{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "talented-chapter",
   "metadata": {},
   "source": [
    "# Text (28/4 - 2021)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "inner-former",
   "metadata": {},
   "source": [
    "## Exercise\n",
    "\n",
    "Read and write a CSV file containing:\n",
    "\n",
    "<pre>\n",
    "artist,song,length\n",
    "ZZ Top,La Grange,3:50\n",
    "Iron Butterfly,In-A-Gadda-Da-Vida,17:04\n",
    "Led Zeppelin,Whole Lotta Love,5:33\n",
    "</pre>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "chemical-labor",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('some_rows.csv', 'w') as file:\n",
    "    file.write(\n",
    "'''artist,song,length\n",
    "ZZ Top,La Grange,3:50\n",
    "Iron Butterfly,In-A-Gadda-Da-Vida,17:04\n",
    "Led Zeppelin,Whole Lotta Love,5:33    \n",
    "''')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "excessive-remark",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Skip newline argument, see that it adds an additional newline\n",
    "\n",
    "import csv\n",
    "\n",
    "data = [\n",
    "    ['artist', 'song', 'length'],\n",
    "    ['ZZ Top', 'La Grange', '3:50'],\n",
    "    ['Iron Butterfly', 'In-A-Gadda-Da-Vida', '17:04'],\n",
    "    ['Led Zeppelin', 'Whole Lotta Love', '5:33']\n",
    "]\n",
    "\n",
    "with open('some_rows.csv', 'w', newline='') as file:\n",
    "#with open('some_rows.csv', 'w') as file:\n",
    "    csv_out = csv.writer(file)\n",
    "#    csv_out = csv.writer(file, delimiter=\"\\t\")\n",
    "    for row in data:\n",
    "        csv_out.writerow(row)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "imposed-thing",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "artist,song,length\n",
      "ZZ Top,La Grange,3:50\n",
      "Iron Butterfly,In-A-Gadda-Da-Vida,17:04\n",
      "Led Zeppelin,Whole Lotta Love,5:33\n"
     ]
    }
   ],
   "source": [
    "with open('some_rows.csv') as file:\n",
    "    for line in file:\n",
    "        print(line, end='')  # skip end, and see that it reads\n",
    "#        print([ord(char) for char in line])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "voluntary-prerequisite",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Header: ['artist', 'song', 'length']\n",
      "1 ['ZZ Top', 'La Grange', '3:50']\n",
      "2 ['Iron Butterfly', 'In-A-Gadda-Da-Vida', '17:04']\n",
      "3 ['Led Zeppelin', 'Whole Lotta Love', '5:33']\n"
     ]
    }
   ],
   "source": [
    "with open('some_rows.csv') as file:\n",
    "    csv_in = csv.reader(file, delimiter=',')\n",
    "    header = next(csv_in)  # csv_in is an iterator for the rows in the CSV file\n",
    "    print('Header:', header)\n",
    "    for i, row in enumerate(csv_in, start=1):\n",
    "        print(i, row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "selective-census",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'artist': 'ZZ Top', 'song': 'La Grange', 'length': '3:50'}\n",
      "{'artist': 'Iron Butterfly', 'song': 'In-A-Gadda-Da-Vida', 'length': '17:04'}\n",
      "{'artist': 'Led Zeppelin', 'song': 'Whole Lotta Love', 'length': '5:33'}\n"
     ]
    }
   ],
   "source": [
    "with open('some_rows.csv') as file:\n",
    "    csv_in = csv.DictReader(file, delimiter='\\t')  # read rows as dictionaries, 1st row are keys\n",
    "    for row in csv_in:\n",
    "        print(row)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "banner-quest",
   "metadata": {},
   "source": [
    "## Exercise\n",
    "\n",
    "Save the following to a JSON file:\n",
    "\n",
    "```\n",
    "[\n",
    "    {'id': 42, 'value': 'Something exciting'},\n",
    "    {'value': 'Also exciting news', 'id': 7}\n",
    "]\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "honest-mediterranean",
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "\n",
    "data = (\n",
    "    {'id': 42, 'value': 'Something exciting'},\n",
    "    {'value': 'Also exciting news', 'id': 7}\n",
    ")\n",
    "\n",
    "with open('some_json.json', 'w') as file:\n",
    "    json.dump(data, file)\n",
    "#    json.dump(data, file, indent=2)\n",
    "#    json.dump(data, file, indent=2, sort_keys=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "cosmetic-spelling",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[{\"id\": 42, \"value\": \"Something exciting\"}, {\"value\": \"Also exciting news\", \"id\": 7}]\n"
     ]
    }
   ],
   "source": [
    "with open('some_json.json') as file:\n",
    "    print(''.join(file))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "natural-particular",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[{'id': 42, 'value': 'Something exciting'}, {'value': 'Also exciting news', 'id': 7}]\n",
      "Also exciting news\n"
     ]
    }
   ],
   "source": [
    "with open('some_json.json') as file:\n",
    "    data = json.load(file)\n",
    "print(data)\n",
    "print(data[1]['value'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "photographic-watson",
   "metadata": {},
   "outputs": [],
   "source": [
    "# try to use pickle instead, Python local format\n",
    "\n",
    "import pickle\n",
    "\n",
    "data = (\n",
    "    {'id': 42, 'value': 'Something exciting'},\n",
    "    {'value': 'Also exciting news', 'id': 7}\n",
    ")\n",
    "\n",
    "with open('some_pickel.pickle', 'wb') as file:  # important that we use b to say it is bytes\n",
    "    pickle.dump(data, file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "thousand-calvin",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "({'id': 42, 'value': 'Something exciting'}, {'value': 'Also exciting news', 'id': 7})\n",
      "Also exciting news\n"
     ]
    }
   ],
   "source": [
    "with open('some_pickel.pickle', 'rb') as file:  # important that we use b to say it is bytes\n",
    "    data = pickle.load(file)\n",
    "print(data)\n",
    "print(data[1]['value'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "alternate-ticket",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "b'\\x80\\x04\\x95J\\x00\\x00\\x00\\x00\\x00\\x00\\x00}\\x94(\\x8c\\x02id\\x94K*\\x8c\\x05value\\x94\\x8c\\x12Something exciting\\x94u}\\x94(h\\x02\\x8c\\x12Also exciting news\\x94h\\x01K\\x07u\\x86\\x94.'\n"
     ]
    }
   ],
   "source": [
    "with open('some_pickel.pickle', 'rb') as file:\n",
    "    print(file.read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "weighted-richardson",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "128 4 149 74 0 0 0 0 0 0 0 125 148 40 140 2 105 100 148 75 42 140 5 118 97 108 117 101 148 140 18 83 111 109 101 116 104 105 110 103 32 101 120 99 105 116 105 110 103 148 117 125 148 40 104 2 140 18 65 108 115 111 32 101 120 99 105 116 105 110 103 32 110 101 119 115 148 104 1 75 7 117 134 148 46 "
     ]
    }
   ],
   "source": [
    "with open('some_pickel.pickle', 'rb') as file:\n",
    "    bytes = file.read()\n",
    "    for byte in bytes:\n",
    "        print(byte, end=' ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "conservative-perception",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "bytes"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(bytes)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "amazing-honor",
   "metadata": {},
   "source": [
    "## Exercise \n",
    "\n",
    "XML - Open Street Map\n",
    "\n",
    "Download a small map from www.openstreetmap.org as XML and plot it using matplotlib."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "impressed-possibility",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import xml.etree.ElementTree as ET\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "tree = ET.parse('map.osm')\n",
    "root = tree.getroot()\n",
    "\n",
    "nodes = [child for child in root if child.tag == 'node']\n",
    "V = {node.attrib['id']: (float(node.attrib['lon']), float(node.attrib['lat'])) for node in nodes}\n",
    "\n",
    "ways = [child for child in root if child.tag == 'way']\n",
    "\n",
    "edges = []\n",
    "for way in ways:\n",
    "    for child in way:\n",
    "        if child.tag == 'tag' and 'k' in child.attrib and child.attrib['k'] == 'highway':\n",
    "            points = [child.attrib['ref'] for child in way if child.tag == 'nd']\n",
    "            for p, q in zip(points, points[1:]):\n",
    "                edges.append((p, q))\n",
    "        \n",
    "data = []\n",
    "for p, q in edges:\n",
    "    xs, ys = zip(V[p], V[q])\n",
    "    data.extend((xs, ys, '-'))\n",
    "\n",
    "plt.plot(*data, color='k')  # edges       \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "accepting-latino",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "node 56.1748392\n",
      "node 56.1748491\n",
      "node 56.1748443\n",
      "node 56.1741359\n",
      "node 56.1699079\n",
      "node 56.1677092\n",
      "node 56.1646877\n",
      "node 56.1646251\n",
      "node 56.1602780\n",
      "node 56.1616331\n",
      "node 56.1649995\n"
     ]
    }
   ],
   "source": [
    "count = 0\n",
    "for child in root:\n",
    "    if child.tag == 'node':\n",
    "        print(child.tag, child.attrib['lat'])\n",
    "        count += 1\n",
    "        if count > 10:\n",
    "            break\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "revised-trace",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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