MF .deps/ta_WMA.Tpo -c -o ta_WMA.lo ta_WMA.c\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_WMA.lo -MD -MP -MF .deps/ta_WMA.Tpo -c ta_WMA.c  -fPIC -DPIC -o .libs/ta_WMA.o\n",
            " gcc -DHAVE_CONFIG_H -I. -I../../include -I../ta_common/ -g -O2 -MT ta_WMA.lo -MD -MP -MF .deps/ta_WMA.Tpo -c ta_WMA.c -o ta_WMA.o >/dev/null 2>&1\n",
            "mv -f .deps/ta_WMA.Tpo .deps/ta_WMA.Plo\n",
            "/bin/bash ../../libtool --tag=CC   --mode=link gcc  -g -O2 -version-info 0:0:0  -o libta_func.la  ta_utility.lo ta_ACOS.lo ta_AD.lo ta_ADD.lo ta_ADOSC.lo ta_ADX.lo ta_ADXR.lo ta_APO.lo ta_AROON.lo ta_AROONOSC.lo ta_ASIN.lo ta_ATAN.lo ta_ATR.lo ta_AVGPRICE.lo ta_BBANDS.lo ta_BETA.lo ta_BOP.lo ta_CCI.lo ta_CDL2CROWS.lo ta_CDL3BLACKCROWS.lo ta_CDL3INSIDE.lo ta_CDL3LINESTRIKE.lo ta_CDL3OUTSIDE.lo ta_CDL3STARSINSOUTH.lo ta_CDL3WHITESOLDIERS.lo ta_CDLABANDONEDBABY.lo ta_CDLADVANCEBLOCK.lo ta_CDLBELTHOLD.lo ta_CDLBREAKAWAY.lo ta_CDLCLOSINGMARUBOZU.lo ta_CDLCONCEALBABYSWALL.lo ta_CDLCOUNTERATTACK.lo ta_CDLDARKCLOUDCOVER.lo ta_CDLDOJI.lo ta_CDLDOJISTAR.lo ta_CDLDRAGONFLYDOJI.lo ta_CDLENGULFING.lo ta_CDLEVENINGDOJISTAR.lo ta_CDLEVENINGSTAR.lo ta_CDLGAPSIDESIDEWHITE.lo ta_CDLGRAVESTONEDOJI.lo ta_CDLHAMMER.lo ta_CDLHANGINGMAN.lo ta_CDLHARAMI.lo ta_CDLHARAMICROSS.lo ta_CDLHIGHWAVE.lo ta_CDLHIKKAKE.lo ta_CDLHIKKAKEMOD.lo ta_CDLHOMINGPIGEON.lo ta_CDLIDENTICAL3CROWS.lo ta_CDLINNECK.lo ta_CDLINVERTEDHAMMER.lo ta_CDLKICKING.lo ta_CDLKICKINGBYLENGTH.lo ta_CDLLADDERBOTTOM.lo ta_CDLLONGLEGGEDDOJI.lo ta_CDLLONGLINE.lo ta_CDLMARUBOZU.lo ta_CDLMATCHINGLOW.lo ta_CDLMATHOLD.lo ta_CDLMORNINGDOJISTAR.lo ta_CDLMORNINGSTAR.lo ta_CDLONNECK.lo ta_CDLPIERCING.lo ta_CDLRICKSHAWMAN.lo ta_CDLRISEFALL3METHODS.lo ta_CDLSEPARATINGLINES.lo ta_CDLSHOOTINGSTAR.lo ta_CDLSHORTLINE.lo ta_CDLSPINNINGTOP.lo ta_CDLSTALLEDPATTERN.lo ta_CDLSTICKSANDWICH.lo ta_CDLTAKURI.lo ta_CDLTASUKIGAP.lo ta_CDLTHRUSTING.lo ta_CDLTRISTAR.lo ta_CDLUNIQUE3RIVER.lo ta_CDLUPSIDEGAP2CROWS.lo ta_CDLXSIDEGAP3METHODS.lo ta_CEIL.lo ta_CMO.lo ta_CORREL.lo ta_COS.lo ta_COSH.lo ta_DEMA.lo ta_DIV.lo ta_DX.lo ta_EMA.lo ta_EXP.lo ta_FLOOR.lo ta_HT_DCPERIOD.lo ta_HT_DCPHASE.lo ta_HT_PHASOR.lo ta_HT_SINE.lo ta_HT_TRENDLINE.lo ta_HT_TRENDMODE.lo ta_KAMA.lo ta_LINEARREG.lo ta_LINEARREG_ANGLE.lo ta_LINEARREG_INTERCEPT.lo ta_LINEARREG_SLOPE.lo ta_LN.lo ta_LOG10.lo ta_MA.lo ta_MACD.lo ta_MACDEXT.lo ta_MACDFIX.lo ta_MAMA.lo ta_MAVP.lo ta_MAX.lo ta_MAXINDEX.lo ta_MEDPRICE.lo ta_MFI.lo ta_MIDPOINT.lo ta_MIDPRICE.lo ta_MIN.lo ta_MININDEX.lo ta_MINMAX.lo ta_MINMAXINDEX.lo ta_MINUS_DI.lo ta_MINUS_DM.lo ta_MOM.lo ta_MULT.lo ta_NATR.lo ta_OBV.lo ta_PLUS_DI.lo ta_PLUS_DM.lo ta_PPO.lo ta_ROC.lo ta_ROCP.lo ta_ROCR.lo ta_ROCR100.lo ta_RSI.lo ta_SAR.lo ta_SAREXT.lo ta_SIN.lo ta_SINH.lo ta_SMA.lo ta_SQRT.lo ta_STDDEV.lo ta_STOCH.lo ta_STOCHF.lo ta_STOCHRSI.lo ta_SUB.lo ta_SUM.lo ta_T3.lo ta_TAN.lo ta_TANH.lo ta_TEMA.lo ta_TRANGE.lo ta_TRIMA.lo ta_TRIX.lo ta_TSF.lo ta_TYPPRICE.lo ta_ULTOSC.lo ta_VAR.lo ta_WCLPRICE.lo ta_WILLR.lo ta_WMA.lo  -lpthread -ldl \n",
            "libtool: link: warning: `-version-info/-version-number' is ignored for convenience libraries\n",
            "ar cru .libs/libta_func.a .libs/ta_utility.o .libs/ta_ACOS.o .libs/ta_AD.o .libs/ta_ADD.o .libs/ta_ADOSC.o .libs/ta_ADX.o .libs/ta_ADXR.o .libs/ta_APO.o .libs/ta_AROON.o .libs/ta_AROONOSC.o .libs/ta_ASIN.o .libs/ta_ATAN.o .libs/ta_ATR.o .libs/ta_AVGPRICE.o .libs/ta_BBANDS.o .libs/ta_BETA.o .libs/ta_BOP.o .libs/ta_CCI.o .libs/ta_CDL2CROWS.o .libs/ta_CDL3BLACKCROWS.o .libs/ta_CDL3INSIDE.o .libs/ta_CDL3LINESTRIKE.o .libs/ta_CDL3OUTSIDE.o .libs/ta_CDL3STARSINSOUTH.o .libs/ta_CDL3WHITESOLDIERS.o .libs/ta_CDLABANDONEDBABY.o .libs/ta_CDLADVANCEBLOCK.o .libs/ta_CDLBELTHOLD.o .libs/ta_CDLBREAKAWAY.o .libs/ta_CDLCLOSINGMARUBOZU.o .libs/ta_CDLCONCEALBABYSWALL.o .libs/ta_CDLCOUNTERATTACK.o .libs/ta_CDLDARKCLOUDCOVER.o .libs/ta_CDLDOJI.o .libs/ta_CDLDOJISTAR.o .libs/ta_CDLDRAGONFLYDOJI.o .libs/ta_CDLENGULFING.o .libs/ta_CDLEVENINGDOJISTAR.o .libs/ta_CDLEVENINGSTAR.o .libs/ta_CDLGAPSIDESIDEWHITE.o .libs/ta_CDLGRAVESTONEDOJI.o .libs/ta_CDLHAMMER.o .libs/ta_CDLHANGINGMAN.o .libs/ta_CDLHARAMI.o .libs/ta_CDLHARAMICROSS.o .libs/ta_CDLHIGHWAVE.o .libs/ta_CDLHIKKAKE.o .libs/ta_CDLHIKKAKEMOD.o .libs/ta_CDLHOMINGPIGEON.o .libs/ta_CDLIDENTICAL3CROWS.o .libs/ta_CDLINNECK.o .libs/ta_CDLINVERTEDHAMMER.o .libs/ta_CDLKICKING.o .libs/ta_CDLKICKINGBYLENGTH.o .libs/ta_CDLLADDERBOTTOM.o .libs/ta_CDLLONGLEGGEDDOJI.o .libs/ta_CDLLONGLINE.o .libs/ta_CDLMARUBOZU.o .libs/ta_CDLMATCHINGLOW.o .libs/ta_CDLMATHOLD.o .libs/ta_CDLMORNINGDOJISTAR.o .libs/ta_CDLMORNINGSTAR.o .libs/ta_CDLONNECK.o .libs/ta_CDLPIERCING.o .libs/ta_CDLRICKSHAWMAN.o .libs/ta_CDLRISEFALL3METHODS.o .libs/ta_CDLSEPARATINGLINES.o .libs/ta_CDLSHOOTINGSTAR.o .libs/ta_CDLSHORTLINE.o .libs/ta_CDLSPINNINGTOP.o .libs/ta_CDLSTALLEDPATTERN.o .libs/ta_CDLSTICKSANDWICH.o .libs/ta_CDLTAKURI.o .libs/ta_CDLTASUKIGAP.o .libs/ta_CDLTHRUSTING.o .libs/ta_CDLTRISTAR.o .libs/ta_CDLUNIQUE3RIVER.o .libs/ta_CDLUPSIDEGAP2CROWS.o .libs/ta_CDLXSIDEGAP3METHODS.o .libs/ta_CEIL.o .libs/ta_CMO.o .libs/ta_CORREL.o .libs/ta_COS.o .libs/ta_COSH.o .libs/ta_DEMA.o .libs/ta_DIV.o .libs/ta_DX.o .libs/ta_EMA.o .libs/ta_EXP.o .libs/ta_FLOOR.o .libs/ta_HT_DCPERIOD.o .libs/ta_HT_DCPHASE.o .libs/ta_HT_PHASOR.o .libs/ta_HT_SINE.o .libs/ta_HT_TRENDLINE.o .libs/ta_HT_TRENDMODE.o .libs/ta_KAMA.o .libs/ta_LINEARREG.o .libs/ta_LINEARREG_ANGLE.o .libs/ta_LINEARREG_INTERCEPT.o .libs/ta_LINEARREG_SLOPE.o .libs/ta_LN.o .libs/ta_LOG10.o .libs/ta_MA.o .libs/ta_MACD.o .libs/ta_MACDEXT.o .libs/ta_MACDFIX.o .libs/ta_MAMA.o .libs/ta_MAVP.o .libs/ta_MAX.o .libs/ta_MAXINDEX.o .libs/ta_MEDPRICE.o .libs/ta_MFI.o .libs/ta_MIDPOINT.o .libs/ta_MIDPRICE.o .libs/ta_MIN.o .libs/ta_MININDEX.o .libs/ta_MINMAX.o .libs/ta_MINMAXINDEX.o .libs/ta_MINUS_DI.o .libs/ta_MINUS_DM.o .libs/ta_MOM.o .libs/ta_MULT.o .libs/ta_NATR.o .libs/ta_OBV.o .libs/ta_PLUS_DI.o .libs/ta_PLUS_DM.o .libs/ta_PPO.o .libs/ta_ROC.o .libs/ta_ROCP.o .libs/ta_ROCR.o .libs/ta_ROCR100.o .libs/ta_RSI.o .libs/ta_SAR.o .libs/ta_SAREXT.o .libs/ta_SIN.o .libs/ta_SINH.o .libs/ta_SMA.o .libs/ta_SQRT.o .libs/ta_STDDEV.o .libs/ta_STOCH.o .libs/ta_STOCHF.o .libs/ta_STOCHRSI.o .libs/ta_SUB.o .libs/ta_SUM.o .libs/ta_T3.o .libs/ta_TAN.o .libs/ta_TANH.o .libs/ta_TEMA.o .libs/ta_TRANGE.o .libs/ta_TRIMA.o .libs/ta_TRIX.o .libs/ta_TSF.o .libs/ta_TYPPRICE.o .libs/ta_ULTOSC.o .libs/ta_VAR.o .libs/ta_WCLPRICE.o .libs/ta_WILLR.o .libs/ta_WMA.o\n",
            "ar: `u' modifier ignored since `D' is the default (see `U')\n",
            "ranlib .libs/libta_func.a\n",
            "creating libta_func.la\n",
            "(cd .libs && rm -f libta_func.la && ln -s ../libta_func.la libta_func.la)\n",
            "make[2]: Leaving directory '/content/ta-lib/src/ta_func'\n",
            "make[2]: Entering directory '/content/ta-lib/src'\n",
            "/bin/bash ../libtool --tag=CC   --mode=link gcc  -g -O2 -version-info 0:0:0  -o libta_lib.la -rpath /usr/lib  ta_abstract/libta_abstract.la ta_func/libta_func.la ta_common/libta_common.la -lpthread -ldl \n",
            "mkdir .libs\n",
            "gcc -shared  -Wl,--whole-archive ta_abstract/.libs/libta_abstract.a ta_func/.libs/libta_func.a ta_common/.libs/libta_common.a -Wl,--no-whole-archive  -lpthread -ldl  -Wl,-soname -Wl,libta_lib.so.0 -o .libs/libta_lib.so.0.0.0\n",
            "(cd .libs && rm -f libta_lib.so.0 && ln -s libta_lib.so.0.0.0 libta_lib.so.0)\n",
            "(cd .libs && rm -f libta_lib.so && ln -s libta_lib.so.0.0.0 libta_lib.so)\n",
            "rm -fr .libs/libta_lib.lax\n",
            "mkdir .libs/libta_lib.lax\n",
            "rm -fr .libs/libta_lib.lax/libta_abstract.a\n",
            "mkdir .libs/libta_lib.lax/libta_abstract.a\n",
            "(cd .libs/libta_lib.lax/libta_abstract.a && ar x /content/ta-lib/src/ta_abstract/.libs/libta_abstract.a)\n",
            "rm -fr .libs/libta_lib.lax/libta_func.a\n",
            "mkdir .libs/libta_lib.lax/libta_func.a\n",
            "(cd .libs/libta_lib.lax/libta_func.a && ar x /content/ta-lib/src/ta_func/.libs/libta_func.a)\n",
            "rm -fr .libs/libta_lib.lax/libta_common.a\n",
            "mkdir .libs/libta_lib.lax/libta_common.a\n",
            "(cd .libs/libta_lib.lax/libta_common.a && ar x /content/ta-lib/src/ta_common/.libs/libta_common.a)\n",
            "ar cru .libs/libta_lib.a   .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-ta_group_idx.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_q.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_z.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_w.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-ta_def_ui.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_r.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-ta_frame.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_d.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_n.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_c.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_e.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_a.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-ta_abstract.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_v.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_h.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_x.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_g.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_u.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_o.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_p.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_b.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_l.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-ta_func_api.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_j.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_m.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_i.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_t.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_y.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_k.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_s.o .libs/libta_lib.lax/libta_abstract.a/libta_abstract_la-table_f.o  .libs/libta_lib.lax/libta_func.a/ta_AROONOSC.o .libs/libta_lib.lax/libta_func.a/ta_SAR.o .libs/libta_lib.lax/libta_func.a/ta_EXP.o .libs/libta_lib.lax/libta_func.a/ta_ASIN.o .libs/libta_lib.lax/libta_func.a/ta_AD.o .libs/libta_lib.lax/libta_func.a/ta_CDLBREAKAWAY.o .libs/libta_lib.lax/libta_func.a/ta_ADX.o .libs/libta_lib.lax/libta_func.a/ta_TYPPRICE.o .libs/libta_lib.lax/libta_func.a/ta_SMA.o .libs/libta_lib.lax/libta_func.a/ta_TAN.o .libs/libta_lib.lax/libta_func.a/ta_DX.o .libs/libta_lib.lax/libta_func.a/ta_CDLSHORTLINE.o .libs/libta_lib.lax/libta_func.a/ta_CCI.o .libs/libta_lib.lax/libta_func.a/ta_MIN.o .libs/libta_lib.lax/libta_func.a/ta_FLOOR.o .libs/libta_lib.lax/libta_func.a/ta_PLUS_DM.o .libs/libta_lib.lax/libta_func.a/ta_T3.o .libs/libta_lib.lax/libta_func.a/ta_CDLSTALLEDPATTERN.o .libs/libta_lib.lax/libta_func.a/ta_MULT.o .libs/libta_lib.lax/libta_func.a/ta_MAX.o .libs/libta_lib.lax/libta_func.a/ta_CDLDOJISTAR.o .libs/libta_lib.lax/libta_func.a/ta_CDLHARAMICROSS.o .libs/libta_lib.lax/libta_func.a/ta_CDLMORNINGDOJISTAR.o .libs/libta_lib.lax/libta_func.a/ta_CDLMATHOLD.o .libs/libta_lib.lax/libta_func.a/ta_ROCR100.o .libs/libta_lib.lax/libta_func.a/ta_CDLIDENTICAL3CROWS.o .libs/libta_lib.lax/libta_func.a/ta_PPO.o .libs/libta_lib.lax/libta_func.a/ta_STOCHRSI.o .libs/libta_lib.lax/libta_func.a/ta_MINMAX.o .libs/libta_lib.lax/libta_func.a/ta_MIDPOINT.o .libs/libta_lib.lax/libta_func.a/ta_MACDFIX.o .libs/libta_lib.lax/libta_func.a/ta_MIDPRICE.o .libs/libta_lib.lax/libta_func.a/ta_ADD.o .libs/libta_lib.lax/libta_func.a/ta_EMA.o .libs/libta_lib.lax/libta_func.a/ta_CDLHAMMER.o .libs/libta_lib.lax/libta_func.a/ta_CDLKICKING.o .libs/libta_lib.lax/libta_func.a/ta_AVGPRICE.o .libs/libta_lib.lax/libta_func.a/ta_LINEARREG_SLOPE.o .libs/libta_lib.lax/libta_func.a/ta_CDLMATCHINGLOW.o .libs/libta_lib.lax/libta_func.a/ta_SINH.o .libs/libta_lib.lax/libta_func.a/ta_CDLINVERTEDHAMMER.o .libs/libta_lib.lax/libta_func.a/ta_MININDEX.o .libs/libta_lib.lax/libta_func.a/ta_WCLPRICE.o .libs/libta_lib.lax/libta_func.a/ta_SAREXT.o .libs/libta_lib.lax/libta_func.a/ta_STOCHF.o .libs/libta_lib.lax/libta_func.a/ta_HT_SINE.o .libs/libta_lib.lax/libta_func.a/ta_HT_PHASOR.o .libs/libta_lib.lax/libta_func.a/ta_ADXR.o .libs/libta_lib.lax/libta_func.a/ta_TANH.o .libs/libta_lib.lax/libta_func.a/ta_CDL3OUTSIDE.o .libs/libta_lib.lax/libta_func.a/ta_WMA.o .libs/libta_lib.lax/libta_func.a/ta_STDDEV.o .libs/libta_lib.lax/libta_func.a/ta_CDLENGULFING.o .libs/libta_lib.lax/libta_func.a/ta_SIN.o .libs/libta_lib.lax/libta_func.a/ta_CORREL.o .libs/libta_lib.lax/libta_func.a/ta_TRANGE.o .libs/libta_lib.lax/libta_func.a/ta_SQRT.o .libs/libta_lib.lax/libta_func.a/ta_CDLSEPARATINGLINES.o .libs/libta_lib.lax/libta_func.a/ta_CDLMARUBOZU.o .libs/libta_lib.lax/libta_func.a/ta_CDLEVENINGDOJISTAR.o .libs/libta_lib.lax/libta_func.a/ta_CDLSHOOTINGSTAR.o .libs/libta_lib.lax/libta_func.a/ta_CDLRISEFALL3METHODS.o .libs/libta_lib.lax/libta_func.a/ta_SUM.o .libs/libta_lib.lax/libta_func.a/ta_CDLHIKKAKE.o .libs/libta_lib.lax/libta_func.a/ta_MOM.o .libs/libta_lib.lax/libta_func.a/ta_CDL3LINESTRIKE.o .libs/libta_lib.lax/libta_func.a/ta_TRIX.o .libs/libta_lib.lax/libta_func.a/ta_HT_TRENDMODE.o .libs/libta_lib.lax/libta_func.a/ta_LINEARREG.o .libs/libta_lib.lax/libta_func.a/ta_NATR.o .libs/libta_lib.lax/libta_func.a/ta_CDL2CROWS.o .libs/libta_lib.lax/libta_func.a/ta_CDLHOMINGPIGEON.o .libs/libta_lib.lax/libta_func.a/ta_CDLCONCEALBABYSWALL.o .libs/libta_lib.lax/libta_func.a/ta_CDL3INSIDE.o .libs/libta_lib.lax/libta_func.a/ta_SUB.o .libs/libta_lib.lax/libta_func.a/ta_MEDPRICE.o .libs/libta_lib.lax/libta_func.a/ta_CDLLADDERBOTTOM.o .libs/libta_lib.lax/libta_func.a/ta_utility.o .libs/libta_lib.lax/libta_func.a/ta_CDLHIGHWAVE.o .libs/libta_lib.lax/libta_func.a/ta_CDLSTICKSANDWICH.o .libs/libta_lib.lax/libta_func.a/ta_MAVP.o .libs/libta_lib.lax/libta_func.a/ta_AROON.o .libs/libta_lib.lax/libta_func.a/ta_COS.o .libs/libta_lib.lax/libta_func.a/ta_CDLHANGINGMAN.o .libs/libta_lib.lax/libta_func.a/ta_ULTOSC.o .libs/libta_lib.lax/libta_func.a/ta_TEMA.o .libs/libta_lib.lax/libta_func.a/ta_CDLLONGLINE.o .libs/libta_lib.lax/libta_func.a/ta_PLUS_DI.o .libs/libta_lib.lax/libta_func.a/ta_BBANDS.o .libs/libta_lib.lax/libta_func.a/ta_LINEARREG_INTERCEPT.o .libs/libta_lib.lax/libta_func.a/ta_MINUS_DI.o .libs/libta_lib.lax/libta_func.a/ta_TSF.o .libs/libta_lib.lax/libta_func.a/ta_CDLBELTHOLD.o .libs/libta_lib.lax/libta_func.a/ta_BOP.o .libs/libta_lib.lax/libta_func.a/ta_DIV.o .libs/libta_lib.lax/libta_func.a/ta_DEMA.o .libs/libta_lib.lax/libta_func.a/ta_VAR.o .libs/libta_lib.lax/libta_func.a/ta_CDLDRAGONFLYDOJI.o .libs/libta_lib.lax/libta_func.a/ta_ADOSC.o .libs/libta_lib.lax/libta_func.a/ta_CDLADVANCEBLOCK.o .libs/libta_lib.lax/libta_func.a/ta_CDLINNECK.o .libs/libta_lib.lax/libta_func.a/ta_MFI.o .libs/libta_lib.lax/libta_func.a/ta_CDLPIERCING.o .libs/libta_lib.lax/libta_func.a/ta_COSH.o .libs/libta_lib.lax/libta_func.a/ta_CDL3WHITESOLDIERS.o .libs/libta_lib.lax/libta_func.a/ta_CDLABANDONEDBABY.o .libs/libta_lib.lax/libta_func.a/ta_LINEARREG_ANGLE.o .libs/libta_lib.lax/libta_func.a/ta_CDLTAKURI.o .libs/libta_lib.lax/libta_func.a/ta_CDL3BLACKCROWS.o .libs/libta_lib.lax/libta_func.a/ta_MAXINDEX.o .libs/libta_lib.lax/libta_func.a/ta_HT_TRENDLINE.o .libs/libta_lib.lax/libta_func.a/ta_TRIMA.o .libs/libta_lib.lax/libta_func.a/ta_MA.o .libs/libta_lib.lax/libta_func.a/ta_CDLDARKCLOUDCOVER.o .libs/libta_lib.lax/libta_func.a/ta_LN.o .libs/libta_lib.lax/libta_func.a/ta_MACD.o .libs/libta_lib.lax/libta_func.a/ta_ROC.o .libs/libta_lib.lax/libta_func.a/ta_ATAN.o .libs/libta_lib.lax/libta_func.a/ta_CDLTRISTAR.o .libs/libta_lib.lax/libta_func.a/ta_MINMAXINDEX.o .libs/libta_lib.lax/libta_func.a/ta_ACOS.o .libs/libta_lib.lax/libta_func.a/ta_CDLLONGLEGGEDDOJI.o .libs/libta_lib.lax/libta_func.a/ta_CDLTHRUSTING.o .libs/libta_lib.lax/libta_func.a/ta_CDLEVENINGSTAR.o .libs/libta_lib.lax/libta_func.a/ta_APO.o .libs/libta_lib.lax/libta_func.a/ta_CDLXSIDEGAP3METHODS.o .libs/libta_lib.lax/libta_func.a/ta_HT_DCPERIOD.o .libs/libta_lib.lax/libta_func.a/ta_MAMA.o .libs/libta_lib.lax/libta_func.a/ta_CDLDOJI.o .libs/libta_lib.lax/libta_func.a/ta_ATR.o .libs/libta_lib.lax/libta_func.a/ta_ROCP.o .libs/libta_lib.lax/libta_func.a/ta_OBV.o .libs/libta_lib.lax/libta_func.a/ta_CDLUNIQUE3RIVER.o .libs/libta_lib.lax/libta_func.a/ta_LOG10.o .libs/libta_lib.lax/libta_func.a/ta_CDLCLOSINGMARUBOZU.o .libs/libta_lib.lax/libta_func.a/ta_CDLHARAMI.o .libs/libta_lib.lax/libta_func.a/ta_CDLCOUNTERATTACK.o .libs/libta_lib.lax/libta_func.a/ta_HT_DCPHASE.o .libs/libta_lib.lax/libta_func.a/ta_CDLHIKKAKEMOD.o .libs/libta_lib.lax/libta_func.a/ta_KAMA.o .libs/libta_lib.lax/libta_func.a/ta_CDLRICKSHAWMAN.o .libs/libta_lib.lax/libta_func.a/ta_RSI.o .libs/libta_lib.lax/libta_func.a/ta_CMO.o .libs/libta_lib.lax/libta_func.a/ta_CDLSPINNINGTOP.o .libs/libta_lib.lax/libta_func.a/ta_CDLUPSIDEGAP2CROWS.o .libs/libta_lib.lax/libta_func.a/ta_CDLGRAVESTONEDOJI.o .libs/libta_lib.lax/libta_func.a/ta_CEIL.o .libs/libta_lib.lax/libta_func.a/ta_CDL3STARSINSOUTH.o .libs/libta_lib.lax/libta_func.a/ta_CDLONNECK.o .libs/libta_lib.lax/libta_func.a/ta_CDLGAPSIDESIDEWHITE.o .libs/libta_lib.lax/libta_func.a/ta_BETA.o .libs/libta_lib.lax/libta_func.a/ta_CDLMORNINGSTAR.o .libs/libta_lib.lax/libta_func.a/ta_MACDEXT.o .libs/libta_lib.lax/libta_func.a/ta_MINUS_DM.o .libs/libta_lib.lax/libta_func.a/ta_ROCR.o .libs/libta_lib.lax/libta_func.a/ta_CDLKICKINGBYLENGTH.o .libs/libta_lib.lax/libta_func.a/ta_STOCH.o .libs/libta_lib.lax/libta_func.a/ta_WILLR.o .libs/libta_lib.lax/libta_func.a/ta_CDLTASUKIGAP.o  .libs/libta_lib.lax/libta_common.a/ta_version.o .libs/libta_lib.lax/libta_common.a/ta_global.o .libs/libta_lib.lax/libta_common.a/ta_retcode.o \n",
            "ar: `u' modifier ignored since `D' is the default (see `U')\n",
            "ranlib .libs/libta_lib.a\n",
            "rm -fr .libs/libta_lib.lax\n",
            "creating libta_lib.la\n",
            "(cd .libs && rm -f libta_lib.la && ln -s ../libta_lib.la libta_lib.la)\n",
            "make[2]: Leaving directory '/content/ta-lib/src'\n",
            "make[1]: Leaving directory '/content/ta-lib/src'\n",
            "Making all in src/tools\n",
            "make[1]: Entering directory '/content/ta-lib/src/tools'\n",
            "Making all in gen_code\n",
            "make[2]: Entering directory '/content/ta-lib/src/tools/gen_code'\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_common   -g -O2 -MT gen_code-gen_code.o -MD -MP -MF .deps/gen_code-gen_code.Tpo -c -o gen_code-gen_code.o `test -f 'gen_code.c' || echo './'`gen_code.c\n",
            "\u001b[01m\u001b[Kgen_code.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[KprintFuncHeaderDoc\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[Kgen_code.c:3456:4:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[Kformat not a string literal and no format arguments [\u001b[01;35m\u001b[K\u001b]8;;https://gcc.gnu.org/onlinedocs/gcc/Warning-Options.html#index-Wformat-security\u0007-Wformat-security\u001b]8;;\u0007\u001b[m\u001b[K]\n",
            " 3456 |    \u001b[01;35m\u001b[Kfprintf\u001b[m\u001b[K( out, prefix );\n",
            "      |    \u001b[01;35m\u001b[K^~~~~~~\u001b[m\u001b[K\n",
            "mv -f .deps/gen_code-gen_code.Tpo .deps/gen_code-gen_code.Po\n",
            "/bin/bash ../../../libtool --tag=CC   --mode=link gcc  -g -O2 -L../../ta_common -L../../ta_abstract -L../../ta_func  -o gen_code gen_code-gen_code.o -lta_common -lta_abstract_gc -lta_func -lm -lpthread -ldl \n",
            "mkdir .libs\n",
            "gcc -g -O2 -o gen_code gen_code-gen_code.o  -L/content/ta-lib/src/ta_common -L/content/ta-lib/src/ta_abstract -L/content/ta-lib/src/ta_func /content/ta-lib/src/ta_common/.libs/libta_common.a /content/ta-lib/src/ta_abstract/.libs/libta_abstract_gc.a /content/ta-lib/src/ta_func/.libs/libta_func.a -lm -lpthread -ldl\n",
            "make  gen_code\n",
            "make[3]: Entering directory '/content/ta-lib/src/tools/gen_code'\n",
            "make[3]: 'gen_code' is up to date.\n",
            "make[3]: Leaving directory '/content/ta-lib/src/tools/gen_code'\n",
            "cp gen_code ../../../bin\n",
            "make[2]: Leaving directory '/content/ta-lib/src/tools/gen_code'\n",
            "Making all in ta_regtest\n",
            "make[2]: Entering directory '/content/ta-lib/src/tools/ta_regtest'\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-ta_regtest.o -MD -MP -MF .deps/ta_regtest-ta_regtest.Tpo -c -o ta_regtest-ta_regtest.o `test -f 'ta_regtest.c' || echo './'`ta_regtest.c\n",
            "mv -f .deps/ta_regtest-ta_regtest.Tpo .deps/ta_regtest-ta_regtest.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_data.o -MD -MP -MF .deps/ta_regtest-test_data.Tpo -c -o ta_regtest-test_data.o `test -f 'test_data.c' || echo './'`test_data.c\n",
            "mv -f .deps/ta_regtest-test_data.Tpo .deps/ta_regtest-test_data.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_util.o -MD -MP -MF .deps/ta_regtest-test_util.Tpo -c -o ta_regtest-test_util.o `test -f 'test_util.c' || echo './'`test_util.c\n",
            "mv -f .deps/ta_regtest-test_util.Tpo .deps/ta_regtest-test_util.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_abstract.o -MD -MP -MF .deps/ta_regtest-test_abstract.Tpo -c -o ta_regtest-test_abstract.o `test -f 'test_abstract.c' || echo './'`test_abstract.c\n",
            "mv -f .deps/ta_regtest-test_abstract.Tpo .deps/ta_regtest-test_abstract.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_adx.o -MD -MP -MF .deps/ta_regtest-test_adx.Tpo -c -o ta_regtest-test_adx.o `test -f 'ta_test_func/test_adx.c' || echo './'`ta_test_func/test_adx.c\n",
            "mv -f .deps/ta_regtest-test_adx.Tpo .deps/ta_regtest-test_adx.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_mom.o -MD -MP -MF .deps/ta_regtest-test_mom.Tpo -c -o ta_regtest-test_mom.o `test -f 'ta_test_func/test_mom.c' || echo './'`ta_test_func/test_mom.c\n",
            "mv -f .deps/ta_regtest-test_mom.Tpo .deps/ta_regtest-test_mom.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_sar.o -MD -MP -MF .deps/ta_regtest-test_sar.Tpo -c -o ta_regtest-test_sar.o `test -f 'ta_test_func/test_sar.c' || echo './'`ta_test_func/test_sar.c\n",
            "mv -f .deps/ta_regtest-test_sar.Tpo .deps/ta_regtest-test_sar.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_rsi.o -MD -MP -MF .deps/ta_regtest-test_rsi.Tpo -c -o ta_regtest-test_rsi.o `test -f 'ta_test_func/test_rsi.c' || echo './'`ta_test_func/test_rsi.c\n",
            "mv -f .deps/ta_regtest-test_rsi.Tpo .deps/ta_regtest-test_rsi.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_candlestick.o -MD -MP -MF .deps/ta_regtest-test_candlestick.Tpo -c -o ta_regtest-test_candlestick.o `test -f 'ta_test_func/test_candlestick.c' || echo './'`ta_test_func/test_candlestick.c\n",
            "mv -f .deps/ta_regtest-test_candlestick.Tpo .deps/ta_regtest-test_candlestick.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_per_ema.o -MD -MP -MF .deps/ta_regtest-test_per_ema.Tpo -c -o ta_regtest-test_per_ema.o `test -f 'ta_test_func/test_per_ema.c' || echo './'`ta_test_func/test_per_ema.c\n",
            "mv -f .deps/ta_regtest-test_per_ema.Tpo .deps/ta_regtest-test_per_ema.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_per_hlc.o -MD -MP -MF .deps/ta_regtest-test_per_hlc.Tpo -c -o ta_regtest-test_per_hlc.o `test -f 'ta_test_func/test_per_hlc.c' || echo './'`ta_test_func/test_per_hlc.c\n",
            "mv -f .deps/ta_regtest-test_per_hlc.Tpo .deps/ta_regtest-test_per_hlc.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_stoch.o -MD -MP -MF .deps/ta_regtest-test_stoch.Tpo -c -o ta_regtest-test_stoch.o `test -f 'ta_test_func/test_stoch.c' || echo './'`ta_test_func/test_stoch.c\n",
            "mv -f .deps/ta_regtest-test_stoch.Tpo .deps/ta_regtest-test_stoch.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_macd.o -MD -MP -MF .deps/ta_regtest-test_macd.Tpo -c -o ta_regtest-test_macd.o `test -f 'ta_test_func/test_macd.c' || echo './'`ta_test_func/test_macd.c\n",
            "mv -f .deps/ta_regtest-test_macd.Tpo .deps/ta_regtest-test_macd.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_minmax.o -MD -MP -MF .deps/ta_regtest-test_minmax.Tpo -c -o ta_regtest-test_minmax.o `test -f 'ta_test_func/test_minmax.c' || echo './'`ta_test_func/test_minmax.c\n",
            "mv -f .deps/ta_regtest-test_minmax.Tpo .deps/ta_regtest-test_minmax.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_per_hlcv.o -MD -MP -MF .deps/ta_regtest-test_per_hlcv.Tpo -c -o ta_regtest-test_per_hlcv.o `test -f 'ta_test_func/test_per_hlcv.c' || echo './'`ta_test_func/test_per_hlcv.c\n",
            "mv -f .deps/ta_regtest-test_per_hlcv.Tpo .deps/ta_regtest-test_per_hlcv.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_1in_1out.o -MD -MP -MF .deps/ta_regtest-test_1in_1out.Tpo -c -o ta_regtest-test_1in_1out.o `test -f 'ta_test_func/test_1in_1out.c' || echo './'`ta_test_func/test_1in_1out.c\n",
            "mv -f .deps/ta_regtest-test_1in_1out.Tpo .deps/ta_regtest-test_1in_1out.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_1in_2out.o -MD -MP -MF .deps/ta_regtest-test_1in_2out.Tpo -c -o ta_regtest-test_1in_2out.o `test -f 'ta_test_func/test_1in_2out.c' || echo './'`ta_test_func/test_1in_2out.c\n",
            "mv -f .deps/ta_regtest-test_1in_2out.Tpo .deps/ta_regtest-test_1in_2out.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_per_ohlc.o -MD -MP -MF .deps/ta_regtest-test_per_ohlc.Tpo -c -o ta_regtest-test_per_ohlc.o `test -f 'ta_test_func/test_per_ohlc.c' || echo './'`ta_test_func/test_per_ohlc.c\n",
            "mv -f .deps/ta_regtest-test_per_ohlc.Tpo .deps/ta_regtest-test_per_ohlc.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_stddev.o -MD -MP -MF .deps/ta_regtest-test_stddev.Tpo -c -o ta_regtest-test_stddev.o `test -f 'ta_test_func/test_stddev.c' || echo './'`ta_test_func/test_stddev.c\n",
            "mv -f .deps/ta_regtest-test_stddev.Tpo .deps/ta_regtest-test_stddev.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_bbands.o -MD -MP -MF .deps/ta_regtest-test_bbands.Tpo -c -o ta_regtest-test_bbands.o `test -f 'ta_test_func/test_bbands.c' || echo './'`ta_test_func/test_bbands.c\n",
            "mv -f .deps/ta_regtest-test_bbands.Tpo .deps/ta_regtest-test_bbands.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_ma.o -MD -MP -MF .deps/ta_regtest-test_ma.Tpo -c -o ta_regtest-test_ma.o `test -f 'ta_test_func/test_ma.c' || echo './'`ta_test_func/test_ma.c\n",
            "mv -f .deps/ta_regtest-test_ma.Tpo .deps/ta_regtest-test_ma.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_po.o -MD -MP -MF .deps/ta_regtest-test_po.Tpo -c -o ta_regtest-test_po.o `test -f 'ta_test_func/test_po.c' || echo './'`ta_test_func/test_po.c\n",
            "mv -f .deps/ta_regtest-test_po.Tpo .deps/ta_regtest-test_po.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_per_hl.o -MD -MP -MF .deps/ta_regtest-test_per_hl.Tpo -c -o ta_regtest-test_per_hl.o `test -f 'ta_test_func/test_per_hl.c' || echo './'`ta_test_func/test_per_hl.c\n",
            "mv -f .deps/ta_regtest-test_per_hl.Tpo .deps/ta_regtest-test_per_hl.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_trange.o -MD -MP -MF .deps/ta_regtest-test_trange.Tpo -c -o ta_regtest-test_trange.o `test -f 'ta_test_func/test_trange.c' || echo './'`ta_test_func/test_trange.c\n",
            "mv -f .deps/ta_regtest-test_trange.Tpo .deps/ta_regtest-test_trange.Po\n",
            "gcc -DHAVE_CONFIG_H -I. -I../../../include  -I../../ta_func -I../../ta_common/trio -I../../ta_common/mt -I../../ta_common -I../../ta_abstract   -g -O2 -MT ta_regtest-test_internals.o -MD -MP -MF .deps/ta_regtest-test_internals.Tpo -c -o ta_regtest-test_internals.o `test -f 'test_internals.c' || echo './'`test_internals.c\n",
            "mv -f .deps/ta_regtest-test_internals.Tpo .deps/ta_regtest-test_internals.Po\n",
            "/bin/bash ../../../libtool --tag=CC   --mode=link gcc  -g -O2 -L../.. -lta_lib -lm  -o ta_regtest ta_regtest-ta_regtest.o ta_regtest-test_data.o ta_regtest-test_util.o ta_regtest-test_abstract.o ta_regtest-test_adx.o ta_regtest-test_mom.o ta_regtest-test_sar.o ta_regtest-test_rsi.o ta_regtest-test_candlestick.o ta_regtest-test_per_ema.o ta_regtest-test_per_hlc.o ta_regtest-test_stoch.o ta_regtest-test_macd.o ta_regtest-test_minmax.o ta_regtest-test_per_hlcv.o ta_regtest-test_1in_1out.o ta_regtest-test_1in_2out.o ta_regtest-test_per_ohlc.o ta_regtest-test_stddev.o ta_regtest-test_bbands.o ta_regtest-test_ma.o ta_regtest-test_po.o ta_regtest-test_per_hl.o ta_regtest-test_trange.o ta_regtest-test_internals.o  -lpthread -ldl \n",
            "mkdir .libs\n",
            "gcc -g -O2 -o .libs/ta_regtest ta_regtest-ta_regtest.o ta_regtest-test_data.o ta_regtest-test_util.o ta_regtest-test_abstract.o ta_regtest-test_adx.o ta_regtest-test_mom.o ta_regtest-test_sar.o ta_regtest-test_rsi.o ta_regtest-test_candlestick.o ta_regtest-test_per_ema.o ta_regtest-test_per_hlc.o ta_regtest-test_stoch.o ta_regtest-test_macd.o ta_regtest-test_minmax.o ta_regtest-test_per_hlcv.o ta_regtest-test_1in_1out.o ta_regtest-test_1in_2out.o ta_regtest-test_per_ohlc.o ta_regtest-test_stddev.o ta_regtest-test_bbands.o ta_regtest-test_ma.o ta_regtest-test_po.o ta_regtest-test_per_hl.o ta_regtest-test_trange.o ta_regtest-test_internals.o  -L/content/ta-lib/src /content/ta-lib/src/.libs/libta_lib.so -lm -lpthread -ldl\n",
            "creating ta_regtest\n",
            "make[2]: Leaving directory '/content/ta-lib/src/tools/ta_regtest'\n",
            "make[2]: Entering directory '/content/ta-lib/src/tools'\n",
            "make[2]: Nothing to be done for 'all-am'.\n",
            "make[2]: Leaving directory '/content/ta-lib/src/tools'\n",
            "make[1]: Leaving directory '/content/ta-lib/src/tools'\n",
            "make[1]: Entering directory '/content/ta-lib'\n",
            "make[1]: Nothing to be done for 'all-am'.\n",
            "make[1]: Leaving directory '/content/ta-lib'\n",
            "Making install in src\n",
            "make[1]: Entering directory '/content/ta-lib/src'\n",
            "Making install in ta_abstract\n",
            "make[2]: Entering directory '/content/ta-lib/src/ta_abstract'\n",
            "make[3]: Entering directory '/content/ta-lib/src/ta_abstract'\n",
            "make[3]: Nothing to be done for 'install-exec-am'.\n",
            "test -z \"/usr/include/ta-lib/\" || /usr/bin/mkdir -p \"/usr/include/ta-lib/\"\n",
            " /usr/bin/install -c -m 644 '../../include/ta_defs.h' '/usr/include/ta-lib//ta_defs.h'\n",
            " /usr/bin/install -c -m 644 '../../include/ta_libc.h' '/usr/include/ta-lib//ta_libc.h'\n",
            " /usr/bin/install -c -m 644 '../../include/ta_abstract.h' '/usr/include/ta-lib//ta_abstract.h'\n",
            "make[3]: Leaving directory '/content/ta-lib/src/ta_abstract'\n",
            "make[2]: Leaving directory '/content/ta-lib/src/ta_abstract'\n",
            "Making install in ta_common\n",
            "make[2]: Entering directory '/content/ta-lib/src/ta_common'\n",
            "make[3]: Entering directory '/content/ta-lib/src/ta_common'\n",
            "make[3]: Nothing to be done for 'install-exec-am'.\n",
            "test -z \"/usr/include/ta-lib/\" || /usr/bin/mkdir -p \"/usr/include/ta-lib/\"\n",
            " /usr/bin/install -c -m 644 '../../include/ta_defs.h' '/usr/include/ta-lib//ta_defs.h'\n",
            " /usr/bin/install -c -m 644 '../../include/ta_libc.h' '/usr/include/ta-lib//ta_libc.h'\n",
            " /usr/bin/install -c -m 644 '../../include/ta_common.h' '/usr/include/ta-lib//ta_common.h'\n",
            "make[3]: Leaving directory '/content/ta-lib/src/ta_common'\n",
            "make[2]: Leaving directory '/content/ta-lib/src/ta_common'\n",
            "Making install in ta_func\n",
            "make[2]: Entering directory '/content/ta-lib/src/ta_func'\n",
            "make[3]: Entering directory '/content/ta-lib/src/ta_func'\n",
            "make[3]: Nothing to be done for 'install-exec-am'.\n",
            "test -z \"/usr/include/ta-lib/\" || /usr/bin/mkdir -p \"/usr/include/ta-lib/\"\n",
            " /usr/bin/install -c -m 644 '../../include/ta_defs.h' '/usr/include/ta-lib//ta_defs.h'\n",
            " /usr/bin/install -c -m 644 '../../include/ta_libc.h' '/usr/include/ta-lib//ta_libc.h'\n",
            " /usr/bin/install -c -m 644 '../../include/ta_func.h' '/usr/include/ta-lib//ta_func.h'\n",
            "make[3]: Leaving directory '/content/ta-lib/src/ta_func'\n",
            "make[2]: Leaving directory '/content/ta-lib/src/ta_func'\n",
            "make[2]: Entering directory '/content/ta-lib/src'\n",
            "make[3]: Entering directory '/content/ta-lib/src'\n",
            "test -z \"/usr/lib\" || /usr/bin/mkdir -p \"/usr/lib\"\n",
            " /bin/bash ../libtool --mode=install /usr/bin/install -c  'libta_lib.la' '/usr/lib/libta_lib.la'\n",
            "/usr/bin/install -c .libs/libta_lib.so.0.0.0 /usr/lib/libta_lib.so.0.0.0\n",
            "(cd /usr/lib && { ln -s -f libta_lib.so.0.0.0 libta_lib.so.0 || { rm -f libta_lib.so.0 && ln -s libta_lib.so.0.0.0 libta_lib.so.0; }; })\n",
            "(cd /usr/lib && { ln -s -f libta_lib.so.0.0.0 libta_lib.so || { rm -f libta_lib.so && ln -s libta_lib.so.0.0.0 libta_lib.so; }; })\n",
            "/usr/bin/install -c .libs/libta_lib.lai /usr/lib/libta_lib.la\n",
            "/usr/bin/install -c .libs/libta_lib.a /usr/lib/libta_lib.a\n",
            "chmod 644 /usr/lib/libta_lib.a\n",
            "ranlib /usr/lib/libta_lib.a\n",
            "PATH=\"$PATH:/sbin\" ldconfig -n /usr/lib\n",
            "----------------------------------------------------------------------\n",
            "Libraries have been installed in:\n",
            "   /usr/lib\n",
            "\n",
            "If you ever happen to want to link against installed libraries\n",
            "in a given directory, LIBDIR, you must either use libtool, and\n",
            "specify the full pathname of the library, or use the `-LLIBDIR'\n",
            "flag during linking and do at least one of the following:\n",
            "   - add LIBDIR to the `LD_LIBRARY_PATH' environment variable\n",
            "     during execution\n",
            "   - add LIBDIR to the `LD_RUN_PATH' environment variable\n",
            "     during linking\n",
            "   - use the `-Wl,--rpath -Wl,LIBDIR' linker flag\n",
            "   - have your system administrator add LIBDIR to `/etc/ld.so.conf'\n",
            "\n",
            "See any operating system documentation about shared libraries for\n",
            "more information, such as the ld(1) and ld.so(8) manual pages.\n",
            "----------------------------------------------------------------------\n",
            "make[3]: Nothing to be done for 'install-data-am'.\n",
            "make[3]: Leaving directory '/content/ta-lib/src'\n",
            "make[2]: Leaving directory '/content/ta-lib/src'\n",
            "make[1]: Leaving directory '/content/ta-lib/src'\n",
            "Making install in src/tools\n",
            "make[1]: Entering directory '/content/ta-lib/src/tools'\n",
            "Making install in gen_code\n",
            "make[2]: Entering directory '/content/ta-lib/src/tools/gen_code'\n",
            "make  gen_code\n",
            "make[3]: Entering directory '/content/ta-lib/src/tools/gen_code'\n",
            "make[3]: 'gen_code' is up to date.\n",
            "make[3]: Leaving directory '/content/ta-lib/src/tools/gen_code'\n",
            "cp gen_code ../../../bin\n",
            "make[3]: Entering directory '/content/ta-lib/src/tools/gen_code'\n",
            "make[3]: Nothing to be done for 'install-exec-am'.\n",
            "make[3]: Nothing to be done for 'install-data-am'.\n",
            "make[3]: Leaving directory '/content/ta-lib/src/tools/gen_code'\n",
            "make[2]: Leaving directory '/content/ta-lib/src/tools/gen_code'\n",
            "Making install in ta_regtest\n",
            "make[2]: Entering directory '/content/ta-lib/src/tools/ta_regtest'\n",
            "make[3]: Entering directory '/content/ta-lib/src/tools/ta_regtest'\n",
            "make[3]: Nothing to be done for 'install-exec-am'.\n",
            "make[3]: Nothing to be done for 'install-data-am'.\n",
            "make[3]: Leaving directory '/content/ta-lib/src/tools/ta_regtest'\n",
            "make[2]: Leaving directory '/content/ta-lib/src/tools/ta_regtest'\n",
            "make[2]: Entering directory '/content/ta-lib/src/tools'\n",
            "make[3]: Entering directory '/content/ta-lib/src/tools'\n",
            "make[3]: Nothing to be done for 'install-exec-am'.\n",
            "make[3]: Nothing to be done for 'install-data-am'.\n",
            "make[3]: Leaving directory '/content/ta-lib/src/tools'\n",
            "make[2]: Leaving directory '/content/ta-lib/src/tools'\n",
            "make[1]: Leaving directory '/content/ta-lib/src/tools'\n",
            "make[1]: Entering directory '/content/ta-lib'\n",
            "make[2]: Entering directory '/content/ta-lib'\n",
            "test -z \"/usr/bin\" || /usr/bin/mkdir -p \"/usr/bin\"\n",
            " /usr/bin/install -c 'ta-lib-config' '/usr/bin/ta-lib-config'\n",
            "make[2]: Nothing to be done for 'install-data-am'.\n",
            "make[2]: Leaving directory '/content/ta-lib'\n",
            "make[1]: Leaving directory '/content/ta-lib'\n",
            "Collecting TA-Lib\n",
            "  Downloading TA-Lib-0.4.28.tar.gz (357 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m357.1/357.1 kB\u001b[0m \u001b[31m3.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
            "  Installing backend dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from TA-Lib) (1.23.5)\n",
            "Building wheels for collected packages: TA-Lib\n",
            "  Building wheel for TA-Lib (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for TA-Lib: filename=TA_Lib-0.4.28-cp310-cp310-linux_x86_64.whl size=2017532 sha256=b4f983f0ca1084cd3b836afbda7cab8c63f8f68028da3aa44e73e6beaff4753d\n",
            "  Stored in directory: /root/.cache/pip/wheels/66/54/9d/10bfd00931c0c993f373269d350635df520b5064e5290a9d94\n",
            "Successfully built TA-Lib\n",
            "Installing collected packages: TA-Lib\n",
            "Successfully installed TA-Lib-0.4.28\n",
            "/content\n"
          ]
        }
      ],
      "source": [
        "# Load the relevant libraries\n",
        "!pip install kafka-python\n",
        "!pip install yfinance --upgrade --no-cache-dir\n",
        "!pip install pyspark\n",
        "!wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz\n",
        "!tar -xzvf ta-lib-0.4.0-src.tar.gz\n",
        "%cd ta-lib/\n",
        "!./configure --prefix=/usr\n",
        "!make\n",
        "!make install\n",
        "!pip install TA-Lib\n",
        "%cd /content"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cQnpYGVYtKWH",
        "outputId": "710f22f6-03bb-4277-bd89-9f8288382d5e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/yfinance/base.py:48: FutureWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.\n",
            "  _empty_series = pd.Series()\n"
          ]
        }
      ],
      "source": [
        "# Import all the relvant libraries and modules\n",
        "import time\n",
        "from kafka import KafkaProducer\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import yfinance as yf\n",
        "from pyspark.sql import SparkSession\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn.cluster import KMeans\n",
        "from sklearn.cluster import AgglomerativeClustering\n",
        "from sklearn.cluster import SpectralClustering\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import talib\n",
        "import json"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "FK2DlPaG9PMn"
      },
      "outputs": [],
      "source": [
        "# Download and extract the Kafka distribution archive using curl and tar respectively\n",
        "!curl -sSOL https://archive.apache.org/dist/kafka/3.3.1/kafka_2.13-3.3.1.tgz\n",
        "!tar -xzf kafka_2.13-3.3.1.tgz"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xNH5t2PM9R3v",
        "outputId": "b2e73f82-5347-409f-908c-a9a88f72c1ca"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Waiting for 10 secs until kafka and zookeeper services are up and running\n"
          ]
        }
      ],
      "source": [
        "# Start Apache Zookeeper and Apache Kafka, and then waiting for 10 seconds to ensure that the services have enough time to initialize before moving on to other tasks\n",
        "!./kafka_2.13-3.3.1/bin/zookeeper-server-start.sh -daemon ./kafka_2.13-3.3.1/config/zookeeper.properties\n",
        "!./kafka_2.13-3.3.1/bin/kafka-server-start.sh -daemon ./kafka_2.13-3.3.1/config/server.properties\n",
        "!echo \"Waiting for 10 secs until kafka and zookeeper services are up and running\"\n",
        "!sleep 10"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mFkip1aHNyRn",
        "outputId": "eedbac8a-05ac-4f1d-d129-d174eab29122"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Created topic BigDataProject.\n"
          ]
        }
      ],
      "source": [
        "# Create a Kafka topic which will be used later with Kafka producer to store the processed data\n",
        "!./kafka_2.13-3.3.1/bin/kafka-topics.sh --create --bootstrap-server 127.0.0.1:9092 --replication-factor 1 --partitions 1 --topic BigDataProject"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-strxaMhaiV8"
      },
      "source": [
        "**Data Crawling**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YnjAof07tb0Q",
        "outputId": "093bd1c5-8fcc-48d1-9bbf-99092ec3256b"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Extracting data of all the 157 US comapanies operating in the energy sector from Yahoo! Finance.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[*********************100%%**********************]  157 of 157 completed\n",
            "ERROR:yfinance:\n",
            "2 Failed downloads:\n",
            "ERROR:yfinance:['SLDPW', 'ARKOW']: Exception(\"%ticker%: Period 'max' is invalid, must be one of ['1d', '5d']\")\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Data has been successfully retrieved.\n"
          ]
        }
      ],
      "source": [
        "# Create a list of stock symbols of all the 157 US companies in the energy sector\n",
        "tickers = [\"AMR\", \"ARCH\", \"AREC\", \"ARLP\", \"BTU\", \"CEIX\", \"HCC\", \"HNRG\", \"METC\", \"METCB\", \"METCL\", \"NC\", \"NRP\", \"MGEE\", \"LFUS\", \"POWL\",\n",
        "\"SLDP\", \"SLDPW\", \"BE\", \"EAF\", \"FCEL\", \"PLUG\", \"THR\", \"WWD\", \"BPT\", \"CLMT\", \"COP\", \"CVI\", \"CVX\", \"DK\", \"HES\", \"MPC\",\n",
        "\"PARR\", \"PBF\", \"PSX\", \"SUN\", \"VLO\", \"VTNR\", \"XOM\", \"DINO\", \"DKL\", \"MPLX\", \"NS\", \"NSS\", \"PAA\", \"PAGP\", \"AMPY\", \"APA\",\n",
        "\"AR\", \"AROC\", \"BATL\", \"BRN\", \"BRY\", \"BSM\", \"CEI\", \"CHK\", \"CHKEL\", \"CHKEW\", \"CHRD\", \"CIVI\", \"CKX\", \"CNX\", \"CPE\",\n",
        "\"CRC\", \"CRGY\", \"CRK\", \"CRT\", \"CTRA\", \"DMLP\", \"DO\", \"DVN\", \"DWSN\", \"EGY\", \"EOG\", \"EP\", \"EPM\", \"EPSN\", \"EQT\", \"FANG\",\n",
        "\"GBR\", \"GPOR\", \"HESM\", \"HP\", \"HPK\", \"HPKEW\", \"HUSA\",  \"KRP\", \"MARPS\", \"MGY\", \"MRO\", \"MTDR\", \"MTR\", \"MUR\", \"MVO\", \"MXC\",\n",
        "\"NFG\", \"NOG\", \"NRT\", \"OXY\", \"PBT\", \"PED\", \"PHX\", \"PNRG\", \"PR\", \"PRT\", \"PTEN\", \"PVL\", \"PXD\", \"REI\", \"REPX\",\n",
        "\"ROI\", \"RRC\", \"SBOW\", \"SBR\", \"SD\", \"SJT\", \"SM\", \"STR\", \"SWN\", \"TALO\", \"TELL\", \"TELZ\", \"TPL\", \"TTI\", \"USEG\",\n",
        "\"VAL\", \"VNOM\", \"VOC\", \"VTLE\", \"VTS\", \"WTI\", \"ACDC\", \"CCLP\", \"ENSV\", \"HAL\", \"HLX\", \"KLXE\", \"LBRT\", \"NCSM\", \"NGS\", \"NINE\",\n",
        "\"OII\", \"PUMP\",\"RES\", \"RNGR\", \"TUSK\", \"VIVK\", \"WTTR\", \"XPRO\", \"AE\", \"ARKO\", \"ARKOW\", \"CAPL\", \"GEL\", \"GLP\", \"MMLP\", \"WKC\"]\n",
        "\n",
        "start_date = \"2023-01-01\"\n",
        "end_date = \"2023-12-31\"\n",
        "\n",
        "print(\"Extracting data of all the 157 US comapanies operating in the energy sector from Yahoo! Finance.\\n\")\n",
        "data = yf.download(tickers, start = start_date, end = end_date, interval = '1mo')\n",
        "print(\"\\nData has been successfully retrieved.\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wGSodtMHa70A"
      },
      "source": [
        "**Data Review**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fmsuc4ojvR97",
        "outputId": "4ba77e87-9705-4b63-eaf0-319b88a555ac"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Type of the dataset: <class 'pandas.core.frame.DataFrame'>\n",
            "\n",
            "\n",
            "The data types of the feature in dataframe:\n",
            " Price      Ticker\n",
            "Adj Close  ACDC      float64\n",
            "           AE        float64\n",
            "           AMPY      float64\n",
            "           AMR       float64\n",
            "           APA       float64\n",
            "                      ...   \n",
            "Volume     WTI         int64\n",
            "           WTTR        int64\n",
            "           WWD         int64\n",
            "           XOM         int64\n",
            "           XPRO        int64\n",
            "Length: 942, dtype: object\n",
            "\n",
            "\n",
            "Shape of the dataframe: (12, 942)\n",
            "\n",
            "\n",
            "Columns in the dataframe: MultiIndex([('Adj Close',  'ACDC'),\n",
            "            ('Adj Close',    'AE'),\n",
            "            ('Adj Close',  'AMPY'),\n",
            "            ('Adj Close',   'AMR'),\n",
            "            ('Adj Close',   'APA'),\n",
            "            ('Adj Close',    'AR'),\n",
            "            ('Adj Close',  'ARCH'),\n",
            "            ('Adj Close',  'AREC'),\n",
            "            ('Adj Close',  'ARKO'),\n",
            "            ('Adj Close', 'ARKOW'),\n",
            "            ...\n",
            "            (   'Volume',   'VOC'),\n",
            "            (   'Volume',  'VTLE'),\n",
            "            (   'Volume',  'VTNR'),\n",
            "            (   'Volume',   'VTS'),\n",
            "            (   'Volume',   'WKC'),\n",
            "            (   'Volume',   'WTI'),\n",
            "            (   'Volume',  'WTTR'),\n",
            "            (   'Volume',   'WWD'),\n",
            "            (   'Volume',   'XOM'),\n",
            "            (   'Volume',  'XPRO')],\n",
            "           names=['Price', 'Ticker'], length=942)\n",
            "\n",
            "\n",
            "\n",
            "Head of the dataframe:\n",
            " Price       Adj Close                                                     \\\n",
            "Ticker           ACDC         AE  AMPY         AMR        APA         AR   \n",
            "Date                                                                       \n",
            "2023-01-01  22.500000  46.759800  8.66  159.314117  42.908794  28.840000   \n",
            "2023-02-01  19.129999  56.686512  8.38  166.055756  37.356354  26.200001   \n",
            "2023-03-01  12.670000  37.427319  6.87  154.433624  35.098228  23.090000   \n",
            "2023-04-01  11.200000  37.274456  6.91  145.487930  35.867157  22.990000   \n",
            "2023-05-01  11.220000  33.957909  6.80  133.982712  31.133032  20.410000   \n",
            "\n",
            "Price                                         ...   Volume            \\\n",
            "Ticker            ARCH  AREC      ARKO ARKOW  ...      VOC      VTLE   \n",
            "Date                                          ...                      \n",
            "2023-01-01  136.583099  1.55  8.261903   NaN  ...  6972300  13363200   \n",
            "2023-02-01  145.192215  1.63  7.897552   NaN  ...  3909000  12239200   \n",
            "2023-03-01  123.866356  1.50  8.360374   NaN  ...  2386400  17525200   \n",
            "2023-04-01  115.188347  1.11  8.261145   NaN  ...  1909900  12592000   \n",
            "2023-05-01   97.380089  1.42  7.164270   NaN  ...  1684900  12786000   \n",
            "\n",
            "Price                                                                    \\\n",
            "Ticker          VTNR         VTS       WKC       WTI      WTTR      WWD   \n",
            "Date                                                                      \n",
            "2023-01-01  41236300         NaN   6160300  50564600  11470300  7399000   \n",
            "2023-02-01  54612600   8083800.0   8505900  53372200  15635800  6540100   \n",
            "2023-03-01  82750600  11522800.0  11665300  79931900  24548300  8405300   \n",
            "2023-04-01  41140100   5501800.0   7008400  45891200  16395300  5359100   \n",
            "2023-05-01  47899900   8525100.0   9536800  52858500  20407900  8934900   \n",
            "\n",
            "Price                            \n",
            "Ticker            XOM      XPRO  \n",
            "Date                             \n",
            "2023-01-01  329848000  16427400  \n",
            "2023-02-01  311238300  15241300  \n",
            "2023-03-01  412537000  19044500  \n",
            "2023-04-01  293288800   9893300  \n",
            "2023-05-01  332357300  11495200  \n",
            "\n",
            "[5 rows x 942 columns]\n",
            "\n",
            "Tail of the dataframe:\n",
            " Price      Adj Close                                                     \\\n",
            "Ticker          ACDC         AE  AMPY         AMR        APA         AR   \n",
            "Date                                                                      \n",
            "2023-08-01     11.00  35.948986  6.54  202.028732  43.231709  27.670000   \n",
            "2023-09-01     10.88  33.181408  7.35  258.691193  40.529728  25.379999   \n",
            "2023-10-01      9.42  31.567184  6.95  219.560410  39.168877  29.440001   \n",
            "2023-11-01      8.06  27.770000  6.14  280.050293  35.706650  23.629999   \n",
            "2023-12-01      8.48  26.180000  5.93  338.920013  35.587627  22.680000   \n",
            "\n",
            "Price                                         ...   Volume            \\\n",
            "Ticker            ARCH  AREC      ARKO ARKOW  ...      VOC      VTLE   \n",
            "Date                                          ...                      \n",
            "2023-08-01  125.855087  1.32  7.471921   NaN  ...  1092800  12814400   \n",
            "2023-09-01  169.483536  1.67  7.120777   NaN  ...  1315000  18109100   \n",
            "2023-10-01  149.790237  1.46  7.519142   NaN  ...  1447500  13856000   \n",
            "2023-11-01  164.815933  1.67  7.449428   NaN  ...  1056600  15980000   \n",
            "2023-12-01  165.940002  1.49  8.250000   NaN  ...  1707500  20520700   \n",
            "\n",
            "Price                                                                    \\\n",
            "Ticker          VTNR        VTS       WKC       WTI      WTTR       WWD   \n",
            "Date                                                                      \n",
            "2023-08-01  53583700  5961700.0  13117800  42709300  21967800  10070300   \n",
            "2023-09-01  40535100  5571900.0  13656900  43676100  16063800   6426700   \n",
            "2023-10-01  30864400  4977800.0  13989000  55576700  11586500   6248700   \n",
            "2023-11-01  51568000  4584000.0   9767000  58534500  17099500   7885000   \n",
            "2023-12-01  68779400  5764700.0  13618200  60485100  15988800   7333400   \n",
            "\n",
            "Price                            \n",
            "Ticker            XOM      XPRO  \n",
            "Date                             \n",
            "2023-08-01  315896100  16440000  \n",
            "2023-09-01  320550000  26635300  \n",
            "2023-10-01  493930700  20632600  \n",
            "2023-11-01  433367400  19256400  \n",
            "2023-12-01  453909500  15642900  \n",
            "\n",
            "[5 rows x 942 columns]\n"
          ]
        }
      ],
      "source": [
        "# Review the dataset by showcasing the initial and final rows, data types, and dimensions\n",
        "print(\"Type of the dataset:\", type(data))\n",
        "print(\"\\n\")\n",
        "print(\"The data types of the feature in dataframe:\\n\", data.dtypes)\n",
        "print(\"\\n\")\n",
        "print(\"Shape of the dataframe:\", data.shape)\n",
        "print(\"\\n\")\n",
        "print(\"Columns in the dataframe:\", data.columns)\n",
        "print(\"\\n\")\n",
        "print(\"\\nHead of the dataframe:\\n\",data.head())\n",
        "print(\"\\nTail of the dataframe:\\n\",data.tail())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cMhyoCuubCpU"
      },
      "source": [
        "**Data Pre-processing**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "j4HUQrrXuUZG",
        "outputId": "4de5f40b-99a0-4114-f1f2-acf42ca15a33"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Type of the dataset: <class 'pandas.core.frame.DataFrame'>\n",
            "Shape of the dataframe: (1853, 5)\n",
            "Columns in the dataframe: Index(['Date', 'Stock', 'Adj Close', 'High', 'Low'], dtype='object')\n",
            "\n",
            "Head of the dataframe:\n",
            "         Date Stock   Adj Close        High         Low\n",
            "0 2023-01-01  ACDC   22.500000   25.440001   19.832001\n",
            "1 2023-01-01    AE   46.759800   51.500000   37.500000\n",
            "2 2023-01-01  AMPY    8.660000    9.360000    7.700000\n",
            "3 2023-01-01   AMR  159.314117  174.554993  130.539993\n",
            "4 2023-01-01   APA   42.908794   46.980000   41.360001\n",
            "\n",
            "Tail of the dataframe:\n",
            "            Date Stock   Adj Close        High         Low\n",
            "1848 2023-12-01   WTI    3.260000    3.440000    2.860000\n",
            "1849 2023-12-01  WTTR    7.590000    7.818000    7.065000\n",
            "1850 2023-12-01   WWD  136.130005  140.729996  132.440002\n",
            "1851 2023-12-01   XOM   99.980003  104.220001   97.480003\n",
            "1852 2023-12-01  XPRO   15.920000   17.000000   14.440000\n"
          ]
        }
      ],
      "source": [
        "# Flatten the dataframe from MultiIndex as the features for all the stocks symbols are homogenous.\n",
        "data1 = data.stack(level=1).reset_index()\n",
        "\n",
        "data1.columns = [\"Date\", \"Stock\", \"Adj Close\", \"Close\", \"High\", \"Low\", \"Open\", \"Volume\"]\n",
        "# Drop less relevant features from the dataframe\n",
        "data1.drop([\"Open\", \"Close\", \"Volume\"], axis = 1, inplace = True)\n",
        "\n",
        "# Review the flattened dataframe by showcasing the initial and final rows, data types, and dimensions\n",
        "print(\"Type of the dataset:\", type(data1))\n",
        "print(\"Shape of the dataframe:\", data1.shape)\n",
        "print(\"Columns in the dataframe:\", data1.columns)\n",
        "print(\"\\nHead of the dataframe:\\n\", data1.head())\n",
        "print(\"\\nTail of the dataframe:\\n\", data1.tail())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AXNf_ixT3oBe",
        "outputId": "79d2ae8f-4d9f-4ee4-e430-d27b28714fc5"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Are there any dupliacates in the dataframe? False\n",
            "Count of missing values in the dataframe:\n",
            " Date         0\n",
            "Stock        0\n",
            "Adj Close    0\n",
            "High         0\n",
            "Low          0\n",
            "dtype: int64\n"
          ]
        }
      ],
      "source": [
        "# Check for duplicate and missing values in the dataframe\n",
        "print(\"Are there any dupliacates in the dataframe?\", data1.duplicated().any())\n",
        "print(\"Count of missing values in the dataframe:\\n\", data1.isna().sum())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XymlM3yjbfMC"
      },
      "source": [
        "**Descriptive Statistics**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uM5hruBc_obB",
        "outputId": "a6ddf3fd-5607-4116-9c1d-c98d86a9f39e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Descriptive statistics of 'Adj Close' for 10 random stocks:\n",
            "        count        mean        std         min         25%         50%  \\\n",
            "Stock                                                                     \n",
            "BATL    12.0    7.149167   1.734738    5.030000    5.947500    6.375000   \n",
            "CTRA    12.0   25.379454   1.671601   22.732538   23.898141   25.275118   \n",
            "EQT     12.0   37.650856   4.309003   31.531101   33.925738   39.235739   \n",
            "GLP     12.0   32.150117   4.072017   27.100784   29.359169   31.299057   \n",
            "GPOR    12.0  103.314999  23.866740   66.120003   87.844999  103.759998   \n",
            "HAL     12.0   35.802979   3.920998   28.263308   32.485541   36.428856   \n",
            "HCC     12.0   43.017597   9.122018   32.605793   36.666106   39.127926   \n",
            "HES     12.0  141.716834   9.040413  125.542862  134.321373  143.743988   \n",
            "HESM    12.0   28.637933   1.967842   25.345642   27.536236   28.536904   \n",
            "HLX     12.0    8.764167   1.489908    6.280000    7.650000    8.800000   \n",
            "\n",
            "              75%         max  \n",
            "Stock                          \n",
            "BATL     8.537500   10.320000  \n",
            "CTRA    26.923340   27.780390  \n",
            "EQT     41.091897   42.906124  \n",
            "GLP     33.598701   42.310001  \n",
            "GPOR   119.897503  137.039993  \n",
            "HAL     38.855322   40.488663  \n",
            "HCC     49.248023   60.970001  \n",
            "HES    148.968647  153.617950  \n",
            "HESM    29.597550   31.869677  \n",
            "HLX      9.885000   11.170000  \n"
          ]
        }
      ],
      "source": [
        "# Display descriptive statistics of 10 random stocks\n",
        "stock_names = [\"BATL\", \"CTRA\", \"EQT\", \"GLP\", \"GPOR\", \"HAL\", \"HCC\", \"HES\", \"HESM\", \"HLX\"]\n",
        "data_des = data1.groupby('Stock')[\"Adj Close\"].describe()\n",
        "print(\"Descriptive statistics of 'Adj Close' for 10 random stocks:\\n\", data_des[data_des.index.isin(stock_names)])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qfJmdhS3S31y"
      },
      "source": [
        "**Visualization for Data Distribution**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 657
        },
        "id": "i224z3RkTD7R",
        "outputId": "06760c0d-f1a1-4468-c1f7-94c6471c2305"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x800 with 10 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "fig, axes = plt.subplots(2, 5, figsize = (10, 8))\n",
        "\n",
        "for ax, stock_name in zip(axes.flat, stock_names):\n",
        "  sns.histplot(data = data1[data1[\"Stock\"] == stock_name], x = \"Adj Close\", kde = True, ax = ax, label = stock_name, color = \"grey\")\n",
        "  ax.set_xticklabels(\"\")\n",
        "  ax.set_yticklabels(\"\")\n",
        "  ax.set_xlabel(\"\")\n",
        "  ax.set_ylabel(\"\")\n",
        "  ax.legend()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tWXzSByUbxnR"
      },
      "source": [
        "**Top 10 and bottom 10 stocks based on the mean of the adjusted closing price**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WeZfV-DoV0FM",
        "outputId": "b5a187a6-e686-4478-f0c4-1df2bfe0f569"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Top 10 stocks based on the mean of the adjusted closing price:\n",
            " Stock\n",
            "TPL     1649.163116\n",
            "LFUS     257.661724\n",
            "PXD      213.949964\n",
            "AMR      199.517476\n",
            "CVX      155.440557\n",
            "CHRD     146.821609\n",
            "HES      141.716834\n",
            "FANG     141.164201\n",
            "ARCH     135.544310\n",
            "MPC      132.315926\n",
            "Name: Adj Close, dtype: float64 \n",
            "\n",
            "TPL seems like an outlier.\n",
            "\n",
            "Bottom 10 stocks based on the mean of the adjusted closing price:\n",
            " Stock\n",
            "DWSN    1.817500\n",
            "AREC    1.558333\n",
            "USEG    1.522408\n",
            "CCLP    1.312837\n",
            "TELL    1.234167\n",
            "GBR     1.113333\n",
            "VIVK    1.080283\n",
            "PED     0.930250\n",
            "CEI     0.890833\n",
            "ENSV    0.460833\n",
            "Name: Adj Close, dtype: float64 \n",
            "\n"
          ]
        }
      ],
      "source": [
        "# Display information of top 10 stocks based on the mean of the adjusted closing price\n",
        "data_ds = data1.groupby(\"Stock\")[\"Adj Close\"].mean().sort_values(ascending = False)\n",
        "print(\"Top 10 stocks based on the mean of the adjusted closing price:\\n\", data_ds.head(10), \"\\n\")\n",
        "print(\"TPL seems like an outlier.\\n\")\n",
        "print(\"Bottom 10 stocks based on the mean of the adjusted closing price:\\n\", data_ds.tail(10), \"\\n\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2_GTlt42cBUV"
      },
      "source": [
        "**Time-Series Visualizations for Top and Bottom 10 Stocks**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 872
        },
        "id": "ttmGDHsmXFQT",
        "outputId": "2b06bbd3-2027-401f-e07d-bde3e8114f38"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1400x1000 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Display time-series visualizations for top 10 and bottom 10 stocks over the months based on adj closing prices\n",
        "top_stocks = list(data_ds.head(10).index)\n",
        "bottom_stocks = list(data_ds.tail(10).index)\n",
        "\n",
        "## Create a month feature based on the dates in the data\n",
        "data1[\"Month\"] = data1[\"Date\"].dt.month\n",
        "\n",
        "## Group the data based on Stock\n",
        "data_ds = data1.groupby(\"Stock\")\n",
        "\n",
        "fig, ax = plt.subplots(2, 1, figsize = (14, 10))\n",
        "for stock in top_stocks:\n",
        "    ### Extract stock name from the list of top stock\n",
        "    stock_data = data_ds.get_group(stock)\n",
        "    ax[0].plot(stock_data[\"Month\"], stock_data[\"Adj Close\"], label=f'{stock}', marker='o')\n",
        "    #ax[0].title(\"Monthly Adjusted Closing Prices of Top 10 Stocks\")\n",
        "ax[0].set_title(\"Monthly Adjusted Closing Prices of Top 10 Stocks\")\n",
        "for stock in bottom_stocks:\n",
        "    ### Extract stock name from the list of bottom stocks and pick values from the Adj Close column\n",
        "    stock_data = data_ds.get_group(stock)\n",
        "    ax[1].plot(stock_data[\"Month\"], stock_data[\"Adj Close\"], label=f'{stock}', marker='o')\n",
        "    #ax[1].title(\"Monthly Adjusted Closing Prices of Bottom 10 Stocks\")\n",
        "ax[1].set_title(\"Monthly Adjusted Closing Prices of Bottom 10 Stocks\")\n",
        "ax[0].set_ylabel('Average Adj Close')\n",
        "ax[1].set_ylabel('Average Adj Close')\n",
        "ax[0].legend()\n",
        "ax[1].legend()\n",
        "ax[0].set_xlabel('Month')\n",
        "ax[1].set_xlabel('Month')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1DF4BcVQcUK2"
      },
      "source": [
        "**Feature Engineering**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "N0SC3_HXnHsz",
        "outputId": "f0213ff6-c9ec-4157-df45-407b956fef94"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           Date Stock  Adj Close       High        Low  Month        SMA  \\\n",
              "0    2023-01-01  ACDC  22.500000  25.440001  19.832001      1        NaN   \n",
              "1    2023-02-01  ACDC  19.129999  22.530001  18.559999      2        NaN   \n",
              "2    2023-03-01  ACDC  12.670000  21.780001  10.150000      3  18.100000   \n",
              "3    2023-04-01  ACDC  11.200000  13.960000  10.550000      4  14.333333   \n",
              "4    2023-05-01  ACDC  11.220000  12.505000   9.010000      5  11.696667   \n",
              "...         ...   ...        ...        ...        ...    ...        ...   \n",
              "1848 2023-08-01  XPRO  23.510000  24.500000  21.450001      8  21.140000   \n",
              "1849 2023-09-01  XPRO  23.230000  25.040001  22.320000      9  22.976667   \n",
              "1850 2023-10-01  XPRO  15.750000  23.290001  15.250000     10  20.830000   \n",
              "1851 2023-11-01  XPRO  15.550000  16.389999  14.330000     11  18.176667   \n",
              "1852 2023-12-01  XPRO  15.920000  17.000000  14.440000     12  15.740000   \n",
              "\n",
              "            EMA        RSI   Returns  Volatility       ATR  \n",
              "0           NaN        NaN       NaN         NaN       NaN  \n",
              "1           NaN        NaN -0.149778         NaN       NaN  \n",
              "2     18.100000        NaN -0.337689    4.078635       NaN  \n",
              "3     14.650000   0.000000 -0.116022    3.444438  6.336667  \n",
              "4     12.935000   0.264790  0.001786    0.688299  5.389445  \n",
              "...         ...        ...       ...         ...       ...  \n",
              "1848  21.800729  76.103334  0.059486    2.477620  4.321769  \n",
              "1849  22.515364  72.168860 -0.011910    0.567881  3.787846  \n",
              "1850  19.132682  23.495129 -0.321997    3.593921  5.205231  \n",
              "1851  17.341341  22.876329 -0.012698    3.574179  4.156821  \n",
              "1852  16.630671  28.129105  0.023794    0.151217  3.624547  \n",
              "\n",
              "[1853 rows x 12 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-0401d2ed-e0fe-44be-82ce-d043c131ca9e\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Stock</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Month</th>\n",
              "      <th>SMA</th>\n",
              "      <th>EMA</th>\n",
              "      <th>RSI</th>\n",
              "      <th>Returns</th>\n",
              "      <th>Volatility</th>\n",
              "      <th>ATR</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2023-01-01</td>\n",
              "      <td>ACDC</td>\n",
              "      <td>22.500000</td>\n",
              "      <td>25.440001</td>\n",
              "      <td>19.832001</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2023-02-01</td>\n",
              "      <td>ACDC</td>\n",
              "      <td>19.129999</td>\n",
              "      <td>22.530001</td>\n",
              "      <td>18.559999</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>-0.149778</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2023-03-01</td>\n",
              "      <td>ACDC</td>\n",
              "      <td>12.670000</td>\n",
              "      <td>21.780001</td>\n",
              "      <td>10.150000</td>\n",
              "      <td>3</td>\n",
              "      <td>18.100000</td>\n",
              "      <td>18.100000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>-0.337689</td>\n",
              "      <td>4.078635</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2023-04-01</td>\n",
              "      <td>ACDC</td>\n",
              "      <td>11.200000</td>\n",
              "      <td>13.960000</td>\n",
              "      <td>10.550000</td>\n",
              "      <td>4</td>\n",
              "      <td>14.333333</td>\n",
              "      <td>14.650000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.116022</td>\n",
              "      <td>3.444438</td>\n",
              "      <td>6.336667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2023-05-01</td>\n",
              "      <td>ACDC</td>\n",
              "      <td>11.220000</td>\n",
              "      <td>12.505000</td>\n",
              "      <td>9.010000</td>\n",
              "      <td>5</td>\n",
              "      <td>11.696667</td>\n",
              "      <td>12.935000</td>\n",
              "      <td>0.264790</td>\n",
              "      <td>0.001786</td>\n",
              "      <td>0.688299</td>\n",
              "      <td>5.389445</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1848</th>\n",
              "      <td>2023-08-01</td>\n",
              "      <td>XPRO</td>\n",
              "      <td>23.510000</td>\n",
              "      <td>24.500000</td>\n",
              "      <td>21.450001</td>\n",
              "      <td>8</td>\n",
              "      <td>21.140000</td>\n",
              "      <td>21.800729</td>\n",
              "      <td>76.103334</td>\n",
              "      <td>0.059486</td>\n",
              "      <td>2.477620</td>\n",
              "      <td>4.321769</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1849</th>\n",
              "      <td>2023-09-01</td>\n",
              "      <td>XPRO</td>\n",
              "      <td>23.230000</td>\n",
              "      <td>25.040001</td>\n",
              "      <td>22.320000</td>\n",
              "      <td>9</td>\n",
              "      <td>22.976667</td>\n",
              "      <td>22.515364</td>\n",
              "      <td>72.168860</td>\n",
              "      <td>-0.011910</td>\n",
              "      <td>0.567881</td>\n",
              "      <td>3.787846</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1850</th>\n",
              "      <td>2023-10-01</td>\n",
              "      <td>XPRO</td>\n",
              "      <td>15.750000</td>\n",
              "      <td>23.290001</td>\n",
              "      <td>15.250000</td>\n",
              "      <td>10</td>\n",
              "      <td>20.830000</td>\n",
              "      <td>19.132682</td>\n",
              "      <td>23.495129</td>\n",
              "      <td>-0.321997</td>\n",
              "      <td>3.593921</td>\n",
              "      <td>5.205231</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1851</th>\n",
              "      <td>2023-11-01</td>\n",
              "      <td>XPRO</td>\n",
              "      <td>15.550000</td>\n",
              "      <td>16.389999</td>\n",
              "      <td>14.330000</td>\n",
              "      <td>11</td>\n",
              "      <td>18.176667</td>\n",
              "      <td>17.341341</td>\n",
              "      <td>22.876329</td>\n",
              "      <td>-0.012698</td>\n",
              "      <td>3.574179</td>\n",
              "      <td>4.156821</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1852</th>\n",
              "      <td>2023-12-01</td>\n",
              "      <td>XPRO</td>\n",
              "      <td>15.920000</td>\n",
              "      <td>17.000000</td>\n",
              "      <td>14.440000</td>\n",
              "      <td>12</td>\n",
              "      <td>15.740000</td>\n",
              "      <td>16.630671</td>\n",
              "      <td>28.129105</td>\n",
              "      <td>0.023794</td>\n",
              "      <td>0.151217</td>\n",
              "      <td>3.624547</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1853 rows × 12 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0401d2ed-e0fe-44be-82ce-d043c131ca9e')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-0401d2ed-e0fe-44be-82ce-d043c131ca9e button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-0401d2ed-e0fe-44be-82ce-d043c131ca9e');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-6faa8a37-e60d-4e32-89be-fb6b74997ed2\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-6faa8a37-e60d-4e32-89be-fb6b74997ed2')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-6faa8a37-e60d-4e32-89be-fb6b74997ed2 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ],
      "source": [
        "'''Apply technical analysis to feature engineer Simple Moving Average, Exponential Moving Average, Relative Strength Index, Returns, Volatility, and Average True Range of the stocks\n",
        "with a time period of 3 months ensuring quaterly division of stocks data.'''\n",
        "data_TA = data1.groupby(\"Stock\")\n",
        "result_df = []\n",
        "\n",
        "for stock, stock_data in data_TA:\n",
        "    stock_data = stock_data.sort_values(by = \"Month\")\n",
        "\n",
        "    ### Calculate simple moving average that gives equal weight to all data points\n",
        "    stock_data[\"SMA\"] = talib.SMA(stock_data[\"Adj Close\"], timeperiod = 3)\n",
        "\n",
        "    ### Calculate exponential moving average that gives more weight to recent data points\n",
        "    stock_data[\"EMA\"] = talib.EMA(stock_data[\"Adj Close\"], timeperiod = 3)\n",
        "\n",
        "    ### Calculate relative strength index (RSI) to identify if a stock is overbought or oversold\n",
        "    stock_data['RSI'] = talib.RSI(stock_data[\"Adj Close\"], timeperiod = 3)\n",
        "\n",
        "    ### Calculate daily returns that tells % change in the worth of the stock\n",
        "    stock_data[\"Returns\"] = stock_data[\"Adj Close\"].pct_change()\n",
        "\n",
        "    ### Calculate volatility of the stocks that describes the fluctuation in price of the stock using standard deviation\n",
        "    stock_data[\"Volatility\"] =talib.STDDEV(stock_data[\"Adj Close\"], timeperiod = 3)\n",
        "\n",
        "    ### Calculate volatility of the stocks that describes the fluctuation in price of the stock using Average True Range\n",
        "    stock_data[\"ATR\"] = talib.ATR(stock_data[\"High\"], stock_data[\"Low\"], stock_data[\"Adj Close\"], timeperiod=3)\n",
        "\n",
        "    ### Storing the results in a list to be used later when performing RDD filter operations and clustering\n",
        "    result_df.append(stock_data)\n",
        "    #print(f\"\\nStock: {stock}\")\n",
        "    #print(stock_data.tail())\n",
        "## Conver the list to pandas dataframe\n",
        "result_df = pd.concat(result_df, ignore_index=True)\n",
        "result_df"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LNImRiDBcmC8"
      },
      "source": [
        "**Data Pre-processing post Feature Engineering**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9u-sMjrsoZze",
        "outputId": "947bc91a-f7c4-4ef6-b7e6-cb0b0592fc48"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Count of missing values in the dataframe:\n",
            " Date            0\n",
            "Stock           0\n",
            "Adj Close       0\n",
            "High            0\n",
            "Low             0\n",
            "Month           0\n",
            "SMA           310\n",
            "EMA           310\n",
            "RSI           465\n",
            "Returns       155\n",
            "Volatility    310\n",
            "ATR           465\n",
            "dtype: int64\n",
            "\n",
            "Count of missing values in the dataframe:\n",
            " Date          0\n",
            "Stock         0\n",
            "Adj Close     0\n",
            "High          0\n",
            "Low           0\n",
            "Month         0\n",
            "SMA           0\n",
            "EMA           0\n",
            "RSI           0\n",
            "Returns       0\n",
            "Volatility    0\n",
            "ATR           0\n",
            "dtype: int64\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-15-d9b9ad5cecb2>:4: FutureWarning: DataFrame.mean and DataFrame.median with numeric_only=None will include datetime64 and datetime64tz columns in a future version.\n",
            "  result_df.fillna(result_df.mean(), inplace=True)\n",
            "<ipython-input-15-d9b9ad5cecb2>:4: FutureWarning: The default value of numeric_only in DataFrame.mean is deprecated. In a future version, it will default to False. In addition, specifying 'numeric_only=None' is deprecated. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
            "  result_df.fillna(result_df.mean(), inplace=True)\n"
          ]
        }
      ],
      "source": [
        "# Check for missing values in the dataframe as new features have been added\n",
        "print(\"Count of missing values in the dataframe:\\n\", result_df.isna().sum())\n",
        "#Impute missing values in SMA, EMA, RSI, Returns and Volatility\n",
        "result_df.fillna(result_df.mean(), inplace=True)\n",
        "print(\"\\nCount of missing values in the dataframe:\\n\", result_df.isna().sum())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UIW01RW6Hksh",
        "outputId": "bff446ea-6ebe-45d2-d9ff-eb6f5e8aeb30"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Initiating a PySpark session\n",
            "\n",
            "Converting the data frame into RDD.\n",
            "\n",
            "******************************************\n",
            "RDD has been successfully created.\n",
            "\n"
          ]
        }
      ],
      "source": [
        "# Create a PySpark session and convert the DataFrame into an RDD to enable distributed processing and ensure fault tolerance in case of node failures\n",
        "spark = SparkSession.builder.appName(\"Raza_Final_Project_Big_Data_A\").getOrCreate()\n",
        "result_df_spark = spark.createDataFrame(result_df)\n",
        "result_df_RDD = result_df_spark.rdd\n",
        "print(\"Initiating a PySpark session\\n\")\n",
        "time.sleep(0.5)\n",
        "print(\"Converting the data frame into RDD.\\n\")\n",
        "for i in range(0, 101, 5):\n",
        "  print(\"**\", end = \"\")\n",
        "  time.sleep(0.1)\n",
        "print(\"\\nRDD has been successfully created.\\n\")\n",
        "\n",
        "def get_unique_symbols(rdd):\n",
        "    return set(row[1] for row in rdd.collect())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PiVWhehGcstX"
      },
      "source": [
        "**Stock Evaluation**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9wYOmkIyLBWh",
        "outputId": "8fd152a1-3295-40e9-df2f-a92f9935ad03"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The strong stocks based on the comparison of adjusted closing price with SMA: {'AMR', 'MVO', 'CLMT', 'WWD', 'SBR', 'AROC', 'THR', 'NSS', 'METCL'}\n",
            "\n",
            "The strong stocks based on the comparison of adjusted closing price with EMA: {'NSS', 'METCL'}\n",
            "\n",
            "The weak stocks based on the comparison of adjusted closing price with SMA: {'MGY', 'XOM', 'PR', 'CHRD', 'PARR', 'SD', 'TALO', 'MRO', 'CRC', 'OXY', 'MARPS', 'SBOW', 'EQT', 'EGY', 'FANG', 'HLX', 'CPE', 'CTRA', 'BRN', 'NINE', 'PBF', 'FCEL', 'METC', 'KRP', 'PTEN', 'DO', 'CRK', 'MXC', 'MGEE', 'DMLP', 'DK', 'DKL', 'PLUG', 'MPLX', 'SM', 'PAA', 'PUMP', 'ROI', 'GPOR', 'HCC', 'VTNR', 'BRY', 'DVN', 'PED', 'SLDP', 'ENSV', 'MTR', 'EPM', 'RRC', 'EOG', 'VIVK', 'CHKEW', 'PBT', 'PNRG', 'HUSA', 'ARKO', 'VNOM', 'XPRO', 'HES', 'WTTR', 'CRT', 'MMLP', 'NRP', 'BE', 'CEIX', 'PSX', 'ARLP', 'MUR', 'CHK', 'CRGY', 'NS', 'DINO', 'VLO', 'WKC', 'GEL', 'USEG', 'HPKEW', 'AE', 'EP', 'CIVI', 'HP', 'HNRG', 'KLXE', 'CKX', 'BATL', 'SUN', 'RES', 'GLP', 'TTI', 'LFUS', 'WTI', 'TUSK', 'TELL', 'AMPY', 'APA', 'GBR', 'SJT', 'HAL', 'PRT', 'PXD', 'PVL', 'ARCH', 'NCSM', 'NGS', 'REI', 'NFG', 'EPSN', 'VTLE', 'BTU', 'BSM', 'CVI', 'RNGR', 'MTDR', 'POWL', 'CEI', 'BPT', 'NC', 'PHX', 'CVX', 'TPL', 'EAF', 'COP', 'NOG', 'METCB', 'TELZ', 'HESM', 'OII', 'DWSN', 'NRT', 'VTS', 'VAL', 'AR', 'ACDC', 'PAGP', 'REPX', 'SWN', 'CAPL', 'MPC', 'VOC', 'HPK', 'LBRT', 'CCLP', 'CNX', 'STR', 'CHKEL', 'AREC'}\n",
            "\n",
            "The weak stocks based on the comparison of adjusted closing price with EMA: {'MGY', 'XOM', 'PR', 'CHRD', 'PARR', 'SD', 'TALO', 'MRO', 'CRC', 'OXY', 'MARPS', 'SBOW', 'EQT', 'EGY', 'FANG', 'HLX', 'CPE', 'CTRA', 'BRN', 'NINE', 'PBF', 'FCEL', 'METC', 'KRP', 'PTEN', 'DO', 'CRK', 'MXC', 'MGEE', 'DMLP', 'DK', 'DKL', 'PLUG', 'MPLX', 'SM', 'PAA', 'PUMP', 'ROI', 'GPOR', 'HCC', 'VTNR', 'BRY', 'DVN', 'PED', 'SLDP', 'ENSV', 'AMR', 'MTR', 'EPM', 'RRC', 'EOG', 'VIVK', 'CLMT', 'CHKEW', 'PBT', 'PNRG', 'HUSA', 'ARKO', 'VNOM', 'SBR', 'XPRO', 'HES', 'WTTR', 'WWD', 'CRT', 'THR', 'MMLP', 'NRP', 'BE', 'CEIX', 'PSX', 'ARLP', 'MUR', 'CHK', 'CRGY', 'NS', 'DINO', 'VLO', 'WKC', 'GEL', 'USEG', 'HPKEW', 'AE', 'EP', 'CIVI', 'HP', 'HNRG', 'KLXE', 'CKX', 'BATL', 'SUN', 'AROC', 'RES', 'GLP', 'TTI', 'LFUS', 'WTI', 'TUSK', 'TELL', 'AMPY', 'APA', 'GBR', 'SJT', 'HAL', 'PRT', 'PXD', 'PVL', 'ARCH', 'NCSM', 'NGS', 'REI', 'NFG', 'EPSN', 'VTLE', 'BTU', 'BSM', 'CVI', 'RNGR', 'MTDR', 'MVO', 'POWL', 'CEI', 'BPT', 'NC', 'PHX', 'CVX', 'TPL', 'EAF', 'COP', 'NOG', 'METCB', 'TELZ', 'HESM', 'OII', 'DWSN', 'NRT', 'VTS', 'VAL', 'AR', 'ACDC', 'PAGP', 'REPX', 'SWN', 'CAPL', 'MPC', 'VOC', 'HPK', 'LBRT', 'CCLP', 'CNX', 'STR', 'CHKEL', 'AREC'}\n",
            "\n",
            "The overbought stock(s) based on RSI: {'NS', 'POWL', 'CHRD', 'GPOR', 'HCC', 'EP', 'PARR', 'NC', 'AMR', 'CKX', 'BATL', 'SUN', 'AROC', 'GLP', 'VNOM', 'ARKO', 'HESM', 'WWD', 'CAPL', 'MPC', 'METC', 'THR', 'NRP', 'METCL', 'ARCH', 'DMLP', 'NGS', 'PSX', 'MPLX'}\n",
            "\n",
            "The oversold stock(s) based on RSI: {'ROI', 'XOM', 'USEG', 'HPKEW', 'AE', 'VTNR', 'CEI', 'CIVI', 'SD', 'PED', 'DVN', 'SLDP', 'BPT', 'ENSV', 'TPL', 'HNRG', 'MRO', 'EPM', 'SBOW', 'EAF', 'MARPS', 'CHKEW', 'PBT', 'HUSA', 'CPE', 'WTI', 'XPRO', 'NRT', 'BRN', 'ACDC', 'NINE', 'VOC', 'AMPY', 'PTEN', 'APA', 'GBR', 'SJT', 'CRK', 'PRT', 'MXC', 'PVL', 'REI', 'CHKEL', 'NFG', 'PLUG', 'CHK', 'PUMP'}\n"
          ]
        }
      ],
      "source": [
        "# Extract overbought and oversold stocks based on RSI and underpriced stocks based on SMA, EMA and RSI in December\n",
        "overbought_stocks_rdd = result_df_RDD.filter(lambda x: x[8] > 70 and x[5] == 12)\n",
        "oversold_stocks_rsi_rdd = result_df_RDD.filter(lambda x: x[8] <30 and x[5] == 12)\n",
        "\n",
        "bullish_stocks_sma_rdd = result_df_RDD.filter(lambda x: x[4] > x[6] and x[5] == 12)\n",
        "bullish_stocks_ema_rdd = result_df_RDD.filter(lambda x: x[4] > x[7] and x[5] == 12)\n",
        "\n",
        "bearish_stocks_sma_rdd = result_df_RDD.filter(lambda x: x[4] < x[6] and x[5] == 12)\n",
        "bearish_stocks_ema_rdd = result_df_RDD.filter(lambda x: x[4] < x[7] and x[5] == 12)\n",
        "\n",
        "bullish_stocks_sma_symbols = get_unique_symbols(bullish_stocks_sma_rdd)\n",
        "bullish_stocks_ema_symbols = get_unique_symbols(bullish_stocks_ema_rdd)\n",
        "bearish_stocks_sma_symbols = get_unique_symbols(bearish_stocks_sma_rdd)\n",
        "bearish_stocks_ema_symbols = get_unique_symbols(bearish_stocks_ema_rdd)\n",
        "overbought_symbols = get_unique_symbols(overbought_stocks_rdd)\n",
        "oversold_rsi_symbols = get_unique_symbols(oversold_stocks_rsi_rdd)\n",
        "\n",
        "print(\"The strong stocks based on the comparison of adjusted closing price with SMA:\", bullish_stocks_sma_symbols)\n",
        "print(\"\\nThe strong stocks based on the comparison of adjusted closing price with EMA:\", bullish_stocks_ema_symbols)\n",
        "print(\"\\nThe weak stocks based on the comparison of adjusted closing price with SMA:\", bearish_stocks_sma_symbols)\n",
        "print(\"\\nThe weak stocks based on the comparison of adjusted closing price with EMA:\", bearish_stocks_ema_symbols)\n",
        "print(\"\\nThe overbought stock(s) based on RSI:\", overbought_symbols)\n",
        "print(\"\\nThe oversold stock(s) based on RSI:\", oversold_rsi_symbols)\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2bq6TGijc0Fo"
      },
      "source": [
        "**Stock Return Overview**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "76SC--VueCsV",
        "outputId": "d249d33e-5fd0-4d73-f795-bfb7e44d5544"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The stocks that gave returns equal or more than 50% are: {'BATL'}\n",
            "\n",
            "The stocks that incurred losses are: {'MGY', 'XOM', 'SD', 'MRO', 'SBOW', 'MARPS', 'EQT', 'EGY', 'CTRA', 'BRN', 'PBF', 'PTEN', 'CRK', 'MXC', 'MGEE', 'DK', 'DKL', 'PAA', 'PUMP', 'GPOR', 'PED', 'ENSV', 'MTR', 'EPM', 'RRC', 'EOG', 'CHKEW', 'PBT', 'PNRG', 'CRT', 'MMLP', 'CEIX', 'CHK', 'GEL', 'USEG', 'HPKEW', 'AE', 'CIVI', 'HNRG', 'TTI', 'WTI', 'AMPY', 'APA', 'GBR', 'SJT', 'HAL', 'PRT', 'PXD', 'PVL', 'REI', 'NFG', 'EPSN', 'BSM', 'MTDR', 'CEI', 'BPT', 'PHX', 'TPL', 'EAF', 'NOG', 'METCB', 'HESM', 'VTS', 'NRT', 'VAL', 'AR', 'PAGP', 'SWN', 'VOC', 'CAPL', 'MPC', 'NSS', 'HPK', 'LBRT', 'CCLP', 'CNX', 'CHKEL', 'AREC'}\n"
          ]
        }
      ],
      "source": [
        "# Extract lists of stocks that provided returns equal to or greater than 50%, and those that resulted in losses in December\n",
        "profitable_stocks_RDD = result_df_RDD.filter(lambda x: x[9] >= 0.5 and x[5] == 12)\n",
        "unprofitable_stocks_RDD = result_df_RDD.filter(lambda x: x[9] < 0.00 and x[5] == 12)\n",
        "\n",
        "profitable_symbols = get_unique_symbols(profitable_stocks_RDD)\n",
        "unprofitable_symbols = get_unique_symbols(unprofitable_stocks_RDD)\n",
        "\n",
        "print(\"The stocks that gave returns equal or more than 50% are:\", profitable_symbols)\n",
        "print(\"\\nThe stocks that incurred losses are:\", unprofitable_symbols)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Qk5XmT9KoJCa"
      },
      "source": [
        "**Risk Analysis**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1yEEZ35SoRbA",
        "outputId": "3c461fa6-01cd-48ec-8bfe-427265b7a30c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "The most volatile stocks using STDEV: {'TPL'}\n",
            "\n",
            "The most volatile stocks using ATR: {'TPL'}\n"
          ]
        }
      ],
      "source": [
        "# Extract lists of stocks that exhibited extreme volatility in December\n",
        "max_volatility_STDEV = result_df_RDD.map(lambda x: x[10]).max()\n",
        "volatile_stocks_STDEV = result_df_RDD.filter(lambda x: x[10] == max_volatility_STDEV)\n",
        "\n",
        "max_volatility_ATR = result_df_RDD.map(lambda x: x[11]).max()\n",
        "volatile_stocks_ATR = result_df_RDD.filter(lambda x: x[11] == max_volatility_ATR)\n",
        "\n",
        "volatile_symbols_STDEV = get_unique_symbols(volatile_stocks_STDEV)\n",
        "volatile_symbols_ATR = get_unique_symbols(volatile_stocks_ATR)\n",
        "\n",
        "print(\"\\nThe most volatile stocks using STDEV:\", volatile_symbols_STDEV)\n",
        "print(\"\\nThe most volatile stocks using ATR:\", volatile_symbols_ATR)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ijusJfJMc4rG"
      },
      "source": [
        "**Data Standardization**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "xy0m_8VqX6wK",
        "outputId": "d4647aae-4249-4465-f314-84155ecde293"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       Adj Close       SMA       EMA       RSI   Returns  Volatility\n",
              "Stock                                                               \n",
              "ACDC   -0.241079 -0.245574 -0.243824 -1.997836 -1.852592   -0.138549\n",
              "AE     -0.066065 -0.067794 -0.067503 -1.145148 -0.977910    0.018002\n",
              "AMPY   -0.280122 -0.281784 -0.281718 -1.278367 -0.666824   -0.234483\n",
              "AMR     1.129943  1.085926  1.101032  1.130275  2.229752    1.769453\n",
              "APA    -0.057225 -0.056981 -0.056697 -0.497918 -0.206327   -0.041050\n",
              "...          ...       ...       ...       ...       ...         ...\n",
              "WTI    -0.299766 -0.301736 -0.301750 -1.543455 -1.245247   -0.240465\n",
              "WTTR   -0.275956 -0.277512 -0.277308 -0.433891 -0.094560   -0.243800\n",
              "WWD     0.513184  0.517929  0.518616  1.605842  0.856535    0.178219\n",
              "XOM     0.451817  0.462158  0.459519 -0.107625 -0.094226    0.156364\n",
              "XPRO   -0.191174 -0.189561 -0.190521  0.102207  0.083816   -0.076827\n",
              "\n",
              "[155 rows x 6 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-537f8a3b-84a6-4827-b075-25461c5f1bb8\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>SMA</th>\n",
              "      <th>EMA</th>\n",
              "      <th>RSI</th>\n",
              "      <th>Returns</th>\n",
              "      <th>Volatility</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Stock</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>ACDC</th>\n",
              "      <td>-0.241079</td>\n",
              "      <td>-0.245574</td>\n",
              "      <td>-0.243824</td>\n",
              "      <td>-1.997836</td>\n",
              "      <td>-1.852592</td>\n",
              "      <td>-0.138549</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AE</th>\n",
              "      <td>-0.066065</td>\n",
              "      <td>-0.067794</td>\n",
              "      <td>-0.067503</td>\n",
              "      <td>-1.145148</td>\n",
              "      <td>-0.977910</td>\n",
              "      <td>0.018002</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AMPY</th>\n",
              "      <td>-0.280122</td>\n",
              "      <td>-0.281784</td>\n",
              "      <td>-0.281718</td>\n",
              "      <td>-1.278367</td>\n",
              "      <td>-0.666824</td>\n",
              "      <td>-0.234483</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AMR</th>\n",
              "      <td>1.129943</td>\n",
              "      <td>1.085926</td>\n",
              "      <td>1.101032</td>\n",
              "      <td>1.130275</td>\n",
              "      <td>2.229752</td>\n",
              "      <td>1.769453</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>APA</th>\n",
              "      <td>-0.057225</td>\n",
              "      <td>-0.056981</td>\n",
              "      <td>-0.056697</td>\n",
              "      <td>-0.497918</td>\n",
              "      <td>-0.206327</td>\n",
              "      <td>-0.041050</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>WTI</th>\n",
              "      <td>-0.299766</td>\n",
              "      <td>-0.301736</td>\n",
              "      <td>-0.301750</td>\n",
              "      <td>-1.543455</td>\n",
              "      <td>-1.245247</td>\n",
              "      <td>-0.240465</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>WTTR</th>\n",
              "      <td>-0.275956</td>\n",
              "      <td>-0.277512</td>\n",
              "      <td>-0.277308</td>\n",
              "      <td>-0.433891</td>\n",
              "      <td>-0.094560</td>\n",
              "      <td>-0.243800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>WWD</th>\n",
              "      <td>0.513184</td>\n",
              "      <td>0.517929</td>\n",
              "      <td>0.518616</td>\n",
              "      <td>1.605842</td>\n",
              "      <td>0.856535</td>\n",
              "      <td>0.178219</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>XOM</th>\n",
              "      <td>0.451817</td>\n",
              "      <td>0.462158</td>\n",
              "      <td>0.459519</td>\n",
              "      <td>-0.107625</td>\n",
              "      <td>-0.094226</td>\n",
              "      <td>0.156364</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>XPRO</th>\n",
              "      <td>-0.191174</td>\n",
              "      <td>-0.189561</td>\n",
              "      <td>-0.190521</td>\n",
              "      <td>0.102207</td>\n",
              "      <td>0.083816</td>\n",
              "      <td>-0.076827</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>155 rows × 6 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-537f8a3b-84a6-4827-b075-25461c5f1bb8')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-537f8a3b-84a6-4827-b075-25461c5f1bb8 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-537f8a3b-84a6-4827-b075-25461c5f1bb8');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-ada11b39-7d62-4cdb-9995-856eb12ea465\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-ada11b39-7d62-4cdb-9995-856eb12ea465')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-ada11b39-7d62-4cdb-9995-856eb12ea465 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ],
      "source": [
        "# Standardize the dataframe to make the values comparable as there are major differences in the means and standard deviations of the stocks\n",
        "standardized_df = result_df.groupby(\"Stock\").agg({\"Adj Close\": \"mean\", \"SMA\": \"mean\", \"EMA\": \"mean\", \"RSI\": \"mean\", \"Returns\": \"mean\", \"Volatility\": \"mean\"})\n",
        "scale = StandardScaler()\n",
        "standardized_df[[\"Adj Close\", \"SMA\", \"EMA\", \"RSI\", \"Returns\", \"Volatility\"]] = scale.fit_transform(standardized_df[[\"Adj Close\", \"SMA\", \"EMA\", \"RSI\", \"Returns\", \"Volatility\"]])\n",
        "standardized_df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "id": "mUGi7A3EIGb1"
      },
      "outputs": [],
      "source": [
        "def visualize_clusters(cluster_label, ax):\n",
        "\n",
        "    #   Create a scatter plot based on the clustering algorithm.\n",
        "\n",
        "    ##  Parameters:\n",
        "    ### - cluster_label (str): The type of clustering algorithm used (\"Cluster_KMeans\", \"Cluster_HC\", \"Cluster_SC\"). This parameter will also be used to extract clustering values\n",
        "    ### from the data and assign colors to the data points.\n",
        "    ### - ax (AxesSubplot): Matplotlib subplot axes.\n",
        "\n",
        "    ##  Returns:\n",
        "    ### None\n",
        "\n",
        "  if cluster_label == \"Cluster_KMeans\": title = \"KMeans Clustering\"\n",
        "  elif cluster_label == \"Cluster_HC\": title = \"Hierarchical Clustering\"\n",
        "  elif cluster_label == \"Cluster_SC\": title = \"Spectral Clustering\"\n",
        "\n",
        "  sns.scatterplot(x = \"Returns\", y = \"Volatility\", s = 500, alpha = 0.9, ax = ax, hue= cluster_label, data = standardized_df, palette = \"Set1\")\n",
        "  ax.set_title(title)\n",
        "  ax.set_xlabel(\"Returns\")\n",
        "  ax.set_ylabel(\"Volatility\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rkjYv_MVc8PR"
      },
      "source": [
        "**Elbow Curve**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 839
        },
        "id": "3BFSefGuRaGE",
        "outputId": "0ac8ca8d-1387-4dcc-dade-b5e16b9f38a8"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Display an elbow curve to find the optimal value of number of clusters before applying any clustering algorigthm\n",
        "n_clusters = range(1, 11)\n",
        "wcss_values = []\n",
        "features_for_model = standardized_df[[\"Returns\", \"Volatility\"]]\n",
        "for k in n_clusters:\n",
        "\n",
        "  kmeans = KMeans(n_clusters = k, random_state = 1)\n",
        "  kmeans.fit(features_for_model)\n",
        "  wcss_values.append(kmeans.inertia_)\n",
        "\n",
        "plt.plot(n_clusters, wcss_values, marker = 'o')\n",
        "plt.xlabel(\"k\")\n",
        "plt.ylabel(\"Cost Function\")\n",
        "plt.axvline(4, 0, color=\"maroon\", linestyle=\"--\", label=\"Optimal numbers of clusters = 4\")\n",
        "plt.grid(True)\n",
        "plt.title(\"Elbow Curve to find the optimal value of number of clusters\")\n",
        "plt.legend()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jjB2aQY6dBNk"
      },
      "source": [
        "**Data Clustering using K-Means**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cwYAXG6haeLy",
        "outputId": "24dee805-aac8-4f80-8b25-272bc09ef568"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cluster Counts:\n",
            "0    78\n",
            "3    57\n",
            "2    19\n",
            "1     1\n",
            "Name: Cluster_KMeans, dtype: int64\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n"
          ]
        }
      ],
      "source": [
        "# Applying Kmeans clustering based on the optimal value of k = 4\n",
        "kmeans = KMeans(n_clusters = 4, random_state = 1)\n",
        "standardized_df[\"Cluster_KMeans\"] = kmeans.fit_predict(features_for_model)\n",
        "print(\"Cluster Counts:\")\n",
        "print(standardized_df['Cluster_KMeans'].value_counts())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rz2p62T0bxsY"
      },
      "source": [
        "**Data Clustering using Hierarchical Clustering**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aJuREoU-f-Qh",
        "outputId": "aa3501fe-95e9-4aed-a706-e55af5040024"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cluster Counts:\n",
            "2    71\n",
            "1    60\n",
            "0    23\n",
            "3     1\n",
            "Name: Cluster_HC, dtype: int64\n"
          ]
        }
      ],
      "source": [
        "# Applying Hierarchical Clustering\n",
        "np.random.seed(1)\n",
        "#Fitting the model using linkage ward which is an approach to measuring the distance between clusters by minimizing the sum of squares differences\n",
        "model = AgglomerativeClustering(n_clusters = 4, linkage = \"ward\")\n",
        "standardized_df[\"Cluster_HC\"] = model.fit_predict(features_for_model)\n",
        "print(\"Cluster Counts:\")\n",
        "print(standardized_df['Cluster_HC'].value_counts())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VCMMLOe1DE-n"
      },
      "source": [
        "**Data Clustering using Spectral Clustering**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mxwBcd-tF-bT",
        "outputId": "9294a7de-6f48-4926-fccc-f529f83d9a4a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cluster Counts:\n",
            "0    58\n",
            "1    47\n",
            "2    27\n",
            "3    23\n",
            "Name: Cluster_SC, dtype: int64\n"
          ]
        }
      ],
      "source": [
        "spectral = SpectralClustering(n_clusters=4, affinity='nearest_neighbors', random_state=0)\n",
        "standardized_df[\"Cluster_SC\"] = spectral.fit_predict(features_for_model)\n",
        "print(\"Cluster Counts:\")\n",
        "print(standardized_df['Cluster_SC'].value_counts())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uwhewsViGavw"
      },
      "source": [
        "**Clusters Visualization**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 475
        },
        "id": "HZnHWO5bGexQ",
        "outputId": "aa7e433a-0b21-465a-f553-b09865711f17"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x500 with 3 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Visualize the clusters by generating a scatter plot\n",
        "fig, ax = plt.subplots(1, 3, figsize = (16, 5))\n",
        "\n",
        "visualize_clusters(\"Cluster_KMeans\", ax[0])\n",
        "visualize_clusters(\"Cluster_HC\", ax[1])\n",
        "visualize_clusters(\"Cluster_SC\", ax[2])\n",
        "\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "adhXsgJjNIs_"
      },
      "source": [
        "**Interpretation of KMeans Clustering**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QKlzcrMPm3Ht"
      },
      "source": [
        "\n",
        "\n",
        "*   Cluster 0 (red): Stocks in this cluster are unprofitable and likely to continue losing money in the future.\n",
        "*   Cluster 1 (blue): Represents stocks with high profits and lower volatility, considered stable and reliable.\n",
        "*   Cluster 2 (green): An outlier containing highly volatile stocks, such as TPL, with potential for medium to higher returns.\n",
        "*   Cluster 3 (purple): Includes stocks with medium profits and lower volatility, offering a middle ground between riskier and more stable stocks.\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TTwqwT_ONLYd"
      },
      "source": [
        "**Interpretation of Hierarchical Clustering**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Lkg02NoyNORn"
      },
      "source": [
        "\n",
        "\n",
        "*   Cluster 1 (blue): Stocks are unprofitable and may continue to incur losses.\n",
        "*   Cluster 0 (red): Comprises stocks with high profits and lower volatility, indicating stability.\n",
        "*   Cluster 2 (green): Includes stocks with medium profits and lower volatility, providing a balanced option.\n",
        "*   Cluster 3 (purple): An outlier with TPL, a highly volatile stock offering medium to higher returns."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tocBWZiiOOxb"
      },
      "source": [
        "**Interpretation of Spectral Clustering**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GL4L5SB7OYzY"
      },
      "source": [
        "*   Cluster 0 (red): Stocks generate medium to somewhat higher profits with lower volatility.\n",
        "*   Cluster 1 (blue): Represents stocks with no clear correlation, suggesting a volatile nature.\n",
        "*   Cluster 2 (green): Comprises unprofitable stocks that have been losing money.\n",
        "*   Cluster 3 (purple): Stocks with less volatility and high returns, indicating strong correlation among them."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ol791O6-Uk5h"
      },
      "source": [
        "**Summary**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zYsXJtHlUnZc"
      },
      "source": [
        "While each algorithm provides unique insights, there is a common theme across clusters suggesting that many energy sector stocks offer a balance of medium to high returns with relatively low volatility. This stability makes them potentially attractive to investors seeking a manageable level of risk in their portfolios."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_T6ZNrVbbdKZ"
      },
      "source": [
        "**Sending data to Kafka**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IAk7UM2xZcHS",
        "outputId": "94e3bcf2-7983-487b-8b8f-8511f841db82"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Starting to load data onto Kafka.\n",
            "\n",
            "*******************************\n",
            "Processed data has been assigned to Kafka topic 'project_data' to be subscribed by other systems.\n"
          ]
        }
      ],
      "source": [
        "# Initialize Kafka producer to store processed financial stocks data\n",
        "producer = KafkaProducer(bootstrap_servers='127.0.0.1:9092', value_serializer=lambda v: json.dumps(v).encode('utf-8'))\n",
        "\n",
        "data_dict_list = standardized_df.reset_index().to_dict(orient='records')\n",
        "\n",
        "n = 0\n",
        "print(\"Starting to load data onto Kafka.\\n\")\n",
        "for data_dict in data_dict_list:\n",
        "    producer.send('project-data', value=data_dict)\n",
        "    n += 1\n",
        "    if n % 5 == 0:\n",
        "      print(\"*\", end = \"\")\n",
        "    time.sleep(0.1)\n",
        "\n",
        "producer.close()\n",
        "print(\"\\nProcessed data has been assigned to Kafka topic 'project_data' to be subscribed by other systems.\")"
      ]
    }
  ],
  "metadata": {
    "accelerator": "TPU",
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}