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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exercises"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## #1: Display the total number of watchers per language (ignore repos w/o a language)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Your output should look something like this:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```bash\n",
    "C# 32\n",
    "C++ 63\n",
    "HTML 349\n",
    "JavaScript 3881\n",
    "Jupyter Notebook 5481\n",
    "PHP 201\n",
    "Python 37007\n",
    "R 18\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use the url `https://api.github.com/search/repositories?q=data` for source data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Your answer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from urllib.request import urlopen\n",
    "from itertools import groupby\n",
    "from operator import itemgetter\n",
    "from ijson import items\n",
    "\n",
    "url2 = 'https://api.github.com/search/repositories?q=data'\n",
    "f = '???'\n",
    "repos = '???'\n",
    "\n",
    "# ...\n",
    "\n",
    "kwargs = {}\n",
    "grouped = groupby([], **kwargs)\n",
    "\n",
    "for key, group in grouped:\n",
    "    cnt = '???'\n",
    "    print(key, cnt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## #2: Language with the most number of watchers, per `owner_type` per `has_pages`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Your output should look something like this:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```python\n",
    "{'has_pages': True,\n",
    " 'language': 'JavaScript',\n",
    " 'owner_type': 'Organization',\n",
    " 'watchers': 128605}\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use the url `https://api.github.com/search/repositories?q=data&sort=stars&order=desc` for source data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Your answer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from urllib.request import urlopen\n",
    "from operator import itemgetter\n",
    "from functools import partial\n",
    "from meza import process as pr, fntools as ft\n",
    "from meza.io import read_json\n",
    "\n",
    "url4 = 'https://api.github.com/search/repositories?q=data&sort=stars&order=desc'\n",
    "f = '???'\n",
    "records = '???'\n",
    "\n",
    "# Some of the functions you will use are `ft.flatten`, `pr.pivot`, `pr.normalize`\n",
    "# `pr.group`, `pr.fillempty`, and `pr.aggregate`. You can view documentation for\n",
    "# these functions in the doc-blocks at the links below:\n",
    "# \n",
    "# https://github.com/reubano/meza/blob/master/meza/process.py\n",
    "# https://github.com/reubano/meza/blob/master/meza/fntools.py\n",
    "\n",
    "# ...\n",
    "\n",
    "keyfunc = lambda x: True\n",
    "kwargs = {}\n",
    "grouped = pr.group([], keyfunc, **kwargs)\n",
    "\n",
    "for key, group in grouped:\n",
    "    # ...\n",
    "    pass"
   ]
  }
 ],
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