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‎Activity01/Activity01.ipynb

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‎Activity02/Activity02.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import urllib.request, urllib.parse, urllib.error\n",
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"import json\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"2.\tLoad the secret API key (you have to get one from the OMDB website and use that; it has a 1,000 daily limit) from a JSON file, stored in the same folder into a variable, by using json.loads(). \n",
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"Note\n",
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"The following cell will not be executed in the solution notebook because the author cannot give out their private API key.\n",
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"The students/users/instructor will need to obtain a key and store it in a JSON file. We are calling this file APIkeys.json. \n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"with open('APIkeys.json') as f:\n",
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" keys = json.load(f)\n",
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" omdbapi = keys['OMDBapi']\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"serviceurl = 'http://www.omdbapi.com/?'"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"apikey = '&apikey='+omdbapi"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"def print_json(json_data):\n",
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" list_keys=['Title', 'Year', 'Rated', 'Released', 'Runtime', 'Genre', 'Director', 'Writer', \n",
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" 'Actors', 'Plot', 'Language', 'Country', 'Awards', 'Ratings', \n",
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" 'Metascore', 'imdbRating', 'imdbVotes', 'imdbID']\n",
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" print(\"-\"*50)\n",
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" for k in list_keys:\n",
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" if k in list(json_data.keys()):\n",
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" print(f\"{k}: {json_data[k]}\")\n",
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" print(\"-\"*50)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"def save_poster(json_data):\n",
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" import os\n",
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" title = json_data['Title']\n",
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" poster_url = json_data['Poster']\n",
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" # Splits the poster url by '.' and picks up the last string as file extension\n",
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" poster_file_extension=poster_url.split('.')[-1]\n",
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" # Reads the image file from web\n",
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" poster_data = urllib.request.urlopen(poster_url).read()\n",
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" \n",
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" savelocation=os.getcwd()+'\\\\'+'Posters'+'\\\\'\n",
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" # Creates new directory if the directory does not exist. Otherwise, just use the existing path.\n",
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" if not os.path.isdir(savelocation):\n",
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" os.mkdir(savelocation)\n",
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" \n",
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" filename=savelocation+str(title)+'.'+poster_file_extension\n",
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" f=open(filename,'wb')\n",
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" f.write(poster_data)\n",
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" f.close()\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"def search_movie(title):\n",
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" try:\n",
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" url = serviceurl + urllib.parse.urlencode({'t': str(title)})+apikey\n",
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" print(f'Retrieving the data of \"{title}\" now... ')\n",
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" print(url)\n",
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" uh = urllib.request.urlopen(url)\n",
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" data = uh.read()\n",
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" json_data=json.loads(data)\n",
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" \n",
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" if json_data['Response']=='True':\n",
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" print_json(json_data)\n",
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" # Asks user whether to download the poster of the movie\n",
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" if json_data['Poster']!='N/A':\n",
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" save_poster(json_data)\n",
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" else:\n",
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" print(\"Error encountered: \",json_data['Error'])\n",
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" \n",
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" except urllib.error.URLError as e:\n",
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" print(f\"ERROR: {e.reason}\"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"search_movie(\"Titanic\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"search_movie(\"Random_error\")"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎Exercise01/Exercise01.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import requests "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"# First assign the URL of Wikipedia home page to a strings \n",
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"\n",
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"wiki_home = \"https://en.wikipedia.org/wiki/Main_Page\" "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<Response [200]>"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"response = requests.get(wiki_home) \n",
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"response\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"requests.models.Response"
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]
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},
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"execution_count": 14,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"type(response) "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎Exercise02/Exercise02.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"def status_check(r):\n",
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" if r.status_code==200:\n",
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" print(\"Success!\")\n",
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" return 1\n",
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" else:\n",
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" print(\"Failed!\")\n",
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" return -1\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"import requests"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"wiki_home = \"https://en.wikipedia.org/wiki/Main_Page\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"response = requests.get(wiki_home)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Success!\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"1"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"status_check(response)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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