Collecting_data_using_API_review-Lab.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"https://cognitiveclass.ai/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDeveloperSkillsNetworkPY0101ENSkillsNetwork19487395-2021-01-01\">\n",
    "    <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/IDSNlogo.png\" width=\"300\" align=\"center\">\n",
    "</a>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1> HTTP and Requests</h1>\n",
    "\n",
    "Estimated time needed: **30** minutes\n",
    "\n",
    "## Objectives\n",
    "\n",
    "After completing this lab you will be able to:\n",
    "\n",
    "*   Understand HTTP\n",
    "*   Handle HTTP Requests\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Table of Contents</h2>\n",
    "\n",
    "<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
    "    <ul>\n",
    "        <li>\n",
    "            <a href=\"#Overview-of-HTTP\">Overview of HTTP </a>\n",
    "            <ul>\n",
    "                <li><a href=\"#Uniform-Resource-Locator:URL\">Uniform Resource Locator:URL</a></li>\n",
    "                 <li><a href=\"#Request\">Request</a></li>\n",
    "                <li><a href=\"#Response\">Response</a></li>\n",
    "            </ul>\n",
    "        </li>\n",
    "        <li>\n",
    "            <a href=\"#Requests-in-Python\">Requests in Python  </a>\n",
    "            <ul>\n",
    "                <li><a href=\"#Get-Request-with-URL-Parameters\">Get Request with URL Parameters</a></li>\n",
    "                <li><a href=\"#Post-Requests\">Post Requests </a></li>\n",
    "\n",
    "</ul>\n",
    "\n",
    "</div>\n",
    "\n",
    "<hr>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overview of HTTP\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When you, the **client**, use a web page your browser sends an **HTTP** request to the **server** where the page is hosted. The server tries to find the desired **resource** by default \"<code>index.html</code>\". If your request is successful, the server will send the object to the client in an **HTTP response**. This includes information like the type of the **resource**, the length of the **resource**, and other information.\n",
    "\n",
    "<p>\n",
    "The figure below represents the process. The circle on the left represents the client, the circle on the right represents the Web server. The table under the Web server represents a list of resources stored in the web server. In  this case an <code>HTML</code> file, <code>png</code> image, and <code>txt</code> file .\n",
    "</p>\n",
    "<p>\n",
    "The <b>HTTP</b> protocol allows you to send and receive information through the web including webpages, images, and other web resources. In this lab, we will provide an overview of the Requests library for interacting with the <code>HTTP</code> protocol. \n",
    "</p\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
    "         <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/labs/Module%205/images/reqest_basics.png\" width=\"750\" align=\"center\">\n",
    "\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Uniform Resource Locator:URL\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Uniform resource locator (URL) is the most popular way to find resources on the web.  We can break the URL into three parts.\n",
    "\n",
    "<ul>\n",
    "    <li><b>Scheme</b>:- This is this protocol, for this lab it will always be <code>http://</code>  </li>\n",
    "    <li><b> Internet address or  Base URL </b>:- This will be used to find the location here are some examples: <code>www.ibm.com</code> and  <code> www.gitlab.com </code> </li>\n",
    "    <li><b>Route</b>:- Location on the web server for example: <code>/images/IDSNlogo.png</code> </li>\n",
    "</ul>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You may also hear the term Uniform Resource Identifier (URI), URL are actually a subset of URIs. Another popular term is endpoint, this is the URL of an operation provided by a Web server.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Request\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The process can be broken into the <b>Request</b> and <b>Response </b> process.  The request using the get method is partially illustrated below. In the start line we have the <code>GET</code> method, this is an <code>HTTP</code> method. Also the location of the resource  <code>/index.html</code> and the <code>HTTP</code> version. The Request header passes additional information with an <code>HTTP</code> request:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
    "         <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/labs/Module%205/images/reqest_messege.png\" width=\"400\" align=\"center\">\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When an <code>HTTP</code> request is made, an <code>HTTP</code> method is sent, this tells the server what action to perform.  A list of several <code>HTTP</code> methods is shown below. We will go over more examples later.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
    "         <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/labs/Module%205/images/http_methods.png\" width=\"400\" align=\"center\">\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Response\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The figure below represents the response; the response start line contains the version number <code>HTTP/1.0</code>, a status code (200) meaning success, followed by a descriptive phrase (OK). The response header contains useful information. Finally, we have the response body containing the requested file, an <code> HTML </code> document.  It should be noted that some requests have headers.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
    "         <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/labs/Module%205/images/response_message.png\" width=\"400\" align=\"center\">\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some status code examples are shown in the table below, the prefix indicates the class. These are shown in yellow, with actual status codes shown in  white. Check out the following <a href=\"https://developer.mozilla.org/en-US/docs/Web/HTTP/Status?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDeveloperSkillsNetworkPY0101ENSkillsNetwork19487395-2021-01-01\">link </a> for more descriptions.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
    "         <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/labs/Module%205/images/status_code.png\" width=\"300\" align=\"center\">\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Requests in Python\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Requests is a Python Library that allows you to send <code>HTTP/1.1</code> requests easily. We can import the library as follows:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import requests"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will also use the following libraries:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import os \n",
    "from PIL import Image\n",
    "from IPython.display import IFrame"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can make a <code>GET</code> request via the method <code>get</code> to [www.ibm.com](http://www.ibm.com/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDeveloperSkillsNetworkPY0101ENSkillsNetwork19487395-2021-01-01):\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "\n",
    "url='https://www.ibm.com/'\n",
    "r=requests.get(url)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have the response object <code>r</code>, this has information about the request, like the status of the request. We can view the status code using the attribute <code>status_code</code>.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "200"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.status_code"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can view the request headers:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'User-Agent': 'python-requests/2.29.0', 'Accept-Encoding': 'gzip, deflate, br', 'Accept': '*/*', 'Connection': 'keep-alive', 'Cookie': '_abck=A2E013E9CA1A0201AE57FDC993D8442A~-1~YAAQbu4uFxj1RleNAQAATdIPrAvU9oz+DR30y4UjCHma6HmhgW7Z1JPiiWrbJVIdsxNayQHIV1nxZEPbEUjZKCnDiiM7P94US5weI2lNvSA2R3LghdUUoiMQMRMs5BiWU8x8p4fEiSqQXGiDvgEF6mfEgK5r9+iBmBsLmCF3gtgNY3agKz55f+Qhd8UaoNjBps+RXahL+xe1CEJ5C2Ahv9AgufwFTWD/UuLemiizP3W8jiC6hH3dNMm1zhx0CHcjRz/KAPzkPeOY8G3ug/Ov/iQaCqRh7nAWuJdTIKoYmhQZbanYuZB+hUjci/2jNs2M5CKbZljuWI6mVAw2VY+AK0byAl7U/k/qhxD+d+xDafguHoaABK4=~-1~-1~-1; bm_sz=F7F432DD6B7431C80DFC0FFCD16634FD~YAAQbu4uFxn1RleNAQAATdIPrBYeRvKzUTJt3dmYbK0Bt51d/jSndFikCcc2mE5paymoy/Ih7dVsrxDn8uu9f3rTFTb2R9JPDRqnDDFKvfi0F5gb2RULvX3FGsgqDR5uUSSFT893dRGgENowFu81bgq0bUZdxbEfXF5ZhMXM8an422C6knEn+7N843zXg8IXSlIbboDLStkG3Ivp4ALsRsby7zBTXC5Ed2WDypdkd2IwxfsBYjnp7kqbqYEzvu/UE1RBxGj+Kc5x8cg5J5LByi2yFc5ztraGP1ImuPdQ+SYwlD2wPrSD0fJ4oaGzeUtly3KnHiMd4ceV+/k=~4273202~3553081'}\n"
     ]
    }
   ],
   "source": [
    "print(r.request.headers)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can view the request body, in the following line, as there is no body for a get request we get a <code>None</code>:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "request body: None\n"
     ]
    }
   ],
   "source": [
    "print(\"request body:\", r.request.body)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can view the <code>HTTP</code> response header using the attribute <code>headers</code>. This returns a python dictionary of <code>HTTP</code> response headers.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Content-Type': 'text/html;charset=utf-8', 'X-Dispatcher': 'prod-publish-0', 'X-Vhost': 'publish', 'X-Content-Type-Options': 'nosniff', 'Last-Modified': 'Thu, 15 Feb 2024 08:11:54 GMT', 'X-Frame-Options': 'SAMEORIGIN', 'CF-Cache-Status': 'DYNAMIC', 'Server': 'cloudflare', 'CF-RAY': '855c31e8d9482d14-IAD', 'Cache-Control': 'max-age=714', 'Expires': 'Thu, 15 Feb 2024 09:30:48 GMT', 'X-Akamai-Transformed': '9 12341 0 pmb=mTOE,2', 'Content-Encoding': 'gzip', 'Date': 'Thu, 15 Feb 2024 09:18:54 GMT', 'Content-Length': '12614', 'Connection': 'keep-alive', 'Vary': 'Accept-Encoding', 'Strict-Transport-Security': 'max-age=31536000'}\n"
     ]
    }
   ],
   "source": [
    "header=r.headers\n",
    "print(r.headers)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can obtain the date the request was sent using the key <code>Date</code>.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Thu, 15 Feb 2024 09:18:54 GMT'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "header['date']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<code>Content-Type</code> indicates the type of data:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'text/html;charset=utf-8'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "header['Content-Type']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can also check the <code>encoding</code>:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'utf-8'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " r.encoding"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As the <code>Content-Type</code> is <code>text/html</code> we can use the attribute <code>text</code> to display the <code>HTML</code> in the body. We can review the first 100 characters:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\n<!DOCTYPE HTML>\\n<html lang=\"en-us\">\\n<head>\\n    \\n    \\n    \\n    \\n    <meta charset=\"UTF-8\"/>\\n    <met'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.text[0:100]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can load other types of data for non-text requests, like images. Consider the URL of the following image:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Use single quotation marks for defining string\n",
    "url='https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/IDSNlogo.png'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can make a get request:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "r=requests.get(url)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can look at the response header:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Date': 'Thu, 15 Feb 2024 09:20:36 GMT', 'X-Clv-Request-Id': 'ebf9da01-956f-4e55-8118-8134e38a1385', 'Server': 'Cleversafe', 'X-Clv-S3-Version': '2.5', 'Accept-Ranges': 'bytes', 'x-amz-request-id': 'ebf9da01-956f-4e55-8118-8134e38a1385', 'ETag': '\"8bb44578fff8fdcc3d2972be9ece0164\"', 'Content-Type': 'image/png', 'Last-Modified': 'Wed, 16 Nov 2022 03:32:41 GMT', 'Content-Length': '78776'}\n"
     ]
    }
   ],
   "source": [
    "print(r.headers)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see the <code>'Content-Type'</code>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'image/png'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.headers['Content-Type']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "An image is a response object that contains the image as a <a href=\"https://docs.python.org/3/glossary.html?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDeveloperSkillsNetworkPY0101ENSkillsNetwork19487395-2021-01-01#term-bytes-like-object\">bytes-like object</a>. As a result, we must save it using a file object. First, we specify the <u>file path and\n",
    "name</u>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "path=os.path.join(os.getcwd(),'image.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We save the file, in order to access the body of the response we use the attribute <code>content</code> then save it using the <code>open</code> function and write <code>method</code>:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "with open(path,'wb') as f:\n",
    "    f.write(r.content)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can view the image:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGBA size=1880x656 at 0x7FE6C05D8B10>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image.open(path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3>Question: Download a file </h3>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Consider the following URL.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<code>URL = <https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/labs/Module%205/data/Example1.txt</code>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Write the commands to download the txt file in the given link.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "url='https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/labs/Module%205/data/Example1.txt'\n",
    "path=os.path.join(os.getcwd(),'example1.txt')\n",
    "r=requests.get(url)\n",
    "with open(path,'wb') as f:\n",
    "    f.write(r.content)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<details><summary>Click here for the solution</summary>\n",
    "\n",
    "```python\n",
    "url='https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/labs/Module%205/data/Example1.txt'\n",
    "path=os.path.join(os.getcwd(),'example1.txt')\n",
    "r=requests.get(url)\n",
    "with open(path,'wb') as f:\n",
    "    f.write(r.content)\n",
    "\n",
    "```\n",
    "\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get Request with URL Parameters\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can use the <b>GET</b> method to modify the results of your query, for example retrieving data from an API. We send a <b>GET</b> request to the  server. Like before we have the <b>Base URL</b>, in the <b>Route</b> we append <code>/get</code>, this indicates we would like to preform a <code>GET</code> request. This is demonstrated in the following table:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
    "         <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/labs/Module%205/images/base_URL_Route.png\" width=\"400\" align=\"center\">\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Base URL is for <code>[http://httpbin.org/](http://httpbin.org/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDeveloperSkillsNetworkPY0101ENSkillsNetwork19487395-2021-01-01)</code> is a simple HTTP Request & Response Service. The <code>URL</code> in Python is given by:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "url_get='http://httpbin.org/get'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A <a href=\"https://en.wikipedia.org/wiki/Query_string?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDeveloperSkillsNetworkPY0101ENSkillsNetwork19487395-2021-01-01\">query string</a> is a part of a uniform resource locator (URL), this sends other information to the web server. The start of the query is a <code>?</code>, followed by a series of parameter and value pairs, as shown in the table below. The first parameter name is <code>name</code> and the value is <code>Joseph</code>. The second parameter name is <code>ID</code> and the Value is <code>123</code>. Each pair, parameter, and value is separated by an equals sign, <code>=</code>.\n",
    "The series of pairs is separated by the ampersand <code>&</code>.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
    "         <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/labs/Module%205/images/query_string.png\" width=\"500\" align=\"center\">\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To create a Query string, add a dictionary. The keys are the parameter names and the values are the value of the Query string.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "payload={\"name\":\"Joseph\",\"ID\":\"123\"}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then passing the dictionary <code>payload</code> to the <code>params</code> parameter of the <code> get()</code> function:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "r=requests.get(url_get,params=payload)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can print out the <code>URL</code> and see the name and values.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'http://httpbin.org/get?name=Joseph&ID=123'"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.url"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There is no request body.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "request body: None\n"
     ]
    }
   ],
   "source": [
    "print(\"request body:\", r.request.body)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can print out the status code.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "200\n"
     ]
    }
   ],
   "source": [
    "print(r.status_code)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can view the response as text:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"args\": {\n",
      "    \"ID\": \"123\", \n",
      "    \"name\": \"Joseph\"\n",
      "  }, \n",
      "  \"headers\": {\n",
      "    \"Accept\": \"*/*\", \n",
      "    \"Accept-Encoding\": \"gzip, deflate, br\", \n",
      "    \"Host\": \"httpbin.org\", \n",
      "    \"User-Agent\": \"python-requests/2.29.0\", \n",
      "    \"X-Amzn-Trace-Id\": \"Root=1-65cdd7da-507d4c154d6e350e24604e7e\"\n",
      "  }, \n",
      "  \"origin\": \"150.239.85.244\", \n",
      "  \"url\": \"http://httpbin.org/get?name=Joseph&ID=123\"\n",
      "}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(r.text)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can look at the <code>'Content-Type'</code>.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'application/json'"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.headers['Content-Type']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As the content <code>'Content-Type'</code> is in the <code>JSON</code> format we can use the method <code>json()</code>, it returns a Python <code>dict</code>:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'args': {'ID': '123', 'name': 'Joseph'},\n",
       " 'headers': {'Accept': '*/*',\n",
       "  'Accept-Encoding': 'gzip, deflate, br',\n",
       "  'Host': 'httpbin.org',\n",
       "  'User-Agent': 'python-requests/2.29.0',\n",
       "  'X-Amzn-Trace-Id': 'Root=1-65cdd7da-507d4c154d6e350e24604e7e'},\n",
       " 'origin': '150.239.85.244',\n",
       " 'url': 'http://httpbin.org/get?name=Joseph&ID=123'}"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The key <code>args</code> has the name and values:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'ID': '123', 'name': 'Joseph'}"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.json()['args']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Post Requests\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Like a <code>GET</code> request, a <code>POST</code> is used to send data to a server, but the <code>POST</code> request sends the data in a request body. In order to send the Post Request in Python, in the <code>URL</code> we change the route to <code>POST</code>:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "url_post='http://httpbin.org/post'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This endpoint will expect data as a file or as a form. A form is convenient way to configure an HTTP request to send data to a server.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To make a <code>POST</code> request we use the <code>post()</code> function, the variable <code>payload</code> is passed to the parameter <code> data </code>:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "r_post=requests.post(url_post,data=payload)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Comparing the URL from the response object of the <code>GET</code> and <code>POST</code> request we see the <code>POST</code> request has no name or value pairs.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"POST request URL:\",r_post.url )\n",
    "print(\"GET request URL:\",r.url)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can compare the <code>POST</code> and <code>GET</code> request body, we see only the <code>POST</code> request has a body:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"POST request body:\",r_post.request.body)\n",
    "print(\"GET request body:\",r.request.body)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can view the form as well:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "r_post.json()['form']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There is a lot more you can do. Check out <a href=\"https://requests.readthedocs.io/en/master/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDeveloperSkillsNetworkPY0101ENSkillsNetwork19487395-2021-01-01\">Requests </a> for more.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Authors\n",
    "\n",
    "<p><a href=\"https://www.linkedin.com/in/joseph-s-50398b136/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDeveloperSkillsNetworkPY0101ENSkillsNetwork19487395-2021-01-01\" target=\"_blank\">Joseph Santarcangelo</a> <br>A Data Scientist at IBM, and holds a PhD in Electrical Engineering. His research focused on using Machine Learning, Signal Processing, and Computer Vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.</p>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Other Contributors\n",
    "\n",
    "<a href=\"https://www.linkedin.com/in/jiahui-mavis-zhou-a4537814a?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDeveloperSkillsNetworkPY0101ENSkillsNetwork19487395-2021-01-01\">Mavis Zhou</a>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Change Log\n",
    "\n",
    "| Date (YYYY-MM-DD) | Version | Changed By | Change Description           |\n",
    "| ----------------- | ------- | ---------- | ---------------------------- |\n",
    "| 2023-11-02 | 2.4 | Abhishek Gagneja | Updated instructions |\n",
    "| 2023-06-07        | 2.3     |Akansha Yadav| Spell Check                 |\n",
    "| 2021-12-20        | 2.1     | Malika     | Updated the links            |\n",
    "| 2020-09-02        | 2.0     | Simran     | Template updates to the file |\n",
    "|                   |         |            |                              |\n",
    "|                   |         |            |                              |\n",
    "\n",
    "## <h3 align=\"center\"> © IBM Corporation 2023. All rights reserved. <h3/>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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