{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## This is a prototype way to create models on the fly using pandas as the type parser.\n",
    "### It was phased out in favor of creating models manually to avoid any mistakes pandas could make. \n",
    "### However it is kept here for just in case."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Automatically create the django model using pandas for type inference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from django.db import models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "read the csv file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"GaiaSource_000000-003111.csv\", comment='#')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "map pandas types to django fields"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "dtype_mapping = {\n",
    "    'int64' : 'models.IntegerField(null=True)',\n",
    "    'float64' : 'models.FloatField(null=True)',\n",
    "    'bool' : 'models.BooleanField(null=True)',\n",
    "    'object' : 'models.CharField(max_length=255, null=True)'\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "generate the model code line by line"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_model(df, model_name):\n",
    "\n",
    "    class_code = f\"class {model_name}(models.Model):\\n\"\n",
    "\n",
    "    for column in df.columns:\n",
    "        dtype = str(df[column].dtype)\n",
    "        field_type = dtype_mapping.get(dtype, 'models.CharField(max_length=255, null=True)')\n",
    "        class_code += f\"    {column} = {field_type}\\n\"\n",
    "    return class_code\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_code = generate_model(df, 'samplemodel')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "save the model code to the models.py file to be used"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('gaia_orm/sample_app/models.py', 'a') as file:\n",
    "    file.write(model_code)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}