notebook/KnockoffTable.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e7908bb7",
   "metadata": {},
   "source": [
    "# KnockoffTable\n",
    "(`knockoff.sdk.table:KnockoffTable`)\n",
    "\n",
    "This is the primary class for configuring how knockoff populates a table. \n",
    "\n",
    "* [Factories](#Factories)\n",
    "    * [ColumnFactory](#ColumnFactory) (`knockoff.sdk.factory.column:ColumnFactory`)\n",
    "    * [CollectionsFactory](#CollectionsFactory) ('knockoff.sdk.factory.collections:CollectionsFactory')\n",
    "    * [KnockoffDataFrameFactory](#KnockoffDataFrameFactory) (`knockoff.sdk.factory.collections:KnockoffDataFrameFactory`) \n",
    "        * randomly sample input DataFrame rows\n",
    "        * cycling through input DataFrame rows\n",
    "    * [KnockoffTableFactory](#KnockoffTableFactory) (`knockoff.sdk.factory.collections:KnockoffTableFactory`)\n",
    "* [KnockoffUniqueConstraint](#KnockoffUniqueConstraint)\n",
    "* [Autoloading](#Autoloading)\n",
    "\n",
    "\n",
    "### <a name=\"Factories\"></a> Factories\n",
    "\n",
    "A list of `factories` are provided in the __init__ of KnockoffTable that will be used at build time to generate rows (the number of rows generated is declared with the `size` parameter). Calls to the factories are made to generate data for each row.\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d5b23219",
   "metadata": {},
   "source": [
    "#### <a name=\"ColumnFactory\"></a>ColumnFactory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d4fac0fc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call[0]: {'some_column': 0.5000619168058782}\n",
      "call[1]: {'some_column': 0.9885946890702473}\n",
      "call[2]: {'some_column': 0.41250444122739394}\n",
      "call[3]: {'some_column': 0.4462999921807126}\n",
      "call[4]: {'some_column': 0.06017712225706928}\n"
     ]
    }
   ],
   "source": [
    "import random\n",
    "from knockoff.sdk.factory.column import ColumnFactory\n",
    "\n",
    "# create a factory that generates a random value for \"some_column\" using the random.random function\n",
    "factory = ColumnFactory('some_column', random.random)\n",
    "for i in range(5):\n",
    "    print(f\"call[{i}]: {factory()}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14b47406",
   "metadata": {},
   "source": [
    "#### <a name=\"CollectionsFactory\"></a>CollectionsFactory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ea5b346f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call[0]: {'col1': 4, 'col2': 0.5771082134122193}\n",
      "call[1]: {'col1': 10, 'col2': 0.9443929581234238}\n",
      "call[2]: {'col1': 9, 'col2': 0.5833487911234037}\n",
      "call[3]: {'col1': 10, 'col2': 0.16599398285529154}\n",
      "call[4]: {'col1': 5, 'col2': 0.3534517643813895}\n"
     ]
    }
   ],
   "source": [
    "from knockoff.sdk.factory.collections import CollectionsFactory\n",
    "\n",
    "# this can be any callable that returns a dictionary\n",
    "def func():\n",
    "    return {'col1': random.randint(0,10),\n",
    "            'col2': random.random()}\n",
    "\n",
    "factory = CollectionsFactory(func)\n",
    "for i in range(5):\n",
    "    print(f\"call[{i}]: {factory()}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31b25cc2",
   "metadata": {},
   "source": [
    "#### <a name=\"KnockoffDataFrameFactory\"></a>KnockoffDataFrameFactory\n",
    "\n",
    "This class takes a DataFrame as input to use to generate rows. The default behavior is to **randomly sample input DataFrame rows** for each call to the factory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ff1e8934",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>a0</td>\n",
       "      <td>b0</td>\n",
       "      <td>c0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>a1</td>\n",
       "      <td>b1</td>\n",
       "      <td>c1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>a2</td>\n",
       "      <td>b2</td>\n",
       "      <td>c2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>a3</td>\n",
       "      <td>b3</td>\n",
       "      <td>c3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>a4</td>\n",
       "      <td>b4</td>\n",
       "      <td>c4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    a   b   c\n",
       "0  a0  b0  c0\n",
       "1  a1  b1  c1\n",
       "2  a2  b2  c2\n",
       "3  a3  b3  c3\n",
       "4  a4  b4  c4"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call[0]: {'a': 'a1', 'b': 'b1', 'c': 'c1'}\n",
      "call[1]: {'a': 'a2', 'b': 'b2', 'c': 'c2'}\n",
      "call[2]: {'a': 'a2', 'b': 'b2', 'c': 'c2'}\n",
      "call[3]: {'a': 'a1', 'b': 'b1', 'c': 'c1'}\n",
      "call[4]: {'a': 'a2', 'b': 'b2', 'c': 'c2'}\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from knockoff.sdk.factory.collections import KnockoffDataFrameFactory\n",
    "\n",
    "# Create an input DataFrame\n",
    "df = pd.DataFrame({letter: [f\"{letter}{i}\" for i in range(5)] for letter in ['a', 'b' ,'c']})\n",
    "display(df)\n",
    "\n",
    "factory = KnockoffDataFrameFactory(df)\n",
    "for i in range(5):\n",
    "    print(f\"call[{i}]: {factory()}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e028cf8",
   "metadata": {},
   "source": [
    "The `next_strategy_factory` or `next_strategy_callable` parameters can be used to change the behavior of the sampling. E.g. the `cycle_df_factory` can be used to cycle **through input DataFrame rows** instead of randomly sampling."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3a81d0b2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "call[0]: {'a': 'a0', 'b': 'b0', 'c': 'c0'}\n",
      "call[1]: {'a': 'a1', 'b': 'b1', 'c': 'c1'}\n",
      "call[2]: {'a': 'a2', 'b': 'b2', 'c': 'c2'}\n",
      "call[3]: {'a': 'a3', 'b': 'b3', 'c': 'c3'}\n",
      "call[4]: {'a': 'a4', 'b': 'b4', 'c': 'c4'}\n",
      "call[5]: {'a': 'a0', 'b': 'b0', 'c': 'c0'}\n",
      "call[6]: {'a': 'a1', 'b': 'b1', 'c': 'c1'}\n",
      "call[7]: {'a': 'a2', 'b': 'b2', 'c': 'c2'}\n",
      "call[8]: {'a': 'a3', 'b': 'b3', 'c': 'c3'}\n",
      "call[9]: {'a': 'a4', 'b': 'b4', 'c': 'c4'}\n"
     ]
    }
   ],
   "source": [
    "from knockoff.sdk.factory.next_strategy.df import cycle_df_factory\n",
    "factory = KnockoffDataFrameFactory(df, next_strategy_factory=cycle_df_factory)\n",
    "for i in range(10):\n",
    "    print(f\"call[{i}]: {factory()}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6dcd04d1",
   "metadata": {},
   "source": [
    "#### <a name=\"KnockoffTableFactory\"></a>KnockoffTableFactory\n",
    "The KnockoffTableFactory behaves very similar to the KnockoffDataFrameFactory except that it takes another KnockoffTable as input instead of a KnockoffDataFrame. When this factory is used, we must declare this dependency when providing the KnockoffTable to the KnockoffDB.\n",
    "\n",
    "\n",
    "#### <a name=\"KnockoffTable-Example\"></a> KnockoffTable Example\n",
    "\n",
    " `columns` need to be provided to the __init__ to determine which fields will be used as columns (factories can generate unused fields). `columns` do not need to be provided if the `autoload` flag is set to `True` where the columns will be reflected from the database table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d71d8587",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>name</th>\n",
       "      <th>address</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Joshua Taylor</td>\n",
       "      <td>935 Anderson Lane\\nAguilarmouth, NH 83805</td>\n",
       "      <td>male</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Andrew Smith</td>\n",
       "      <td>PSC 3613, Box 7286\\nAPO AP 82138</td>\n",
       "      <td>female</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Melissa Schroeder</td>\n",
       "      <td>23917 Mcdonald Path Apt. 242\\nWest Mark, ID 73045</td>\n",
       "      <td>male</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Michael Anderson</td>\n",
       "      <td>8132 Horton Avenue Suite 634\\nLake Melissaland...</td>\n",
       "      <td>male</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Nancy Johnson</td>\n",
       "      <td>207 Juan Islands Suite 189\\nJaniceside, CT 33016</td>\n",
       "      <td>female</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Amy Rosales</td>\n",
       "      <td>15030 Beard Club Apt. 873\\nPort Matthewbury, O...</td>\n",
       "      <td>male</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Dawn Lynch</td>\n",
       "      <td>201 Chad Valleys Suite 416\\nEast Dawn, WY 39184</td>\n",
       "      <td>female</td>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Jenna Davis</td>\n",
       "      <td>62813 Kimberly Meadows\\nWest Heatherchester, T...</td>\n",
       "      <td>female</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Bobby Diaz</td>\n",
       "      <td>8555 Watkins Brooks Apt. 607\\nSharonmouth, OH ...</td>\n",
       "      <td>male</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Matthew Jones MD</td>\n",
       "      <td>57744 Angelica Ramp\\nBrianashire, WV 41784</td>\n",
       "      <td>female</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                name                                            address  \\\n",
       "0      Joshua Taylor          935 Anderson Lane\\nAguilarmouth, NH 83805   \n",
       "1       Andrew Smith                   PSC 3613, Box 7286\\nAPO AP 82138   \n",
       "2  Melissa Schroeder  23917 Mcdonald Path Apt. 242\\nWest Mark, ID 73045   \n",
       "3   Michael Anderson  8132 Horton Avenue Suite 634\\nLake Melissaland...   \n",
       "4      Nancy Johnson   207 Juan Islands Suite 189\\nJaniceside, CT 33016   \n",
       "5        Amy Rosales  15030 Beard Club Apt. 873\\nPort Matthewbury, O...   \n",
       "6         Dawn Lynch    201 Chad Valleys Suite 416\\nEast Dawn, WY 39184   \n",
       "7        Jenna Davis  62813 Kimberly Meadows\\nWest Heatherchester, T...   \n",
       "8         Bobby Diaz  8555 Watkins Brooks Apt. 607\\nSharonmouth, OH ...   \n",
       "9   Matthew Jones MD         57744 Angelica Ramp\\nBrianashire, WV 41784   \n",
       "\n",
       "   gender  age  \n",
       "0    male   62  \n",
       "1  female   47  \n",
       "2    male    6  \n",
       "3    male   75  \n",
       "4  female   45  \n",
       "5    male   24  \n",
       "6  female   92  \n",
       "7  female   35  \n",
       "8    male   65  \n",
       "9  female   66  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from knockoff.sdk.table import KnockoffTable\n",
    "from knockoff.sdk.factory.column import ColumnFactory, ChoiceFactory, FakerFactory\n",
    "\n",
    "\n",
    "table = KnockoffTable(\n",
    "    \"person\",\n",
    "    columns=[\"name\", \"address\", \"gender\", \"age\"],\n",
    "    factories=[\n",
    "        ColumnFactory(\"name\", FakerFactory(\"name\")),\n",
    "        ColumnFactory(\"address\", FakerFactory(\"address\")),\n",
    "        ColumnFactory(\"gender\", ChoiceFactory([\"male\", \"female\"])),\n",
    "        ColumnFactory(\"age\", FakerFactory(\"pyint\", min_value=0, max_value=100)),\n",
    "    ],\n",
    "    size=10,\n",
    ")\n",
    "\n",
    "display(table.build())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73c5a97a",
   "metadata": {},
   "source": [
    "If multiple factories provide the same column, the KnockoffTable will apply those in the order provided to the `factories` parameter. I.e. factories towards the end of the list will take precendence. ColumnFactory and CollectionsFactory can declare a dependency on another column which will be provided to the factory as a kwarg. The factory must be provided after the factory that generates the column it depends on in order to do so. Please see the below example as a reference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c61ebfd0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>name</th>\n",
       "      <th>address</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>other_address</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Heather Chung</td>\n",
       "      <td>9509 James Rapids</td>\n",
       "      <td>female</td>\n",
       "      <td>74</td>\n",
       "      <td>Rebeccaborough, OR 73595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Stephen Hayes</td>\n",
       "      <td>188 David Run Suite 795</td>\n",
       "      <td>male</td>\n",
       "      <td>49</td>\n",
       "      <td>New Linda, WA 05108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Thomas Huerta</td>\n",
       "      <td>481 Rivera Ford</td>\n",
       "      <td>female</td>\n",
       "      <td>26</td>\n",
       "      <td>Lake Bradview, FL 11180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Samuel Lawson</td>\n",
       "      <td>61652 Amy Road Suite 256</td>\n",
       "      <td>female</td>\n",
       "      <td>39</td>\n",
       "      <td>Markview, WV 39420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Richard Cummings</td>\n",
       "      <td>468 Michael Skyway</td>\n",
       "      <td>male</td>\n",
       "      <td>81</td>\n",
       "      <td>Kaylafort, OR 85551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Stephanie Clark</td>\n",
       "      <td>0885 Reeves Camp Suite 040</td>\n",
       "      <td>male</td>\n",
       "      <td>86</td>\n",
       "      <td>Dianaland, CO 88542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>David Hahn</td>\n",
       "      <td>1123 Hernandez Corner</td>\n",
       "      <td>male</td>\n",
       "      <td>61</td>\n",
       "      <td>South Toddport, KS 11955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>James Davis</td>\n",
       "      <td>674 Monica Dam</td>\n",
       "      <td>male</td>\n",
       "      <td>84</td>\n",
       "      <td>Meganport, IA 84426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Laura Hunter</td>\n",
       "      <td>2304 Marvin Inlet Suite 853</td>\n",
       "      <td>female</td>\n",
       "      <td>4</td>\n",
       "      <td>Olsonchester, TX 69125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Stephanie Gamble</td>\n",
       "      <td>129 Howard Knolls Suite 070</td>\n",
       "      <td>female</td>\n",
       "      <td>72</td>\n",
       "      <td>Gonzalezfort, CT 76785</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               name                      address  gender  age  \\\n",
       "0     Heather Chung            9509 James Rapids  female   74   \n",
       "1     Stephen Hayes      188 David Run Suite 795    male   49   \n",
       "2     Thomas Huerta              481 Rivera Ford  female   26   \n",
       "3     Samuel Lawson     61652 Amy Road Suite 256  female   39   \n",
       "4  Richard Cummings           468 Michael Skyway    male   81   \n",
       "5   Stephanie Clark   0885 Reeves Camp Suite 040    male   86   \n",
       "6        David Hahn        1123 Hernandez Corner    male   61   \n",
       "7       James Davis               674 Monica Dam    male   84   \n",
       "8      Laura Hunter  2304 Marvin Inlet Suite 853  female    4   \n",
       "9  Stephanie Gamble  129 Howard Knolls Suite 070  female   72   \n",
       "\n",
       "              other_address  \n",
       "0  Rebeccaborough, OR 73595  \n",
       "1       New Linda, WA 05108  \n",
       "2   Lake Bradview, FL 11180  \n",
       "3        Markview, WV 39420  \n",
       "4       Kaylafort, OR 85551  \n",
       "5       Dianaland, CO 88542  \n",
       "6  South Toddport, KS 11955  \n",
       "7       Meganport, IA 84426  \n",
       "8    Olsonchester, TX 69125  \n",
       "9    Gonzalezfort, CT 76785  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "def split_address(address):\n",
    "    street_address, other = address.split('\\n')\n",
    "    return {\n",
    "        \"address\": street_address,\n",
    "        \"other_address\": other\n",
    "    }\n",
    "    \n",
    "table = KnockoffTable(\n",
    "    \"person\",\n",
    "    columns=[\"name\", \"address\", \"gender\", \"age\", \"other_address\"],\n",
    "    factories=[\n",
    "        ColumnFactory(\"name\", FakerFactory(\"name\")),\n",
    "        ColumnFactory(\"address\", FakerFactory(\"address\")),\n",
    "        ColumnFactory(\"gender\", ChoiceFactory([\"male\", \"female\"])),\n",
    "        ColumnFactory(\"age\", FakerFactory(\"pyint\", min_value=0, max_value=100)),\n",
    "        # this factory will take the address generated and split into columns\n",
    "        # including a column that will replace the original address with just\n",
    "        # the street address\n",
    "        CollectionsFactory(split_address, depends_on=[\"address\"])\n",
    "    ],\n",
    "    size=10,\n",
    ")\n",
    "\n",
    "display(table.build())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac391b37",
   "metadata": {},
   "source": [
    "###  <a name=\"KnockoffUniqueConstraint\"></a> KnockoffUniqueConstraint\n",
    "\n",
    "Constraints such as the KnockoffUniqueConstraint can be provided to the KnockoffTable to enforce when generating a row. Any generated row must satisfy the unique constraint, otherwise it will be rejected. If `attempt_limit` is reached for trying to generate a row that satisfies all constraints, an `AttemptLimitReached` Error will be thrown. The default `attempt_limit` is 1000000 if `None` is provided in the __init__ of KnockoffTable. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "aa972752",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>id</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4</td>\n",
       "      <td>Debbie Hill</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>Rebecca Bell</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5</td>\n",
       "      <td>Michael Kelly</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>Christine Hernandez</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>Stephanie Wright</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id                 name\n",
       "0   4          Debbie Hill\n",
       "1   3         Rebecca Bell\n",
       "2   5        Michael Kelly\n",
       "3   2  Christine Hernandez\n",
       "4   1     Stephanie Wright"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from knockoff.sdk.constraints import KnockoffUniqueConstraint\n",
    "\n",
    "table = KnockoffTable(\n",
    "    \"person\",\n",
    "    columns=[\"id\", \"name\"],\n",
    "    factories=[\n",
    "        ColumnFactory(\"id\", FakerFactory(\"pyint\", min_value=1, max_value=5)),\n",
    "        ColumnFactory(\"name\", FakerFactory(\"name\"))\n",
    "    ],\n",
    "    size=5,\n",
    "    constraints=[KnockoffUniqueConstraint(['id'])]\n",
    ")\n",
    "display(table.build())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d187718",
   "metadata": {},
   "source": [
    "### <a name=\"Autoloading\"></a> Autoloading\n",
    "\n",
    "Using `autoload=True` in the __init__ of KnockoffTable will allow the schema including any unique constraints to be relfected automatically from the database. This setting requires the KnockoffTable instance to be prepared with a `KnockoffDatabaseService` which provides database operations that enables the autoloading. This is done via the KnockoffTable's `prepare` method which takes an optional database service which needs to be called prior to the `build` method. In most cases, the `prepare` and `build` method for the KnockoffTable will be called indirectly by a `KnockoffDB` instance."
   ]
  }
 ],
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