exercise_notebooks/assessing_model_results.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Setup\n",
    "\n",
    "Make sure your virtualenv (use the same one as ml_api) is active, and all the imports below are installed\n",
    "\n",
    "Make sure your database docker container is running."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import sys\n",
    "from sqlalchemy import create_engine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add the ptdraft folder path to the sys.path list\n",
    "# WINDOWS USERS: You will need to change the backslashes (TODO: check if this is true)\n",
    "sys.path.append('../../')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A reminder that SQLAlchemy DB URIs look like this:\n",
    "`postgres+psycop2://myuser:mypassword@hackersdb.example.com:5432/mydatabase`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['/Users/christophersamiullah/repos/testing-and-monitoring-ml-deployments/exercise_notebooks', '/Users/christophersamiullah/repos/advanced_ml_deployment_draft/packages/ml_api/differential_tests', '/Users/christophersamiullah/repos/advanced_ml_deployment_draft/packages/ml_api', '/usr/local/bin/python3.7', '/usr/local/Cellar/python/3.7.4/Frameworks/Python.framework/Versions/3.7/lib/python37.zip', '/usr/local/Cellar/python/3.7.4/Frameworks/Python.framework/Versions/3.7/lib/python3.7', '/usr/local/Cellar/python/3.7.4/Frameworks/Python.framework/Versions/3.7/lib/python3.7/lib-dynload', '', '/Users/christophersamiullah/repos/testing-and-monitoring-ml-deployments/packages/ml_api/env/lib/python3.7/site-packages', '/Users/christophersamiullah/repos/testing-and-monitoring-ml-deployments/packages/ml_api/env/lib/python3.7/site-packages/IPython/extensions', '/Users/christophersamiullah/.ipython', '../', '..', '../../']\n"
     ]
    }
   ],
   "source": [
    "print(sys.path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from packages.ml_api.api.config import DevelopmentConfig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "postgresql+psycopg2://user:password@0.0.0.0:6609/ml_api_dev\n"
     ]
    }
   ],
   "source": [
    "db_uri = DevelopmentConfig.SQLALCHEMY_DATABASE_URI\n",
    "print(db_uri)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "engine = create_engine(db_uri)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "lasso_model_df = pd.read_sql_table(\"regression_model_predictions\", con=engine)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "gradient_model_df = pd.read_sql_table(\"gradient_boosting_model_predictions\", con=engine)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "combined_df = lasso_model_df.merge(gradient_model_df, how='outer')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
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       "   id user_id                datetime_captured model_version  \\\n",
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       "4  37     007 2019-12-21 11:10:34.408394+00:00      0.0.4444   \n",
       "\n",
       "                                              inputs               outputs  \n",
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       "1  [{\"1stFlrSF\": 896, \"2ndFlrSF\": 0, \"3SsnPorch\":...  [105437.16948684008]  \n",
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       "4  [{\"1stFlrSF\": 896, \"2ndFlrSF\": 0, \"3SsnPorch\":...  [105437.16948684008]  "
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     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "combined_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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