arg_parser_example.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div style=\"background: #efffed;\n",
    "            border: 1px solid grey;\n",
    "            margin: 8px 0 8px 0;\n",
    "            text-align: center;\n",
    "            padding: 8px; \">\n",
    "    <i class=\"fa-play fa\" \n",
    "       style=\"font-size: 40px;\n",
    "              line-height: 40px;\n",
    "              margin: 8px;\n",
    "              color: #444;\">\n",
    "    </i>\n",
    "    <center>\n",
    "    Click into a code cell (the gray blocks below) to select or edit it.<br/>\n",
    "    To run a selected code cell, hit <pre style=\"background: #efffed\">Shift + Enter</pre>\n",
    "    Make sure that each code cell runs successfully before you move on to the next one.\n",
    "    </center>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for development purposes, enable modules autoreload\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scripts.calculator import predict_y\n",
    "predict_y(5, m = 2, c = 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20.0\n"
     ]
    }
   ],
   "source": [
    "!python3 scripts/calculator.py predict_y -x 5 -m 2 -c 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "usage: calculator.py [-h] {predict_y} ...\n",
      "\n",
      "positional arguments:\n",
      "  {predict_y}\n",
      "    predict_y  linear regression y predictor\n",
      "\n",
      "optional arguments:\n",
      "  -h, --help   show this help message and exit\n"
     ]
    }
   ],
   "source": [
    "!python3 scripts/calculator.py -h"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "usage: calculator.py predict_y [-h] -x X [-m M] [-c C]\n",
      "\n",
      "optional arguments:\n",
      "  -h, --help  show this help message and exit\n",
      "  -x X        x value\n",
      "  -m M        slope\n",
      "  -c C        y-intercept\n"
     ]
    }
   ],
   "source": [
    "!python3 scripts/calculator.py predict_y -h"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}