PY0101EN-4-1-ReadFile.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p style=\"text-align:center\">\n",
    "    <a href=\"https://skills.network/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDeveloperSkillsNetworkPY0101ENSkillsNetwork19487395-2022-01-01\" target=\"_blank\">\n",
    "    <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/assets/logos/SN_web_lightmode.png\" width=\"200\" alt=\"Skills Network Logo\"  />\n",
    "    </a>\n",
    "</p>\n",
    "\n",
    "# Reading Files Python\n",
    "\n",
    "Estimated time needed: **40** minutes\n",
    "\n",
    "## Objectives\n",
    "\n",
    "After completing this lab you will be able to:\n",
    "\n",
    "*   Read text files using Python libraries\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Table of Contents</h2>\n",
    "<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
    "    <ul>\n",
    "        <li><a href=\"https://download/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDeveloperSkillsNetworkPY0101ENSkillsNetwork19487395-2022-01-01\">Download Data</a></li>\n",
    "        <li><a href=\"https://read/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDeveloperSkillsNetworkPY0101ENSkillsNetwork19487395-2022-01-01\">Reading Text Files</a></li>\n",
    "        <li><a href=\"https://better/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDeveloperSkillsNetworkPY0101ENSkillsNetwork19487395-2022-01-01\">A Better Way to Open a File</a></li>\n",
    "    </ul>\n",
    "\n",
    "</div>\n",
    "\n",
    "<hr>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2 id=\"download\">Download Data</h2>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('Example1.txt', <http.client.HTTPMessage at 0x22602ba5070>)"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import urllib.request\n",
    "url = 'https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/labs/Module%204/data/example1.txt'\n",
    "filename = 'Example1.txt'\n",
    "urllib.request.urlretrieve(url, filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "'wget' is not recognized as an internal or external command,\n",
      "operable program or batch file.\n"
     ]
    }
   ],
   "source": [
    "# Download Example file\n",
    "\n",
    "\n",
    "!wget -O /resources/data/Example1.txt https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/labs/Module%204/data/example1.txt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2 id=\"read\">Reading Text Files</h2>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One way to read or write a file in Python is to use the built-in <code>open</code> function. The <code>open</code> function provides a **File object** that contains the methods and attributes you need in order to read, save, and manipulate the file. In this notebook, we will only cover **.txt** files. The first parameter you need is the file path and the file name. An example is shown as follow:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/labs/Module%204/images/ReadOpen.png\" width=\"500\" />\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The mode argument is optional and the default value is **r**. In this notebook we only cover two modes:\n",
    "\n",
    "<ul>\n",
    "    <li>**r**: Read mode for reading files </li>\n",
    "    <li>**w**: Write mode for writing files</li>\n",
    "</ul>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the next example, we will use the text file **Example1.txt**. The file is shown as follows:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/labs/Module%204/images/ReadFile.png\" width=\"100\" />\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We read the file:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read the Example1.txt\n",
    "\n",
    "example1 = \"Example1.txt\"\n",
    "file1 = open(example1, \"r\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can view the attributes of the file.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The name of the file:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Example1.txt'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Print the path of file\n",
    "\n",
    "file1.name"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The mode the file object is in:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'r'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Print the mode of file, either 'r' or 'w'\n",
    "\n",
    "file1.mode"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can read the file and assign it to a variable :\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'This is line 1 \\nThis is line 2\\nThis is line 3'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read the file\n",
    "\n",
    "FileContent = file1.read()\n",
    "FileContent"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The **/n** means that there is a new line.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can print the file:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is line 1 \n",
      "This is line 2\n",
      "This is line 3\n"
     ]
    }
   ],
   "source": [
    "# Print the file with '\\n' as a new line\n",
    "\n",
    "print(FileContent)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The file is of type string:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "str"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Type of file content\n",
    "\n",
    "type(FileContent)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is very important that the file is closed in the end. This frees up resources and ensures consistency across different python versions.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Close file after finish\n",
    "\n",
    "file1.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2 id=\"better\">A Better Way to Open a File</h2>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using the <code>with</code> statement is better practice, it automatically closes the file even if the code encounters an exception. The code will run everything in the indent block then close the file object.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is line 1 \n",
      "This is line 2\n",
      "This is line 3\n"
     ]
    }
   ],
   "source": [
    "# Open file using with\n",
    "\n",
    "with open(example1, \"r\") as file1:\n",
    "    FileContent = file1.read()\n",
    "    print(FileContent)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The file object is closed, you can verify it by running the following cell:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Verify if the file is closed\n",
    "\n",
    "file1.closed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see the info in the file:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is line 1 \n",
      "This is line 2\n",
      "This is line 3\n"
     ]
    }
   ],
   "source": [
    "# See the content of file\n",
    "\n",
    "print(FileContent)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The syntax is a little confusing as the file object is after the <code>as</code> statement. We also don’t explicitly close the file. Therefore we summarize the steps in a figure:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/labs/Module%204/images/ReadWith.png\" width=\"500\" />\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We don’t have to read the entire file, for example, we can read the first 4 characters by entering three as a parameter to the method **.read()**:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This\n"
     ]
    }
   ],
   "source": [
    "# Read first four characters\n",
    "\n",
    "with open(example1, \"r\") as file1:\n",
    "    print(file1.read(4))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once the method <code>.read(4)</code> is called the first 4 characters are called. If we call the method again, the next 4 characters are called. The output for the following cell will demonstrate the process for different inputs to the method <code>read()</code>:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This\n",
      " is \n",
      "line 1 \n",
      "\n",
      "This is line 2\n"
     ]
    }
   ],
   "source": [
    "# Read certain amount of characters\n",
    "\n",
    "with open(example1, \"r\") as file1:\n",
    "    print(file1.read(4))\n",
    "    print(file1.read(4))\n",
    "    print(file1.read(7))\n",
    "    print(file1.read(15))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The process is illustrated in the below figure, and each color represents the part of the file read after the method <code>read()</code> is called:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-PY0101EN-SkillsNetwork/labs/Module%204/images/read.png\" width=\"500\" />\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is an example using the same file, but instead we read 16, 5, and then 9 characters at a time:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is line 1 \n",
      "\n",
      "This \n",
      "is line 2\n"
     ]
    }
   ],
   "source": [
    "# Read certain amount of characters\n",
    "\n",
    "with open(example1, \"r\") as file1:\n",
    "    print(file1.read(16))\n",
    "    print(file1.read(5))\n",
    "    print(file1.read(9))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also read one line of the file at a time using the method <code>readline()</code>:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "first line: This is line 1 \n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Read one line\n",
    "\n",
    "with open(example1, \"r\") as file1:\n",
    "    print(\"first line: \" + file1.readline())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also pass an argument to <code> readline() </code> to specify the number of charecters we want to read. However, unlike <code> read()</code>, <code> readline()</code> can only read one line at most.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is line 1 \n",
      "\n",
      "This is line 2\n",
      "This \n"
     ]
    }
   ],
   "source": [
    "with open(example1, \"r\") as file1:\n",
    "    print(file1.readline(20)) # does not read past the end of line\n",
    "    print(file1.read(20)) # Returns the next 20 chars\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can use a loop to iterate through each line:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 0 :  This is line 1 \n",
      "\n",
      "Iteration 1 :  This is line 2\n",
      "\n",
      "Iteration 2 :  This is line 3\n"
     ]
    }
   ],
   "source": [
    "# Iterate through the lines\n",
    "\n",
    "with open(example1,\"r\") as file1:\n",
    "        i = 0;\n",
    "        for line in file1:\n",
    "            print(\"Iteration\", str(i), \": \", line)\n",
    "            i = i + 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can use the method <code>readlines()</code> to save the text file to a list:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read all lines and save as a list\n",
    "\n",
    "with open(example1, \"r\") as file1:\n",
    "    FileasList = file1.readlines()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Each element of the list corresponds to a line of text:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'This is line 1 \\n'"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Print the first line\n",
    "\n",
    "FileasList[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Print the second line\n",
    "\n",
    "FileasList\\[1]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'This is line 3'"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Print the third line\n",
    "\n",
    "FileasList[2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n",
    "<h2>The last exercise!</h2>\n",
    "<p>Congratulations, you have completed your first lesson and hands-on lab in Python.\n",
    "<hr>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Author\n",
    "\n",
    "<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-SkillsNetworkCoursesIBMDeveloperSkillsNetworkPY0101ENSkillsNetwork19487395-2022-01-01\" target=\"_blank\">Joseph Santarcangelo</a>\n",
    "\n",
    "## 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-SkillsNetworkCoursesIBMDeveloperSkillsNetworkPY0101ENSkillsNetwork19487395-2022-01-01\">Mavis Zhou</a>\n",
    "\n",
    "## Change Log\n",
    "\n",
    "| Date (YYYY-MM-DD) | Version | Changed By    | Change Description                                        |\n",
    "| ----------------- | ------- | ------------- | --------------------------------------------------------- |\n",
    "| 2022-01-10        | 2.1     | Malika        | Removed the readme for GitShare                           |\n",
    "| 2020-09-30        | 1.3     | Malika        | Deleted exericse \"Weather Data\"                           |\n",
    "| 2020-09-30        | 1.2     | Malika Singla | Weather Data dataset link added                           |\n",
    "| 2020-09-30        | 1.1     | Arjun Swani   | Added exericse \"Weather Data\"                             |\n",
    "| 2020-09-30        | 1.0     | Arjun Swani   | Added blurbs about closing files and read() vs readline() |\n",
    "| 2020-08-26        | 0.2     | Lavanya       | Moved lab to course repo in GitLab                        |\n",
    "|                   |         |               |                                                           |\n",
    "|                   |         |               |                                                           |\n",
    "\n",
    "<hr/>\n",
    "\n",
    "## <h3 align=\"center\"> © IBM Corporation 2020. All rights reserved. <h3/>\n"
   ]
  }
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