From 7cf646101ddada802a053882ea05bd7b8019f8cf Mon Sep 17 00:00:00 2001 From: Axel Gard Date: Fri, 14 Jun 2024 17:11:53 +0200 Subject: [PATCH] refreshed the readme a little bit, still needs some work but is more clean now ! --- README.md | 106 ++++++++++++----------------------- examples/dev.ipynb | 136 ++++++++------------------------------------- 2 files changed, 57 insertions(+), 185 deletions(-) diff --git a/README.md b/README.md index d9b089e..3cec292 100644 --- a/README.md +++ b/README.md @@ -19,14 +19,6 @@ The name **cira** is a miss spelling of the word for a [baby alpaca cria](https: [Axel Gard](https://github.com/AxelGard) is main developer for cira. -## News - -**cira v3.0.0 is now out!!** - -If you want to know more about v3 check, the details are [here](./docs/news/v3_realse.md). - -If you find an issue with the new relase, open an [issue](https://github.com/AxelGard/cira/issues/new/choose). - ## Getting Started If you are new to cira checkout the [tutorial](https://github.com/AxelGard/cira/wiki/Tutorial). @@ -51,21 +43,23 @@ cira.auth.APCA_API_KEY_ID = "my key" cira.auth.APCA_API_SECRET_KEY = "my secret key" stock = cira.Stock("TSLA") -stock.buy(1) -stock.sell(1) +stock.buy(1) # buy 1 TSLA stock on alpaca +stock.sell(1) # sell 1 TSLA stock on alpaca ``` -New classes with cira v.2! +For interactons with alpaca you can: ```python portfolio = cira.Portfolio() # methods for your portfolio exchange = cira.Exchange() # methods for exchange stock = cira.Stock("TSLA") # a class for one stock +crypto = cira.Cryptocurrency("BTC/USD") # method for one cryptocurrency ``` ### DEMO, no keys needed Crypto market data can be accessed [without any alpaca keys](https://alpaca.markets/sdks/python/market_data.html#api-keys). So there for you can try cira out with out needing to get alpaca keys. +To put you model in production where you buy and sell you will need alpaca keys. Needs `cira>=3.2.2`. @@ -83,7 +77,7 @@ print(f"The current asking price for {SYMBOL} is {ast.price()}") # alpaca only have BTC data from 2021 and forward -data = ast.historical_data_df(datetime(2021, 6, 1), datetime(2024, 6, 1)) +data = ast.historical_data_df(datetime(2021, 1, 1), datetime.now().date()) print(data.head()) # All of strategies and backtesting works with out keys as well. @@ -92,45 +86,11 @@ cira.strategy.back_test_against_buy_and_hold(strat, data, data["open"].to_frame( plt.savefig('./result.png') ``` - -### Sci-kit learn + cira - -> only for v3 - -I have made a simple example on how to use cira together with Sci-kit learn, using linear regression. -This model is just a toy example. - -**Checkout it out [./examples/linear.ipynb](./examples/linear.ipynb)** - -### A simple algorithm - -In just a couple of lines you are up and running, with a super simple algorithm. - -```python -import cira -import random -import time - -cira.alpaca.KEY_FILE = "../mypath/key.json" - -portfolio = cira.Portfolio() -exchange = cira.Exchange() - -qty = 1 # choose how many stocks should be handled in one session -while True: - while exchange.is_open: - for stock in random.choices(exchange.get_all_stocks(), k=qty): - stock.buy(1) - for stock in random.choices(portfolio.owned_stocks(), k=qty): - stock.sell(1) - time.sleep(60*30) # 30 min timer -``` - -you can find more examples on the **[wiki/examples](https://github.com/AxelGard/cira/wiki/Examples)** and the **[wiki/tutorial](https://github.com/AxelGard/cira/wiki/Tutorial)** for even more information. +you can find more examples on the **[examples repo](https://github.com/AxelGard/cira-examples)** and the **[wiki/tutorial](https://github.com/AxelGard/cira/wiki/Tutorial)** for even more information. ### Cira Stratergies -Cira have also now (v3) support for strategies. +Cira have also support for strategies. An **full example** of how to use the strategy is [example/linear](../../examples/linear.ipynb). With strategies you can run a cira backtests. @@ -148,33 +108,36 @@ class MyStrat(Strategy): # this mehod will be called for each row of data in the backtest # the function should return the change of your portfolio. # -1 means sell one stock, 0 means hold, 1 means buy one stock - return np.array([ portfolio_change_as_int ]) + return np.array([ portfolio_change_as_int_or_float ]) ``` #### Backtest If your model is put into a strategy you can run a backtest on you own data. -This is a minimal setup for a backtest using the Randomness strategy included in cira. -You should of course use your own strategy, but as an example. +This is a backtest using some of the included strategy in cira. +You can run a backtest aginst multiple strategies using the same data, this requires however that all features for all models are in the given data to the backtest. +You should of course add your own strategy, but as an example. ```python import cira -from cira.strategy import Randomness -from cira.strategy import back_test from datetime import datetime -import pandas as pd +import matplotlib.pyplot as plt -cira.auth.KEY_FILE = "../../alpc_key.json" -assert cira.auth.check_keys(), "the set keys dose not work" +assert not cira.auth.check_keys() # back testing against crypto do not need keys -stock = cira.Stock("AAPL") -df = stock.historical_data_df(datetime(2022, 1, 1), datetime(2024, 1, 1)) -prices = pd.DataFrame() -prices["AAPL"] = df["close"] +SYMBOL = "ETH/USD" +ast = cira.Cryptocurrency(SYMBOL) + +data = ast.historical_data_df(datetime(2021, 1, 1), datetime.now().date()) -strat = Randomness(-10,10, seed=23323) -bt = back_test(strat, df.copy(), prices.copy(), 10_000, use_fees=True) -bt.plot() +strats = [ + cira.strategy.ByAndHold(), + cira.strategy.DollarCostAveraging(0.8), + cira.strategy.Randomness(-100, 100, seed=None, use_float=True), + # add your own strategy and compare your model against other models + ] +cira.strategy.multi_strategy_backtest(strats, data, data["open"].to_frame(), 100_000).plot() +plt.savefig("./result.png") ``` If you want more full example of how to use the backtest checkout @@ -189,20 +152,18 @@ If you want more full example of how to use the backtest checkout * [Wiki](https://github.com/AxelGard/cira/wiki/) * [Tutorial](https://github.com/AxelGard/cira/wiki/Tutorial) * [Storing the Alpaca API key](https://github.com/AxelGard/cira/wiki/Storing-the-Alpaca-API-key) -* [Examples of how to use cira](https://github.com/AxelGard/cira/wiki/Examples) +* [Examples of how to use cira](https://github.com/AxelGard/cira-examples) * [Discussions](https://github.com/AxelGard/cira/discussions) -## [Wiki](https://github.com/AxelGard/cira/wiki) and docs +### [Wiki](https://github.com/AxelGard/cira/wiki) and docs To see what more you can do check out the [wiki](https://github.com/AxelGard/cira/wiki). -I also have an example of how to build a [index fund trader with cira](https://github.com/AxelGard/cira/wiki/Examples#simple-index-fund). - ### Want the old version? For backwards compatibility I made sure to fork cira in to [cira-classic](https://github.com/AxelGard/cira-classic) and cira-classic is also available on [pypi with pip](https://pypi.org/project/cira-classic/). -if you find bug plz let me know with a issue. If you know how to solve the problem then you can of course make a pull request and I will take a look at it. +**If you find bug plz let me know with a issue.** If you know how to solve the problem then you can of course make a pull request and I will take a look at it. ### Have a question? @@ -230,20 +191,23 @@ and know you need to python3 -m venv env source env/bin/activate pip install -e . +pip install -r requirements.txt ``` Run tests using pytest. Ensure that you are in the cira dir. But you will need a new key. This key should not only be used for testing or if you don't mind if all of the assets in the portfolio being sold. ```bash -touch tests/test_key.json -pytest +pytest -rP ``` ### Coding style I'm trying to follow the [pep8](https://pep8.org/) standard notation. I try to make the library to be so intuitive as possible for easy of use. +I enforce [black formater](https://github.com/psf/black) when you commit code, by [pre-commit githooks](https://git-scm.com/docs/githooks#_pre_commit) to keep it some what well formated. + ## License -This project is licensed under the MIT License - see the [LICENSE](LICENSE.txt) file for details + +This project is licensed under the MIT License - see the [LICENSE](LICENSE.txt) file for details. ## Acknowledgments diff --git a/examples/dev.ipynb b/examples/dev.ipynb index 4bddc63..856351a 100644 --- a/examples/dev.ipynb +++ b/examples/dev.ipynb @@ -12,15 +12,6 @@ "assert cira.auth.check_keys(), \"the set keys dose not work\"" ] }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "exch = cira.Exchange()" - ] - }, { "cell_type": "code", "execution_count": 3, @@ -28,118 +19,35 @@ "outputs": [ { "data": { + "image/png": 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", "text/plain": [ - "False" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "exch.is_open()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[]" + "
" ] }, - "execution_count": 4, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ - "exch.symbols_options()" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(True, False, False)" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ast = cira.Cryptocurrency(\"BTC/USD\")\n", - "ast.is_tradable(), ast.is_sortable(), ast.can_borrow()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[(BTCUSD, 0), (MSFT, 14), (PYPL, 3), (TSLA, 1)]" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "cira.Portfolio().all_positions()" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'asset_id': UUID('b6d1aa75-5c9c-4353-a305-9e2caa1925ab'),\n", - " 'symbol': 'MSFT',\n", - " 'exchange': ,\n", - " 'asset_class': ,\n", - " 'asset_marginable': True,\n", - " 'avg_entry_price': 328.152857143,\n", - " 'qty': 14,\n", - " 'side': ,\n", - " 'market_value': 5821.9,\n", - " 'cost_basis': 4594.14,\n", - " 'unrealized_pl': 1227.76,\n", - " 'unrealized_plpc': 0.2672447944555455,\n", - " 'unrealized_intraday_pl': 16.52,\n", - " 'unrealized_intraday_plpc': 0.0028456362890974,\n", - " 'current_price': 415.85,\n", - " 'lastday_price': 414.67,\n", - " 'change_today': 0.0028456362890974,\n", - " 'swap_rate': None,\n", - " 'avg_entry_swap_rate': None,\n", - " 'usd': None,\n", - " 'qty_available': 14}" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "cira.Stock(\"MSFT\").position()" + "import cira\n", + "from datetime import datetime\n", + "import matplotlib.pyplot as plt\n", + "\n", + "cira.auth.KEY_FILE = \"\"\n", + "assert not cira.auth.check_keys()\n", + "\n", + "SYMBOL = \"ETH/USD\"\n", + "ast = cira.Cryptocurrency(SYMBOL)\n", + "\n", + "data = ast.historical_data_df(datetime(2021, 1, 1), datetime.now().date())\n", + "\n", + "strats = [\n", + " cira.strategy.ByAndHold(),\n", + " cira.strategy.DollarCostAveraging(0.8),\n", + " cira.strategy.Randomness(-100, 100, seed=None, use_float=True),\n", + " ]\n", + "cira.strategy.multi_strategy_backtest(strats, data, data[\"open\"].to_frame(), 100_000).plot()\n", + "plt.savefig(\"./result.png\")" ] }, {