Updated_Python_Notes_Colab_File.ipynb

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      "display_name": "Python 3",
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        "<a href=\"https://colab.research.google.com/github/hussain0048/Python-Notes/blob/master/Updated_Python_Notes_Colab_File.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "cell_type": "markdown",
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      "source": [
        "# **Table of Content**\n",
        "\n",
        "1. *_[Introduction](#introduction)_*\n",
        "2. *_[Access your PC Information using Platform Library](#access_information)_*\n",
        "3. *_[Integerated Development Environment (IDE) ](#IDE)_*\n",
        "4. *_[First Program in Python](#first_program)_*\n",
        "5. *_[Indentation](#indentation)_*\n",
        "6.*_[Getting User Input](#user_input)_*\n",
        "7. *_[Data Types in Python](#data_types_python)_*\n",
        "8. *_[Basic Operators](#basic_operators)_*\n",
        "9. *_[Strings](#str)_*\n",
        "10. *_[Conditional Statements](#conditional_statement)_*\n",
        "11.  *_[Loops](#loops)_*   \n",
        "12. *_[Functions](#functions)_*\n",
        "13. *_[Classes and Objects](#class)_*\n",
        "14. *_[Dictionaries](#dictionary)_*\n",
        "15. *_[List](#list)_*\n",
        "16. *_[Modules and Packages](#module_package)_*\n",
        "17. *_[File Handling](#file_handling)_*\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ]
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2WZFQQORCAcS"
      },
      "source": [
        "# **Section 1-Introduction <a name='introduction'></a>**\n",
        "Python is a very simple language, and has a very straightforward syntax. It encourages programmers to program without boilerplate (prepared) code. There are two major Python versions, Python 2 and Python 3. Python 2 and 3 are quite different. This tutorial uses Python 3, because it more semantically correct and supports newer features.\n",
        "\n",
        "Python is a high-level programming language that Google, Facebook, NASA, and almost all other multinational companies worldwide use. Python has overtaken every language in recent years and has become the most popular and widely used programming language globally.\n",
        "Its popularity on the job market has grown to the extent that companies have made Python a requirement in their job postings. According to the Times of India, Python was among the top 5 highest-paid programming languages in 2021.\n",
        "But what exactly is Python, and why has it suddenly become such a sought-after language?\n",
        "\n",
        "#**1.1-Why is  ‘Python’?**\n",
        "\n",
        "Python is an interpreted, object-oriented programming language created by Guido van Rossum in 1991.\n",
        "Python can be used for everything from web development to Machine learning, Artificial intelligence, and Data Science.\n",
        "Unlike some other programming languages, Python does not require you to worry about syntax. Writing in Python is almost equal to written English. You have to use the proper functions or \"modules\" and let Python do the rest.\n",
        "The easy syntax of Python makes it great for beginners who are learning how to code and seasoned developers who want to quickly create software prototypes and earn a reasonable amount of income.\n",
        "Without wasting further time, let us get into the real business\n",
        "\n",
        "#**1.2-Why is it called ‘Python’?[4]**\n",
        "While many people assume the name Python Programming comes from something related to the Python snake, it actually comes from the TV comedy series ‘Monty Python’s Flying Circus.’ This series broadcast on the BBC channelin the United Kingdom in the 1970s and was a favorite of Guido Van Rossum’s. Because it was short, cryptic, and included the name of his favorite TV comedy show, he chose the name ‘Python.’\n",
        "\n",
        "#**1.3-Python does not require a compiler[4]**\n",
        "Python is a high-level, interpreted language that does not require a compiler, unlike other programming languages such as Java and C++.Python code is stored in a .pyc file, which serves as the Python engine and eliminates the need for a compiler.\n",
        "\n",
        "#**1.4-Python is one of Google’s official programming languages[4]**\n",
        "Python is one of the few programming languages that has been designated as an official Google language. Python became one of Google’s official programming languages due of its efficiency. It was advantageous to them because it is simple to use, even on large projects. Even YouTube is powered by Python programming.\n",
        "\n",
        "#**1.5-Python is similar to English[4]**\n",
        "Many people claim that Python is a simple language to learn. The fundamental reason for this claim is that Python is more similar to English than other programming languages. It’s simple to figure out what each line of code accomplishes. Everything is simple and straightforward.\n",
        "\n",
        "#**1.6-Wide range of aspects[4]**\n",
        "Python is a general-purpose programming language. In fact, it can be used in a wide range of coding scenarios like web development, artificial intelligence, machine learning, data analytics, internet of things and many more."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wAU3XpQj-IXe"
      },
      "source": [
        "![](https://drive.google.com/uc?export=view&id=1dGhEqYFL26I3zksGS6VGWMAfO6WM8kX5\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fEReTqP9z6Qq"
      },
      "source": [
        "# **Section 2-Access your PC Information using Platform Library**<a name='access_information'></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7SydDKYO0bM2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "4ab4febd-e560-451e-f96d-d9094091b4fd"
      },
      "source": [
        "import platform\n",
        "# Retrun Machine Type\n",
        "platform.machine()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
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            "text/plain": [
              "'x86_64'"
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    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tUfGGySY0nI2"
      },
      "source": [
        "# retrun computer Name\n",
        "platform.node()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "41bsa8OM01Ll"
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      "source": [
        "# Return your current OS\n",
        "platform.platform()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hP9N5G3j1O26"
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      "source": [
        "# Retrun process name\n",
        "platform.processor()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dB4kwr4R1Vfo"
      },
      "source": [
        "# Retrun System release\n",
        "platform.release()"
      ],
      "execution_count": null,
      "outputs": []
    },
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      "cell_type": "code",
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          "height": 35
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        "outputId": "f7561240-ba68-4399-c6e9-9b2c45bbb292"
      },
      "source": [
        "# Retrun OS name\n",
        "platform.system()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
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            "text/plain": [
              "'Linux'"
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          },
          "metadata": {},
          "execution_count": 7
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      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JrUej5wX1sl6"
      },
      "source": [
        "# Retrun process name\n",
        "platform.uname()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "R1CeWBKSEkjD"
      },
      "source": [
        "# **Section 3- Integrated Development Environment (IDE)**<a name='IDE'></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **PyCharm**"
      ],
      "metadata": {
        "id": "CD0TNslfFiI8"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Next up we have PyCharm, this is one of my favorite IDE’s I pretty much use for all of my tutorials. PyCharm is one of the largest IDE’s on this list but it offers a ton of features."
      ],
      "metadata": {
        "id": "52-N0yChFtUu"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "![](https://drive.google.com/uc?export=view&id=1hhsg82AzVSqtlpoSRXRwu77ZkT7yiWxq)"
      ],
      "metadata": {
        "id": "qt685jeGGJ3A"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "One of my favorite things with this IDE is running the code within the environment, this allows us to run line by line or the whole program right in the IDE. On top of this, PyCharm has all of the following features as well:\n",
        "\n",
        "PyCharm is by far one of my favorite IDE’s To download for Python, download it here:\n",
        "\n",
        "https://www.jetbrains.com/pycharm/"
      ],
      "metadata": {
        "id": "zIqdCdTcIMTu"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Visual Studio Code**"
      ],
      "metadata": {
        "id": "ZUwfT1WtIgrS"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "![](https://drive.google.com/uc?export=view&id=1zZ4EeJ--rtxCFIMLWQFKiRp3io4veQT7)"
      ],
      "metadata": {
        "id": "dJiKFFurJT3W"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Next up we have Visual Studio Code, this is a very popular IDE built by Microsoft! This IDE is a multi language interpreter, so you can run code from multiple different languages, one of these languages is Python!"
      ],
      "metadata": {
        "id": "8JdRY0J5Jcfn"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Visual Studio Code is an industry standard used at tons of different companies, so I would totally recommend learning it for sure! This is the link to download this software:\n",
        "\n",
        "https://code.visualstudio.com/"
      ],
      "metadata": {
        "id": "2iY8PBTCJfYK"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "M3R_O-6lEw2Z"
      },
      "source": [
        "![](https://drive.google.com/uc?export=view&id=1NSev_N3lLjUQZ5NFE8Kmm0jJWDfdAA5k)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ok0y6k_3EIQj"
      },
      "source": [
        "##**- Install Jupyter Notebook**\n",
        "in this machine learning project for beginners, we will use Jupyter Notebook for the development. Let’s see steps for the installation and configuration of Jupyter Notebook.\n",
        "\n",
        "Using pip python package manager you can install Jupyter notebook:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pXDOoZn2Ea9x"
      },
      "source": [
        "pip3 install notebook"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e761fj-KEg2I"
      },
      "source": [
        "And that’s it, you have installed jupyter notebook\n",
        "\n",
        "After installing Jupyter notebook you can run the notebook server. To run the notebook, open terminal and type:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M6wAlWSSEvWa"
      },
      "source": [
        "jupyter notebook"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eCskjWPwE3FB"
      },
      "source": [
        "It will start the notebook server at http://localhost:8888\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gYSnZoM86Lxq"
      },
      "source": [
        "!git clone https://github.com/hussain0048/Python.git"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Google CoLab**"
      ],
      "metadata": {
        "id": "8m5woM6-JovL"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "![](https://drive.google.com/uc?export=view&id=1YIY3dgHftHKRyRuNLK3a9OPPnVhLBQTg)"
      ],
      "metadata": {
        "id": "Vw8BekysKhE7"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Finally we have Google CoLab, one of my favorite IDE’s available right now. Google CoLab is a little bit different from the other IDE’s, there are no files to download, nothing to install, everything is ran within your browser!\n",
        "\n",
        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)"
      ],
      "metadata": {
        "id": "3fSKc6DjKos7"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Another massive feature is that you get to have access to Google’s GPU’s for free! This allows you to run your code much faster compared to a CPU! That feature alone makes Google CoLab stand out over the other IDE’s. You can also share your code easily by sending them a link, very similar to sharing a Google Drive file to someone. If you want to learn more about Google CoLab, check out the link down below:\n",
        "\n",
        "https://colab.research.google.com/notebooks/"
      ],
      "metadata": {
        "id": "JSHV8orzK1AM"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Spyder**"
      ],
      "metadata": {
        "id": "SO_H4NoqLAAl"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "![](\n",
        "https://drive.google.com/uc?export=view&id=1bT3Chuyd_NargQLmbh19lv05z47GNb0J)"
      ],
      "metadata": {
        "id": "qqZj5P_JLdJ1"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Starting off we have Spyder, a very powerful IDE specifically tailored for data science. Unlike some other IDE’s on this list, Spyder allows you to turn different languages inside one software, you can also run code line by line, per cell or the whole file!"
      ],
      "metadata": {
        "id": "4t0tNTbkLOvx"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        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)"
      ],
      "metadata": {
        "id": "pL_SaIN7LSHy"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "My 2 favorite things about this IDE are the variable explorer and the plots being plotted straight in the side bar (unlike other IDE’s which print them out differently). Another massive feature about Spyder are the plugins, there are tons of plugins available for this software for a ton of different tasks, if you want to download this IDE check out the link below:\n",
        "\n",
        "https://www.spyder-ide.org/"
      ],
      "metadata": {
        "id": "CBqemMU6LnXm"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "beVu-1UqCAcU"
      },
      "source": [
        "# **Section 4- First Program in Python**<a name='first_program'></a>\n",
        "\n",
        "1.   List item\n",
        "2.   List item\n",
        "\n",
        "\n",
        "The simplest directive in Python is the \"print\" directive - it simply prints out a line (and also includes a newline, unlike in C).For example, one difference between Python 2 and 3 is the print statement. In Python 2, the \"print\" statement is not a function, and therefore it is invoked without parentheses. However, in Python 3, it is a function, and must be invoked with parentheses."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZF03EKpuCAcV"
      },
      "source": [
        "#To print a string in Python 3, just write:\n",
        "print(\"This line will be printed.\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "u7Cy9SPr653c"
      },
      "source": [
        "print(\"Goodbye, World!\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "collapsed": true,
        "id": "nhYP15aoCAcf"
      },
      "source": [
        "# **Section 5-Indentation** <a name='indentation'></a>\n",
        "Python uses indentation for blocks, instead of curly braces. Both tabs and spaces are supported, but the standard indentation requires standard Python code to use four spaces. For example\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "y1wsGi52CAch",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "98258588-7413-41ae-a7fa-9279c275eee8"
      },
      "source": [
        "x = 1\n",
        "if x == 1:\n",
        "    # indented four spaces\n",
        "    print(\"x is 1.\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "x is 1.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zthc85D-kW6k"
      },
      "source": [
        "x = 1\n",
        "if x == 1:"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Section6-Getting User Input**<a name='user_input'></a>\n",
        "\n",
        "1.   List item\n",
        "2.   List item\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "6HlWRwy52klq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Get user input\n",
        "name = input(\"Please enter your name: \")\n",
        "\n",
        "# Greet the user\n",
        "print(f\"Hello, {user_name}! Nice to meet you!\")"
      ],
      "metadata": {
        "id": "mhbDDGM-2zZq"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "P4QYI2IoHWpL"
      },
      "source": [
        "# **Section 7-DataTypes in Python**<a name='data_types_python'></a>\n",
        "Python provides several built-in data types that can be assigned to variables. Each data type has its own characteristics and usage.\n",
        "\n",
        "Let’s explore some of the most commonly used data types in Python:"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "![](https://drive.google.com/uc?export=view&id=1JcCi5V8xSC4ZjPn8oh5icJDtk3XDWHPX)"
      ],
      "metadata": {
        "id": "2mPVkO9A3bUp"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AMaWX5x481qW"
      },
      "source": [
        "## **7.1 Numbers** <a name='numbers'></a>\n",
        "Python supports two types of numbers - integers and floating point numbers. (It also supports complex numbers, which will not be explained in this tutorial).\n",
        "\n",
        "To define an integer, use the following syntax:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HV4itFik94rG",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ff385d41-e4f6-49c4-eb08-1a2053173f62"
      },
      "source": [
        "myint = 7\n",
        "print(myint)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "7\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p9JGZRKCCAcq",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "621c15ce-aa46-4876-df36-75008dc7363d"
      },
      "source": [
        "#To define a floating point number, you may use one of the following notations:\n",
        "myfloat = 7.0\n",
        "print(myfloat)\n",
        "myfloats = float(7)\n",
        "print(myfloats)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "7.0\n",
            "7.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# float variable\n",
        "x = 5.0\n",
        "print (x, type(x))"
      ],
      "metadata": {
        "id": "PG8Q_laJeLFP",
        "outputId": "fa6a4309-838a-4127-b1c7-80c2969843e0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "5.0 <class 'float'>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Integer variable\n",
        "x = 5\n",
        "print (x)\n",
        "print (type(x))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "x2vI8tW2XGWJ",
        "outputId": "29f7e71c-2c83-4463-a3ab-417c9f061e4d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "5\n",
            "<class 'int'>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# int variable\n",
        "x = 5\n",
        "print (x, type(x))"
      ],
      "metadata": {
        "id": "OKfdLMkMeGRv",
        "outputId": "488dfa8e-df58-48b7-b5c4-a04ba1b35e70",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "5 <class 'int'>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# String variable\n",
        "x = \"hello\"\n",
        "print (x)\n",
        "print (type(x))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rk6FVEQqXP6L",
        "outputId": "f3b0e3e7-b81a-468d-8d3a-14c8d2d7f11b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "hello\n",
            "<class 'str'>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# text variable\n",
        "x = \"5\"\n",
        "print (x, type(x))"
      ],
      "metadata": {
        "id": "14bb7JxMeQ9w"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# boolean variable\n",
        "x = True\n",
        "print (x, type(x))"
      ],
      "metadata": {
        "id": "Zu9SKD0eeVRu",
        "outputId": "daf6988f-2208-410d-fe03-77f0940dc9f7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "True <class 'bool'>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yCl8lMKR-WRg"
      },
      "source": [
        "## **7.2- Strings**<a name='string'></a>\n",
        "Strings are defined either with a single quote or a double quotes.The difference between the two is that using double quotes makes it easy to include apostrophes (whereas these would terminate the string if using single quotes)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "t1DlRZn5-m4_"
      },
      "source": [
        "mystring = 'hello'\n",
        "print(mystring)\n",
        "mystring = \"hello\"\n",
        "print(mystring)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "my_string = \"Python is my favorite programming language!\""
      ],
      "metadata": {
        "id": "95rdpaQezxKk"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "my_string"
      ],
      "metadata": {
        "id": "ZfrtqD_lz98M",
        "outputId": "f59dc871-a1e6-4d9c-9429-0daf06ba0592",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Python is my favorite programming language!'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "type(my_string)"
      ],
      "metadata": {
        "id": "IBkKNk5W0Bw6",
        "outputId": "7a3d99dc-96e4-448c-f678-d2ba7c1e73b0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "str"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(my_string)"
      ],
      "metadata": {
        "id": "Y7bVKz360Ff6",
        "outputId": "a4483519-f35b-4c4c-886d-56f4da18172e",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "43"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "str.replace()"
      ],
      "metadata": {
        "id": "NYuY967a0Ml5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "help(str.replace)\n"
      ],
      "metadata": {
        "id": "OWWWWMFb0Ke0",
        "outputId": "e1bbda76-4559-4295-c325-e6dbd556dae2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Help on method_descriptor:\n",
            "\n",
            "replace(self, old, new, count=-1, /)\n",
            "    Return a copy with all occurrences of substring old replaced by new.\n",
            "    \n",
            "      count\n",
            "        Maximum number of occurrences to replace.\n",
            "        -1 (the default value) means replace all occurrences.\n",
            "    \n",
            "    If the optional argument count is given, only the first count occurrences are\n",
            "    replaced.\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "my_string.replace(\"a\", \"?\")\n",
        "print(my_string)"
      ],
      "metadata": {
        "id": "nOjdbetF2jmZ",
        "outputId": "be9aeb83-73de-4105-a835-4a237b443695",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Python is my favorite programming language!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "my_modified_string = my_string.replace(\"is\", \"will be\")\n",
        "print(my_modified_string)"
      ],
      "metadata": {
        "id": "MpuPhLup28Zo",
        "outputId": "a5c9267a-628b-45d6-d00a-f05747311508",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Python will be my favorite programming language!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**str.join()**"
      ],
      "metadata": {
        "id": "9YpxG4Zt4WxQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "pandas = \"pandas\"\n",
        "numpy = \"numpy\"\n",
        "requests = \"requests\"\n",
        "cool_python_libs = \", \".join([pandas, numpy, requests])"
      ],
      "metadata": {
        "id": "qGw1UnMz4crF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(f\"Some cool python libraries: {cool_python_libs}\")\n"
      ],
      "metadata": {
        "id": "KCRdtx1b4hi_",
        "outputId": "d184a536-e38d-4705-e95e-4d0964fd991e",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Some cool python libraries: pandas, numpy, requests\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mixed_case = \"PyTHoN hackER\"\n",
        "mixed_case.upper()\n",
        "mixed_case.lower()\n",
        "mixed_case.title()"
      ],
      "metadata": {
        "id": "MFV1-Xfz5m3Z",
        "outputId": "e9b5cfa8-6796-4d49-d085-0f87699f255c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Python Hacker'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **7.3- Lists** <a name='lists'></a>"
      ],
      "metadata": {
        "id": "ZC7rATSt7W6b"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Create a list of numbers\n",
        "numbers = [1, 2, 3, 4, 5]\n",
        "\n",
        "# Create a list of strings\n",
        "strings = [\"hello\", \"world\", \"python\"]\n",
        "\n",
        "# Create a list of lists\n",
        "nested_list = [[1, 2, 3], [\"a\", \"b\", \"c\"]]\n",
        "# Print the first element in the numbers list\n",
        "print(numbers[0])"
      ],
      "metadata": {
        "id": "oPDJ4pyu7gk1"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **7.4-Tuples**<a name='tuples'></a>\n",
        "\n",
        "---\n",
        "\n"
      ],
      "metadata": {
        "id": "WBCm_0Kl7nsk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Create a tuple of numbers\n",
        "numbers = (1, 2, 3, 4, 5)\n",
        "\n",
        "# Create a tuple of strings\n",
        "strings = (\"hello\", \"world\", \"python\")\n",
        "\n",
        "# Create a tuple of tuples\n",
        "nested_tuple = ((1, 2, 3), (\"a\", \"b\", \"c\"))"
      ],
      "metadata": {
        "id": "rsZlqMK_7uq1"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **7.5- Dictionaries**<a name='dictionaries'></a>"
      ],
      "metadata": {
        "id": "N0bhs9rp77VO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "dict = {\n",
        "  \"name\": \"John Doe\",\n",
        "  \"age\": 30,\n",
        "  \"occupation\": \"Software Engineer\"\n",
        "}"
      ],
      "metadata": {
        "id": "1ZiHP6Xs8BIj"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(dict[\"name\"])"
      ],
      "metadata": {
        "id": "hXT-Npaj8GUm",
        "outputId": "db8e5567-694c-4a10-fb06-d438c8d2df04",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "John Doe\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **7.6 Sets**<a name='sets'></a>"
      ],
      "metadata": {
        "id": "mOV4VfoZ8Lrk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "set1 = {1, 2, 3, 4, 5}"
      ],
      "metadata": {
        "id": "chdKxOXX8Pj0"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "set1.add(6)"
      ],
      "metadata": {
        "id": "tXtICiov8U0s"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "if 3 in set1:\n",
        "  print(\"3 is in the set\")\n"
      ],
      "metadata": {
        "id": "wyL7leqx8Xur"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "izbM6eEUKAV-"
      },
      "source": [
        "# **Section 8-Basic Operators**<a name='basic_operators'></a>\n",
        "This section explains how to use basic operators in Python."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "M_GxDC5VBogz"
      },
      "source": [
        "## **8.1- Arithmetic Operators**<a name='arthimetic_operators'></a>\n",
        "Just as any other programming languages, the addition, subtraction, multiplication, and division operators can be used with numbers."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zt-vctO1Kb3o"
      },
      "source": [
        "number = 1 + 2 * 3 / 4.0\n",
        "print(number)\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Example usage of arithmetic operators\n",
        "number = 1 + 2 * 3 / 4.0\n",
        "print(number)\n",
        "a = 10\n",
        "b = 3\n",
        "addition = a + b\n",
        "subtraction = a - b\n",
        "multiplication = a * b\n",
        "division = a / b\n",
        "modulo = a % b\n",
        "exponentiation = a ** b\n",
        "floor_division = a // b\n",
        "print(addition)         # Output: 13\n",
        "print(subtraction)      # Output: 7\n",
        "print(multiplication)   # Output: 30\n",
        "print(division)         # Output: 3.3333333333333335\n",
        "print(modulo)           # Output: 1\n",
        "print(exponentiation)   # Output: 1000\n",
        "print(floor_division)   # Output: 3"
      ],
      "metadata": {
        "id": "Zqhlhxje0oBa"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YLQMNIDNuMLr",
        "outputId": "122a7f79-67a7-426c-8931-a94b58e75a83",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "print(type(number))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'float'>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xAsBlVQ0DmXi",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "532691f7-5988-45f9-e833-04acb1dea3c0"
      },
      "source": [
        "# Another operator available is the modulo (%) operator, which returns the integer remainder of the division. dividend % divisor = remainder\n",
        "remainder = 11 % 3\n",
        "print(remainder)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lYnhlcS1DtiH"
      },
      "source": [
        "# Using two multiplication symbols makes a power relationship.\n",
        "squared = 7 ** 2\n",
        "cubed = 2 ** 3\n",
        "print(squared)\n",
        "print(cubed)\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **8.2. Comparison Operators**<a name='comparison_operators'></a>"
      ],
      "metadata": {
        "id": "MggNT0761bZB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Example usage of comparison operators\n",
        "a = 5\n",
        "b = 10\n",
        "\n",
        "print(a == b)     # Output: False\n",
        "print(a != b)     # Output: True\n",
        "print(a > b)      # Output: False\n",
        "print(a < b)      # Output: True\n",
        "print(a >= b)     # Output: False\n",
        "print(a <= b)     # Output: True"
      ],
      "metadata": {
        "id": "LO-CAQtZ1l72",
        "outputId": "176d3f74-4af5-46e8-ceeb-e5305cad5083",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "False\n",
            "True\n",
            "False\n",
            "True\n",
            "False\n",
            "True\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "## **8.3-Logical Operators**<a name='logical_operators'></a>"
      ],
      "metadata": {
        "id": "pgMLxMXAi0Ot"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "x = 5\n",
        "y = 10\n",
        "\n",
        "print(x > 0 and y < 20)  # True\n",
        "print(x > 0 or y < 20)   # True\n",
        "print(not(x > 0))        # False"
      ],
      "metadata": {
        "id": "3sdwjz50jSkq",
        "outputId": "87c5c197-2fc6-46c2-bb23-48a4d00b669b",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "True\n",
            "True\n",
            "False\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **8.4-Assignment Operators**<a name='assignment_operators'></a>"
      ],
      "metadata": {
        "id": "lM5XfkkAjZx9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "x = 5\n",
        "x += 3  # Equivalent to x = x + 3\n",
        "print(x)  # Output: 8\n",
        "\n",
        "y = 10\n",
        "y -= 5  # Equivalent to y = y - 5\n",
        "print(y)  # Output: 5"
      ],
      "metadata": {
        "id": "7zLuH78XjflP",
        "outputId": "22ef6d13-05a0-4ede-c4b9-a77298dcd6e2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "8\n",
            "5\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **8.5- Bitwise Operators**<a name='bit_operators'></a>"
      ],
      "metadata": {
        "id": "_XuTFJLeveOO"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "qFTq34My-WRy"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x = 5  # Binary representation: 0101\n",
        "y = 3  # Binary representation: 0011\n",
        "\n",
        "print(x & y)   # Bitwise AND:    0001 (Decimal: 1)\n",
        "print(x | y)   # Bitwise OR:     0111 (Decimal: 7)\n",
        "print(x ^ y)   # Bitwise XOR:    0110 (Decimal: 6)\n",
        "print(~x)      # Bitwise NOT:    -6 (Decimal: -6)\n",
        "print(x << 1)  # Left Shift:     1010 (Decimal: 10)\n",
        "print(x >> 1)  # Right Shift:    0010 (Decimal: 2)"
      ],
      "metadata": {
        "id": "biQiEKjBvqoC"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **8.6-Identity operators**<a name='identify_operators'></a>"
      ],
      "metadata": {
        "id": "amSAQWJFv04D"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Integers (small integers are often stored as singletons)\n",
        "a = 5\n",
        "b = 5\n",
        "print(a is b)  # True (they might share the same memory location)\n",
        "\n",
        "# Strings (immutable, often reused if the same value exists)\n",
        "c = \"hello\"\n",
        "d = \"hello\"\n",
        "print(c is d)  # True (they might share the same memory location)\n",
        "\n",
        "# Lists (mutable, each list has its own memory location)\n",
        "e = [1, 2, 3]\n",
        "f = [1, 2, 3]\n",
        "print(e is f)  # False (even though they have the same values, they are different objects)\n",
        "\n",
        "# Checking with `id()`\n",
        "print(id(a))  # Same for `a` and `b` if they share memory\n",
        "print(id(c))  # Same for `c` and `d` if they share memory\n",
        "print(id(e))  # Different for each `list` object"
      ],
      "metadata": {
        "id": "w_Kp23Pkv_EB",
        "outputId": "d821734b-66b9-496d-ef97-081291220fe5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "True\n",
            "True\n",
            "False\n",
            "133175360586096\n",
            "133175070111984\n",
            "133175067211776\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **8.7-Membership Operators**<a name='member_operators'></a>"
      ],
      "metadata": {
        "id": "unvrP28HwGmk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "my_list = [1, 2, 3, 4]\n",
        "print(2 in my_list)  # True\n",
        "\n",
        "my_string = \"Hello World!\"\n",
        "print(\"lo\" in my_string)  # True\n",
        "\n",
        "my_tuple = (5, 7, 9)\n",
        "print(7 in my_tuple)  # True\n",
        "\n",
        "my_set = {10, 12, 14}\n",
        "print(12 in my_set)  # True\n",
        "\n",
        "my_dict = {\"name\": \"Alice\", \"age\": 30}\n",
        "print(\"Alice\" in my_dict)  # True (checks keys, not values)"
      ],
      "metadata": {
        "id": "d8uyDHDGwQYq",
        "outputId": "b14972aa-c92b-4dc4-f341-aa98da24fc6a",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "True\n",
            "True\n",
            "True\n",
            "True\n",
            "False\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1x8QNZN3CAdF"
      },
      "source": [
        "##**8.8  -Using Operators with Strings** <a name='operators_with_strings'></a>\n",
        "Python supports concatenating strings using the addition operator:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zNBdXxiHLfLW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "fc89c894-c3de-41d0-bc3e-2c56d9219259"
      },
      "source": [
        "helloworld = \"hello\" + \" \" + \"world\"\n",
        "print(helloworld)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "hello world\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RkXFMVZP76K4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "6289712e-da8d-4952-c555-097499b2079b"
      },
      "source": [
        "lotsofhellos = \"hello\" * 10\n",
        "print(lotsofhellos)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "hellohellohellohellohellohellohellohellohellohello\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "12f__4N3FDY3"
      },
      "source": [
        "## **8.9- Using Operators with Lists**<a name='operators_with_lists'></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FZWfCifvFTXC"
      },
      "source": [
        "even_numbers = [2,4,6,8]\n",
        "odd_numbers = [1,3,5,7]\n",
        "all_numbers = odd_numbers + even_numbers\n",
        "print(all_numbers)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ss60eiRpFln5"
      },
      "source": [
        "# Just as in strings, Python supports forming new lists with a repeating sequence using the multiplication operator:\n",
        "print([1,2,3] * 3)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **9- String**<a name='str'></a>"
      ],
      "metadata": {
        "id": "sW14pgzoJapn"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-WNB53OY8IfG"
      },
      "source": [
        "## **9.1-- String Formatting** <a name='str_format'></a>\n",
        "\n",
        "Python uses C-style string formatting to create new, formatted strings. The \"%\" operator is used to format a set of variables enclosed in a \"tuple\" (a fixed size list), together with a format string, which contains normal text together with \"argument specifiers\", special symbols like \"%s\" and \"%d\".\n",
        "\n",
        "Let's say you have a variable called \"name\" with your user name in it, and you would then like to print(out a greeting to that user.)\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-_ykAt_v8egH",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7aed1a81-a4f6-43d4-e64c-2a04c37cb12b"
      },
      "source": [
        "# This prints out \"Hello, John!\"\n",
        "name = \"John\"\n",
        "print(\"Hello, %s!\" % name)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Hello, John!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OcoimUu1s4MI"
      },
      "source": [
        "To use two or more argument specifiers, use a tuple (parentheses):"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0tyfd8avhp58",
        "outputId": "213f082a-6f95-4364-cdef-c6e36cc417b3",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# This prints out \"John is 23 years old.\"\n",
        "name = \"John\"\n",
        "age = 23\n",
        "print(\"%s is %d years old.\" % (name, age))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "John is 23 years old.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "l3epbWLyh-p4"
      },
      "source": [
        "Any object which is not a string can be formatted using the %s operator as well. The string which returns from the \"repr\" method of that object is formatted as the string. For example"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T-QKZojviCCq",
        "outputId": "0384af99-e6b1-4d11-ed8e-5ca5607bb5b9",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# This prints out: A list: [1, 2, 3]\n",
        "mylist = [1,2,3]\n",
        "print(\"A list: %s\" % mylist)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "A list: [1, 2, 3]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "htcsGPA0iMJn"
      },
      "source": [
        "Here are some basic argument specifiers you should know:\n",
        "\n",
        "%s - String (or any object with a string representation, like numbers)\n",
        "\n",
        "%d - Integers\n",
        "\n",
        "%f - Floating point numbers\n",
        "\n",
        "%.<number of digits>f - Floating point numbers with a fixed amount of digits to the right of the dot.\n",
        "\n",
        "%x/%X - Integers in hex representation (lowercase/uppercase)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BdpTOYOlCAdP"
      },
      "source": [
        "##**9.2--Basic String Operations**<a name='string_operations'></a>\n",
        "Strings are bits of text. They can be defined as anything between quotes:\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "R5uHKjQWZ0WV"
      },
      "source": [
        "astring = \"Hello world!\"\n",
        "astring2 = 'Hello world!'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "r_VGeM-W6ADp"
      },
      "source": [
        "As you can see, the first thing you learned was printing a simple sentence. This sentence was stored by Python as a string. However, instead of immediately printing strings out, we will explore the various things you can do to them. You can also use single quotes to assign a string. However, you will face problems if the value to be assigned itself contains single quotes.For example to assign the string in these bracket(single quotes are ' ') you need to use double quotes only like this"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RP9VUw8v6CKq",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a7945590-ef03-45f9-a6aa-c003d52c411b"
      },
      "source": [
        "astring = \"Hello world!\"\n",
        "print(\"single quotes are ' '\")\n",
        "print(len(astring))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "single quotes are ' '\n",
            "12\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kMZsbrdxMsk_",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8d48b4a5-f743-4b3c-95e3-d9317eb1ac67"
      },
      "source": [
        "astring = \"Hello world!\"\n",
        "print(astring.index(\"o\"))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "4\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jib_dHP4MnL8"
      },
      "source": [
        "That prints out 4, because the location of the first occurrence of the letter \"o\" is 4 characters away from the first character. Notice how there are actually two o's in the phrase - this method only recognizes the first.\n",
        "\n",
        "But why didn't it print out 5? Isn't \"o\" the fifth character in the string? To make things more simple, Python (and most other programming languages) start things at 0 instead of 1. So the index of \"o\" is 4."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_VZPHeAVM7W-",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f994af23-4e2d-44ee-ebbc-56af0ba6844b"
      },
      "source": [
        "astring = \"Hello world!\"\n",
        "print(astring.count(\"H\"))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vJuKccPBNkDH"
      },
      "source": [
        "For those of you using silly fonts, that is a lowercase L, not a number one. This counts the number of l's in the string. Therefore, it should print 3."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zntMPysON5Ts",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "bb1f7992-fb64-4424-93dc-a37ac6da650b"
      },
      "source": [
        "astring = \"Hello world!\"\n",
        "print(astring[3:7])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "lo w\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EHo45-BfN-wE"
      },
      "source": [
        "This prints a slice of the string, starting at index 3, and ending at index 6. But why 6 and not 7? Again, most programming languages do this - it makes doing math inside those brackets easier.\n",
        "\n",
        "If you just have one number in the brackets, it will give you the single character at that index. If you leave out the first number but keep the colon, it will give you a slice from the start to the number you left in. If you leave out the second number, it will give you a slice from the first number to the end.\n",
        "\n",
        "You can even put negative numbers inside the brackets. They are an easy way of starting at the end of the string instead of the beginning. This way, -3 means \"3rd character from the end\"."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f2fVOhDtOOVj",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cc819a08-5618-4468-f913-d2433966a98e"
      },
      "source": [
        "astring = \"Hello world!\"\n",
        "print(astring[3:7:2])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "l \n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9JPolHSEOSqH"
      },
      "source": [
        "This prints the characters of string from 3 to 7 skipping one character. This is extended slice syntax. The general form is [start:stop:step]."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1m8tU3n8OdSk",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e4a70667-9f16-4e53-9e7a-e92805356959"
      },
      "source": [
        "astring = \"Hello world!\"\n",
        "print(astring[3:7])\n",
        "print(astring[3:7:1])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "lo w\n",
            "lo w\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZQp54I1kOneQ"
      },
      "source": [
        "Note that both of them produce same output\n",
        "\n",
        "There is no function like strrev in C to reverse a string. But with the above mentioned type of slice syntax you can easily reverse a string like this"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_4BaWsS0Osab",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9fb9ffc8-24cf-4f2b-81e3-87399344e276"
      },
      "source": [
        "astring = \"Hello world!\"\n",
        "print(astring[::-1])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "!dlrow olleH\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UXGsuQmhO1ND",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "149919ad-6383-4712-ce30-619e5d37759b"
      },
      "source": [
        "astring = \"Hello world!\"\n",
        "print(astring.upper())\n",
        "print(astring.lower())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "HELLO WORLD!\n",
            "hello world!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0AFCFOpXO_Cr"
      },
      "source": [
        "hese make a new string with all letters converted to uppercase and lowercase, respectively."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yQGbPPncPA30",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "95ccab41-877d-4f64-e530-3c7c07e3b5d7"
      },
      "source": [
        "astring = \"Hello world!\"\n",
        "print(astring.startswith(\"Hello\"))\n",
        "print(astring.endswith(\"asdfasdfasdf\"))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "True\n",
            "False\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "v5Rg7hGqPNMO"
      },
      "source": [
        "This is used to determine whether the string starts with something or ends with something, respectively. The first one will print True, as the string starts with \"Hello\". The second one will print False, as the string certainly does not end with \"asdfasdfasdf\""
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bLLTo7DRPBIT"
      },
      "source": [
        "astring = \"Hello world!\"\n",
        "afewwords = astring.split(\" \")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LTX2uBXKPZUx"
      },
      "source": [
        "This splits the string into a bunch of strings grouped together in a list. Since this example splits at a space, the first item in the list will be \"Hello\", and the second will be \"world!\"."
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **9.3-- Concatenation**"
      ],
      "metadata": {
        "id": "wqXCDYgUBCDc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "name = \"John\"\n",
        "greeting = \"Hello,\" + name + \"!\"\n",
        "print(greeting)  # Output: Hello, John!\n",
        "# Using str.join() method\n",
        "languages = ['Python', 'Java', 'C++']\n",
        "joined_string = ','.join(languages)\n",
        "print(joined_string)  # Output: Python, Java, C++"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "B3RWhqriBH1L",
        "outputId": "464a0ecc-b9cd-4936-9d1d-7ecf92aa70e4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Hello,John!\n",
            "Python,Java,C++\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        " **String Length**"
      ],
      "metadata": {
        "id": "D-nroeGRCK1J"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "message = \"Hello, World!\"\n",
        "length = len(message)\n",
        "print(length)  # Output: 13"
      ],
      "metadata": {
        "id": "BAh57_3kCNOS",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "31642048-3bdf-4c1f-cd7c-58cdec0845c1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "13\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Accessing Characters**"
      ],
      "metadata": {
        "id": "Mj6-Ls2cCeZa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "message = \"Hello, World!\"\n",
        "first_char = message[0]\n",
        "last_char = message[-1]\n",
        "print(first_char)  # Output: H\n",
        "print(last_char)  # Output: !"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "E2abRWs3Ckra",
        "outputId": "e7f7b234-957b-41dd-db46-9b53d6699639"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "H\n",
            "!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**String Slicing**"
      ],
      "metadata": {
        "id": "FOHLmigkWI2d"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "message = \"Hello, World!\"\n",
        "slice = message[7:12]\n",
        "print(slice)  # Output: World"
      ],
      "metadata": {
        "id": "MLl5iagcWK6y",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "908a1ec3-b2c6-4ae2-e14f-737776fe9899"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "World\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lTe0Qqi3CAeA"
      },
      "source": [
        "# **10- Conditions Statements**<a name='conditional_statement'></a>\n",
        "Python uses boolean variables to evaluate conditions. The boolean values True and False are returned when an expression is compared or evaluated. For example:"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x = 10\n",
        "if x > 0:\n",
        " print(\"x is positive\")\n",
        "elif x < 0:\n",
        " print(\"x is negative\")\n",
        "else:\n",
        " print(\"x is zero\")"
      ],
      "metadata": {
        "id": "DKjS9wGui_Ea",
        "outputId": "986855f2-182c-4c9d-e8e0-bf60be20566e",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "x is positive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **10.1-if statement**<a name='if_statement'></a>"
      ],
      "metadata": {
        "id": "LZZhzR0mWQ29"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# if statement\n",
        "i = 10\n",
        "if i>5:\n",
        "    print('i is greater than 5..')"
      ],
      "metadata": {
        "id": "KWc49KnBWkEQ",
        "outputId": "deb02a93-346a-4f57-ffe5-5cc5692661d0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "i is greater than 5..\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **10.2-if-else statement**<a name='if_else_statement'></a>"
      ],
      "metadata": {
        "id": "kz58hLJAWrdE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "i = 1\n",
        "if i>5:\n",
        "    print('i is greater than 5..')\n",
        "else:\n",
        "    print('i is less than 5')"
      ],
      "metadata": {
        "id": "cEGbmnchWxuf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **10.3-if-elif-else statement**<a name='if_elif_else_statement'></a>"
      ],
      "metadata": {
        "id": "SU2caGFgW0Wb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "i = 10\n",
        "if i==5:\n",
        "    print('i is equal 5..')\n",
        "elif i==10:\n",
        "    print('i is equal 10..')\n",
        "else:\n",
        "    print('i is other..')"
      ],
      "metadata": {
        "id": "HYkHjqKUW-PP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **10.4-if-elif-else statement** <a name='if_elif_else_statement'></a>"
      ],
      "metadata": {
        "id": "96s0_V2PYzzC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "i = 10\n",
        "if i==5:\n",
        "    print('i is equal 5..')\n",
        "elif i==10:\n",
        "    print('i is equal 10..')\n",
        "else:\n",
        "    print('i is other..')"
      ],
      "metadata": {
        "id": "uUUa5zSsY8Ws",
        "outputId": "2a98ca07-4159-4fb3-8b05-6c09f0b57f50",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "i is equal 10..\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **10.5-Nested-if statements:**<a name='nested_if_statement'></a>"
      ],
      "metadata": {
        "id": "IKtmVxLUZCB5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Program to determine a student's grade based on their marks\n",
        "\n",
        "marks = int(input(\"Enter the student's marks: \"))\n",
        "\n",
        "if marks >= 90:\n",
        "    grade = 'A'\n",
        "    if marks >= 95:\n",
        "        distinction = True\n",
        "    else:\n",
        "        distinction = False\n",
        "elif marks >= 80:\n",
        "    grade = 'B'\n",
        "    distinction = False\n",
        "elif marks >= 70:\n",
        "    grade = 'C'\n",
        "    distinction = False\n",
        "elif marks >= 60:\n",
        "    grade = 'D'\n",
        "    distinction = False\n",
        "else:\n",
        "    grade = 'F'\n",
        "    distinction = False\n",
        "\n",
        "print(\"Grade:\", grade)\n",
        "\n",
        "if distinction:\n",
        "    print(\"Distinction achieved!\")"
      ],
      "metadata": {
        "id": "Urhq2IZZZMhn",
        "outputId": "d0e7f108-2d03-4b29-c1ab-b6f7beab45b7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Enter the student's marks: 34\n",
            "Grade: F\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **10.6-Short hand if statement**:<a name='if_short_hand'></a>"
      ],
      "metadata": {
        "id": "B1hLthVkZUZC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Short hand if statement\n",
        "\n",
        "i = 10\n",
        "if i<15: print('i less than 15..')"
      ],
      "metadata": {
        "id": "YF-o2Ag3ZcG1",
        "outputId": "2ddd9049-e4bd-46ed-e663-99df25b57345",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "i less than 15..\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Short hand if-else statement\n",
        "\n",
        "i = 10\n",
        "print(True) if i==10 else print(False)"
      ],
      "metadata": {
        "id": "19706DMIZf_e",
        "outputId": "7f9b5041-9e34-4a61-d2ff-de3933305818",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "True\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# match-case statement\n",
        "\n",
        "flag = int(input('Enter num: '))\n",
        "\n",
        "match flag:\n",
        "    case 5 :\n",
        "        print('Flag = 5')\n",
        "    case 10 :\n",
        "        print('Flag = 10')\n",
        "    case 15 :\n",
        "        print('Flag = 15')\n",
        "    case 20 :\n",
        "        print('Flag = 20')\n",
        "    case _ :\n",
        "        print('Not matched')"
      ],
      "metadata": {
        "id": "NOamv8jgZkDX",
        "outputId": "ea7c6e08-4544-4793-9927-ef0057ff975e",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Enter num: 4\n",
            "Not matched\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **10.7-Indentation**<a name='indent'></a>"
      ],
      "metadata": {
        "id": "o16dAHuXjSUM"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "password = input(\"Please type in a password: \")\n",
        "\n",
        "if password == \"kittycat\":\n",
        "    print(\"You knew the password!\")\n",
        "    print(\"You must be either the intended user...\")\n",
        "    print(\"...or quite an accomplished hacker.\")\n",
        "\n",
        "print(\"The program has finished its execution. Thanks and bye!\")"
      ],
      "metadata": {
        "id": "s_5YEMtmjgUW",
        "outputId": "a3474f87-397a-47b3-be58-2e440a6b5e18",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Please type in a password: kittycat\n",
            "You knew the password!\n",
            "You must be either the intended user...\n",
            "...or quite an accomplished hacker.\n",
            "The program has finished its execution. Thanks and bye!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Kq4Ho1l8Ksjt"
      },
      "source": [
        "x = 2\n",
        "print(x == 2) # prints out True\n",
        "print(x == 3) # prints out False\n",
        "print(x < 3) # prints out True\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "t_FZLht0akQz"
      },
      "source": [
        "Notice that variable assignment is done using a single equals operator \"=\", whereas comparison between two variables is done using the double equals operator \"==\". The \"not equals\" operator is marked as \"!=\"."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-VwPfoQSS4Av"
      },
      "source": [
        "## **10.8 - Boolean operators** <a name='boolean_operators'></a>\n",
        "The \"and\" and \"or\" boolean operators allow building complex boolean expressions, for example:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5DYf8Quv_PxR"
      },
      "source": [
        "name = \"John\"\n",
        "age = 23\n",
        "if name == \"John\" and age == 23:\n",
        "    print(\"Your name is John, and you are also 23 years old.\")\n",
        "\n",
        "if name == \"John\" or name == \"Rick\":\n",
        "    print(\"Your name is either John or Rick.\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qrZx-6XeziR0"
      },
      "source": [
        "## **10.9 The \"in\" operator**<a name='in_operator'></a>\n",
        "The \"in\" operator could be used to check if a specified object exists within an iterable object container, such as a list:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_q87nKz4zxr1"
      },
      "source": [
        "name = \"John\"\n",
        "if name in [\"John\", \"Rick\"]:\n",
        "    print(\"Your name is either John or Rick.\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jnWR24dBHGty"
      },
      "source": [
        "Python uses indentation to define code blocks, instead of brackets. The standard Python indentation is 4 spaces, although tabs and any other space size will work, as long as it is consistent. Notice that code blocks do not need any termination.\n",
        "\n",
        "Here is an example for using Python's \"if\" statement using code blocks:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YzkWkVZEbrpw"
      },
      "source": [
        "statement = False\n",
        "another_statement = True\n",
        "if statement is True:\n",
        "    # do something\n",
        "    pass\n",
        "elif another_statement is True: # else if\n",
        "    # do something else\n",
        "    pass\n",
        "else:\n",
        "    # do another thing\n",
        "    pass"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "03BGhfi0b5Tx"
      },
      "source": [
        "x = 2\n",
        "if x == 2:\n",
        "    print(\"x equals two!\")\n",
        "else:\n",
        "    print(\"x does not equal to two.\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3BFbDJjCcACN"
      },
      "source": [
        "A statement is evaulated as true if one of the following is correct: 1. The \"True\" boolean variable is given, or calculated using an expression, such as an arithmetic comparison. 2. An object which is not considered \"empty\" is passed.\n",
        "\n",
        "Here are some examples for objects which are considered as empty: 1. An empty string: \"\" 2. An empty list: [] 3. The number zero: 0 4. The false boolean variable: False"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_Sq0XpVN0UZ7"
      },
      "source": [
        "## **10.10 The 'is' operator**<a name='is_operator'></a>\n",
        "Unlike the double equals operator \"==\", the \"is\" operator does not match the values of the variables, but the instances themselves. For example:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YQ2nyHRV0dnH",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        },
        "outputId": "1c2b114f-7e56-4595-f427-abe0ac6540af"
      },
      "source": [
        "x = [1,2,3]\n",
        "y = [1,2,3]\n",
        "print(x == y) # Prints out True\n",
        "print(x is y) # Prints out False"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "True\n",
            "False\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tuCqDl8Ojb71"
      },
      "source": [
        "## **10.11-The \"not\" operator**<a name='not_operator'></a>\n",
        "Using \"not\" before a boolean expression inverts it:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AEhV6wPLjxKW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        },
        "outputId": "719d1f6a-47cf-4fd3-f6f3-313507dd02b6"
      },
      "source": [
        "print(not False) # Prints out True\n",
        "print((not False) == (False)) # Prints out False"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "True\n",
            "False\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NSfAbkM9j9n0"
      },
      "source": [
        "#**11-Loops**<a name='loops'></a>\n",
        "There are two types of loops in Python.\n",
        "\n",
        " **For Loop** and **While Loop**."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CQw5qCkwkQtl"
      },
      "source": [
        "## **11.1- For Loops**<a name='for_loop'></a>\n",
        "For loops iterate over a given sequence. Here is an example [1]"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fruits = [\"apple\", \"banana\", \"cherry\"]\n",
        "for fruit in fruits:\n",
        " print(fruit)"
      ],
      "metadata": {
        "id": "FE4Q4IbTHeMZ",
        "outputId": "69bdaab7-eed7-43ab-b497-2e073cd59cba",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "apple\n",
            "banana\n",
            "cherry\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yXE0z8LTkh_n",
        "outputId": "cd99945c-5631-4f1c-d0fa-80be21017438",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "primes = [2, 3, 5, 7]\n",
        "for prime in primes:\n",
        "    print(prime)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2\n",
            "3\n",
            "5\n",
            "7\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Jk7_uCXBk2p8"
      },
      "source": [
        "For loops can iterate over a sequence of numbers using the \"range\" and \"xrange\" functions. The difference between range and xrange is that the range function returns a new list with numbers of that specified range, whereas xrange returns an iterator, which is more efficient. (Python 3 uses the range function, which acts like xrange). Note that the range function is zero based[1]"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "75rKveONk5uR",
        "outputId": "6d0f5c6f-3584-4aa9-ed47-fd7d38695ea5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# Prints out the numbers 0,1,2,3,4\n",
        "for x in range(5):\n",
        "    print(x)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0\n",
            "1\n",
            "2\n",
            "3\n",
            "4\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZAVayvJGlJTf",
        "outputId": "7b923799-414a-4580-f295-2eabdfb9bd8f",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# Prints out 3,4,5\n",
        "for x in range(3, 6):\n",
        "    print(x)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "3\n",
            "4\n",
            "5\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ob6Xmq2olPbP"
      },
      "source": [
        "# Prints out 3,5,7\n",
        "for x in range(3, 8, 2):\n",
        "    print(x)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "z92vvofurd8i"
      },
      "source": [
        "## **11.2 \"while\" loops**<a name='while_loop'></a>\n",
        "While loops repeat as long as a certain boolean condition is met. For example:\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xWy8CNotruT-",
        "outputId": "7ebbf654-855c-4f13-8299-2714a9719714",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# Prints out 0,1,2,3,4\n",
        "count = 0\n",
        "while count < 5:\n",
        "    print(count)\n",
        "    count += 1  # This is the same as count = count + 1"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0\n",
            "1\n",
            "2\n",
            "3\n",
            "4\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# While loop\n",
        "count = 1\n",
        "while count<5:\n",
        "    print(count)\n",
        "    count += 1"
      ],
      "metadata": {
        "id": "r3u-YIHUHtVH",
        "outputId": "145257ac-444e-4ed8-b1d2-83c29b11dbc6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1\n",
            "2\n",
            "3\n",
            "4\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# While loop with else block\n",
        "count = 1\n",
        "while count<5:\n",
        "    print(count)\n",
        "    count += 1\n",
        "else:\n",
        "    print('End of else')"
      ],
      "metadata": {
        "id": "WYLz95CDHzhG",
        "outputId": "81648673-8fef-4559-bfc1-5e553610f095",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1\n",
            "2\n",
            "3\n",
            "4\n",
            "End of else\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Infinite While Loop\n",
        "count = 1\n",
        "while True:\n",
        "    print(count, end=' ')\n",
        "    count += 1"
      ],
      "metadata": {
        "id": "YFszZNXMH3f-",
        "outputId": "5c98137c-52d5-40c0-ee0f-30418e7a3905",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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84218 84219 84220 84221 84222 84223 84224 84225 84226 84227 "
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "ERROR:root:Internal Python error in the inspect module.\n",
            "Below is the traceback from this internal error.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 3553, in run_code\n",
            "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
            "  File \"<ipython-input-8-3ff67e744096>\", line 4, in <cell line: 3>\n",
            "    print(count, end=' ')\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/ipykernel/iostream.py\", line 402, in write\n",
            "    self.pub_thread.schedule(lambda : self._buffer.write(string))\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/ipykernel/iostream.py\", line 203, in schedule\n",
            "    self._event_pipe.send(b'')\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/zmq/sugar/socket.py\", line 618, in send\n",
            "    return super().send(data, flags=flags, copy=copy, track=track)\n",
            "  File \"zmq/backend/cython/socket.pyx\", line 740, in zmq.backend.cython.socket.Socket.send\n",
            "  File \"zmq/backend/cython/socket.pyx\", line 787, in zmq.backend.cython.socket.Socket.send\n",
            "  File \"zmq/backend/cython/socket.pyx\", line 244, in zmq.backend.cython.socket._send_copy\n",
            "  File \"zmq/backend/cython/checkrc.pxd\", line 13, in zmq.backend.cython.checkrc._check_rc\n",
            "KeyboardInterrupt\n",
            "\n",
            "During handling of the above exception, another exception occurred:\n",
            "\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 2099, in showtraceback\n",
            "    stb = value._render_traceback_()\n",
            "AttributeError: 'KeyboardInterrupt' object has no attribute '_render_traceback_'\n",
            "\n",
            "During handling of the above exception, another exception occurred:\n",
            "\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\", line 1101, in get_records\n",
            "    return _fixed_getinnerframes(etb, number_of_lines_of_context, tb_offset)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\", line 248, in wrapped\n",
            "    return f(*args, **kwargs)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\", line 281, in _fixed_getinnerframes\n",
            "    records = fix_frame_records_filenames(inspect.getinnerframes(etb, context))\n",
            "  File \"/usr/lib/python3.10/inspect.py\", line 1662, in getinnerframes\n",
            "    frameinfo = (tb.tb_frame,) + getframeinfo(tb, context)\n",
            "  File \"/usr/lib/python3.10/inspect.py\", line 1620, in getframeinfo\n",
            "    filename = getsourcefile(frame) or getfile(frame)\n",
            "  File \"/usr/lib/python3.10/inspect.py\", line 829, in getsourcefile\n",
            "    module = getmodule(object, filename)\n",
            "  File \"/usr/lib/python3.10/inspect.py\", line 875, in getmodule\n",
            "    f = getabsfile(module)\n",
            "  File \"/usr/lib/python3.10/inspect.py\", line 844, in getabsfile\n",
            "    _filename = getsourcefile(object) or getfile(object)\n",
            "  File \"/usr/lib/python3.10/inspect.py\", line 826, in getsourcefile\n",
            "    if os.path.exists(filename):\n",
            "  File \"/usr/lib/python3.10/genericpath.py\", line 19, in exists\n",
            "    os.stat(path)\n",
            "KeyboardInterrupt\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "ERROR:root:Internal Python error in the inspect module.\n",
            "Below is the traceback from this internal error.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 3553, in run_code\n",
            "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
            "  File \"<ipython-input-8-3ff67e744096>\", line 4, in <cell line: 3>\n",
            "    print(count, end=' ')\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/ipykernel/iostream.py\", line 402, in write\n",
            "    self.pub_thread.schedule(lambda : self._buffer.write(string))\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/ipykernel/iostream.py\", line 203, in schedule\n",
            "    self._event_pipe.send(b'')\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/zmq/sugar/socket.py\", line 618, in send\n",
            "    return super().send(data, flags=flags, copy=copy, track=track)\n",
            "  File \"zmq/backend/cython/socket.pyx\", line 740, in zmq.backend.cython.socket.Socket.send\n",
            "  File \"zmq/backend/cython/socket.pyx\", line 787, in zmq.backend.cython.socket.Socket.send\n",
            "  File \"zmq/backend/cython/socket.pyx\", line 244, in zmq.backend.cython.socket._send_copy\n",
            "  File \"zmq/backend/cython/checkrc.pxd\", line 13, in zmq.backend.cython.checkrc._check_rc\n",
            "KeyboardInterrupt\n",
            "\n",
            "During handling of the above exception, another exception occurred:\n",
            "\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 2099, in showtraceback\n",
            "    stb = value._render_traceback_()\n",
            "AttributeError: 'KeyboardInterrupt' object has no attribute '_render_traceback_'\n",
            "\n",
            "During handling of the above exception, another exception occurred:\n",
            "\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 3473, in run_ast_nodes\n",
            "    if (await self.run_code(code, result,  async_=asy)):\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 3575, in run_code\n",
            "    self.showtraceback(running_compiled_code=True)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 2101, in showtraceback\n",
            "    stb = self.InteractiveTB.structured_traceback(etype,\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\", line 1367, in structured_traceback\n",
            "    return FormattedTB.structured_traceback(\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\", line 1267, in structured_traceback\n",
            "    return VerboseTB.structured_traceback(\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\", line 1124, in structured_traceback\n",
            "    formatted_exception = self.format_exception_as_a_whole(etype, evalue, etb, number_of_lines_of_context,\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\", line 1082, in format_exception_as_a_whole\n",
            "    last_unique, recursion_repeat = find_recursion(orig_etype, evalue, records)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\", line 382, in find_recursion\n",
            "    return len(records), 0\n",
            "TypeError: object of type 'NoneType' has no len()\n",
            "\n",
            "During handling of the above exception, another exception occurred:\n",
            "\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 2099, in showtraceback\n",
            "    stb = value._render_traceback_()\n",
            "AttributeError: 'TypeError' object has no attribute '_render_traceback_'\n",
            "\n",
            "During handling of the above exception, another exception occurred:\n",
            "\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\", line 1101, in get_records\n",
            "    return _fixed_getinnerframes(etb, number_of_lines_of_context, tb_offset)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\", line 248, in wrapped\n",
            "    return f(*args, **kwargs)\n",
            "  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\", line 281, in _fixed_getinnerframes\n",
            "    records = fix_frame_records_filenames(inspect.getinnerframes(etb, context))\n",
            "  File \"/usr/lib/python3.10/inspect.py\", line 1662, in getinnerframes\n",
            "    frameinfo = (tb.tb_frame,) + getframeinfo(tb, context)\n",
            "  File \"/usr/lib/python3.10/inspect.py\", line 1620, in getframeinfo\n",
            "    filename = getsourcefile(frame) or getfile(frame)\n",
            "  File \"/usr/lib/python3.10/inspect.py\", line 829, in getsourcefile\n",
            "    module = getmodule(object, filename)\n",
            "  File \"/usr/lib/python3.10/inspect.py\", line 878, in getmodule\n",
            "    os.path.realpath(f)] = module.__name__\n",
            "  File \"/usr/lib/python3.10/posixpath.py\", line 396, in realpath\n",
            "    path, ok = _joinrealpath(filename[:0], filename, strict, {})\n",
            "  File \"/usr/lib/python3.10/posixpath.py\", line 431, in _joinrealpath\n",
            "    st = os.lstat(newpath)\n",
            "KeyboardInterrupt\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "TypeError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
            "    \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n",
            "\u001b[0;32m<ipython-input-8-3ff67e744096>\u001b[0m in \u001b[0;36m<cell line: 3>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;32mwhile\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcount\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mend\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m' '\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m     \u001b[0mcount\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/ipykernel/iostream.py\u001b[0m in \u001b[0;36mwrite\u001b[0;34m(self, string)\u001b[0m\n\u001b[1;32m    401\u001b[0m             \u001b[0;31m# only touch the buffer in the IO thread to avoid races\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 402\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpub_thread\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mschedule\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0;34m:\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_buffer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstring\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    403\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mis_child\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/ipykernel/iostream.py\u001b[0m in \u001b[0;36mschedule\u001b[0;34m(self, f)\u001b[0m\n\u001b[1;32m    202\u001b[0m             \u001b[0;31m# wake event thread (message content is ignored)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 203\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_event_pipe\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mb''\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    204\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/zmq/sugar/socket.py\u001b[0m in \u001b[0;36msend\u001b[0;34m(self, data, flags, copy, track, routing_id, group)\u001b[0m\n\u001b[1;32m    617\u001b[0m             \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroup\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgroup\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 618\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflags\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mflags\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtrack\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtrack\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    619\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32mzmq/backend/cython/socket.pyx\u001b[0m in \u001b[0;36mzmq.backend.cython.socket.Socket.send\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32mzmq/backend/cython/socket.pyx\u001b[0m in \u001b[0;36mzmq.backend.cython.socket.Socket.send\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32mzmq/backend/cython/socket.pyx\u001b[0m in \u001b[0;36mzmq.backend.cython.socket._send_copy\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/zmq/backend/cython/checkrc.pxd\u001b[0m in \u001b[0;36mzmq.backend.cython.checkrc._check_rc\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m: ",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mshowtraceback\u001b[0;34m(self, exc_tuple, filename, tb_offset, exception_only, running_compiled_code)\u001b[0m\n\u001b[1;32m   2098\u001b[0m                         \u001b[0;31m# in the engines. This should return a list of strings.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2099\u001b[0;31m                         \u001b[0mstb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_render_traceback_\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2100\u001b[0m                     \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mAttributeError\u001b[0m: 'KeyboardInterrupt' object has no attribute '_render_traceback_'",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mrun_ast_nodes\u001b[0;34m(self, nodelist, cell_name, interactivity, compiler, result)\u001b[0m\n\u001b[1;32m   3472\u001b[0m                         \u001b[0masy\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcompare\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcode\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3473\u001b[0;31m                     \u001b[0;32mif\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;32mawait\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_code\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m,\u001b[0m  \u001b[0masync_\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0masy\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3474\u001b[0m                         \u001b[0;32mreturn\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "    \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mshowtraceback\u001b[0;34m(self, exc_tuple, filename, tb_offset, exception_only, running_compiled_code)\u001b[0m\n\u001b[1;32m   2100\u001b[0m                     \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2101\u001b[0;31m                         stb = self.InteractiveTB.structured_traceback(etype,\n\u001b[0m\u001b[1;32m   2102\u001b[0m                                             value, tb, tb_offset=tb_offset)\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mstructured_traceback\u001b[0;34m(self, etype, value, tb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m   1366\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtb\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1367\u001b[0;31m         return FormattedTB.structured_traceback(\n\u001b[0m\u001b[1;32m   1368\u001b[0m             self, etype, value, tb, tb_offset, number_of_lines_of_context)\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mstructured_traceback\u001b[0;34m(self, etype, value, tb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m   1266\u001b[0m             \u001b[0;31m# Verbose modes need a full traceback\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1267\u001b[0;31m             return VerboseTB.structured_traceback(\n\u001b[0m\u001b[1;32m   1268\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0metype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtb_offset\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnumber_of_lines_of_context\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mstructured_traceback\u001b[0;34m(self, etype, evalue, etb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m   1123\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1124\u001b[0;31m         formatted_exception = self.format_exception_as_a_whole(etype, evalue, etb, number_of_lines_of_context,\n\u001b[0m\u001b[1;32m   1125\u001b[0m                                                                tb_offset)\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mformat_exception_as_a_whole\u001b[0;34m(self, etype, evalue, etb, number_of_lines_of_context, tb_offset)\u001b[0m\n\u001b[1;32m   1081\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1082\u001b[0;31m         \u001b[0mlast_unique\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrecursion_repeat\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfind_recursion\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0morig_etype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mevalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrecords\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1083\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mfind_recursion\u001b[0;34m(etype, value, records)\u001b[0m\n\u001b[1;32m    381\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mis_recursion_error\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0metype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrecords\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 382\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrecords\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    383\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mTypeError\u001b[0m: object of type 'NoneType' has no len()",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mshowtraceback\u001b[0;34m(self, exc_tuple, filename, tb_offset, exception_only, running_compiled_code)\u001b[0m\n\u001b[1;32m   2098\u001b[0m                         \u001b[0;31m# in the engines. This should return a list of strings.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2099\u001b[0;31m                         \u001b[0mstb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_render_traceback_\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2100\u001b[0m                     \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mAttributeError\u001b[0m: 'TypeError' object has no attribute '_render_traceback_'",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/async_helpers.py\u001b[0m in \u001b[0;36m_pseudo_sync_runner\u001b[0;34m(coro)\u001b[0m\n\u001b[1;32m     76\u001b[0m     \"\"\"\n\u001b[1;32m     77\u001b[0m     \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 78\u001b[0;31m         \u001b[0mcoro\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     79\u001b[0m     \u001b[0;32mexcept\u001b[0m \u001b[0mStopIteration\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     80\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mrun_cell_async\u001b[0;34m(self, raw_cell, store_history, silent, shell_futures, transformed_cell, preprocessing_exc_tuple, cell_id)\u001b[0m\n\u001b[1;32m   3255\u001b[0m                     \u001b[0minteractivity\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'async'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3256\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3257\u001b[0;31m                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,\n\u001b[0m\u001b[1;32m   3258\u001b[0m                        interactivity=interactivity, compiler=compiler, result=result)\n\u001b[1;32m   3259\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mrun_ast_nodes\u001b[0;34m(self, nodelist, cell_name, interactivity, compiler, result)\u001b[0m\n\u001b[1;32m   3490\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3491\u001b[0m                 \u001b[0mresult\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merror_before_exec\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexc_info\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3492\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshowtraceback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3493\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3494\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mshowtraceback\u001b[0;34m(self, exc_tuple, filename, tb_offset, exception_only, running_compiled_code)\u001b[0m\n\u001b[1;32m   2099\u001b[0m                         \u001b[0mstb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_render_traceback_\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2100\u001b[0m                     \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2101\u001b[0;31m                         stb = self.InteractiveTB.structured_traceback(etype,\n\u001b[0m\u001b[1;32m   2102\u001b[0m                                             value, tb, tb_offset=tb_offset)\n\u001b[1;32m   2103\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mstructured_traceback\u001b[0;34m(self, etype, value, tb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m   1365\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1366\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtb\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1367\u001b[0;31m         return FormattedTB.structured_traceback(\n\u001b[0m\u001b[1;32m   1368\u001b[0m             self, etype, value, tb, tb_offset, number_of_lines_of_context)\n\u001b[1;32m   1369\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mstructured_traceback\u001b[0;34m(self, etype, value, tb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m   1265\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mmode\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mverbose_modes\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1266\u001b[0m             \u001b[0;31m# Verbose modes need a full traceback\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1267\u001b[0;31m             return VerboseTB.structured_traceback(\n\u001b[0m\u001b[1;32m   1268\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0metype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtb_offset\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnumber_of_lines_of_context\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1269\u001b[0m             )\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mstructured_traceback\u001b[0;34m(self, etype, evalue, etb, tb_offset, number_of_lines_of_context)\u001b[0m\n\u001b[1;32m   1140\u001b[0m         \u001b[0mchained_exc_ids\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1141\u001b[0m         \u001b[0;32mwhile\u001b[0m \u001b[0mevalue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1142\u001b[0;31m             formatted_exceptions += self.format_exception_as_a_whole(etype, evalue, etb, lines_of_context,\n\u001b[0m\u001b[1;32m   1143\u001b[0m                                                                      chained_exceptions_tb_offset)\n\u001b[1;32m   1144\u001b[0m             \u001b[0mexception\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_parts_of_chained_exception\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mevalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mformat_exception_as_a_whole\u001b[0;34m(self, etype, evalue, etb, number_of_lines_of_context, tb_offset)\u001b[0m\n\u001b[1;32m   1080\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1081\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1082\u001b[0;31m         \u001b[0mlast_unique\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrecursion_repeat\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfind_recursion\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0morig_etype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mevalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrecords\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1083\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1084\u001b[0m         \u001b[0mframes\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat_records\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrecords\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlast_unique\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrecursion_repeat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/ultratb.py\u001b[0m in \u001b[0;36mfind_recursion\u001b[0;34m(etype, value, records)\u001b[0m\n\u001b[1;32m    380\u001b[0m     \u001b[0;31m# first frame (from in to out) that looks different.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    381\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mis_recursion_error\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0metype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrecords\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 382\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrecords\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    383\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    384\u001b[0m     \u001b[0;31m# Select filename, lineno, func_name to track frames with\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mTypeError\u001b[0m: object of type 'NoneType' has no len()"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Q1huBl7_s92A"
      },
      "source": [
        "## **11.3 break\" and \"continue\" statements**<a name='break_continue_statement'></a>\n",
        "break is used to exit a for loop or a while loop, whereas continue is used to skip the current block, and return to the \"for\" or \"while\" statement. A few examples:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "loSiWLLftM6c"
      },
      "source": [
        "# Prints out 0,1,2,3,4\n",
        "count = 0\n",
        "while True:\n",
        "    print(count)\n",
        "    count += 1\n",
        "    if count >= 5:\n",
        "        break\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s0fLXLzetlUZ"
      },
      "source": [
        "# Prints out only odd numbers - 1,3,5,7,9\n",
        "for x in range(10):\n",
        "    # Check if x is even\n",
        "    if x % 2 == 0:\n",
        "        continue\n",
        "    print(x)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yfQXiYbot7oP"
      },
      "source": [
        "##**11.4-Can we use \"else\" clause for loops?**<a name='loop_else'></a>\n",
        "Unlike languages like C,CPP.. we can use else for loops. When the loop condition of \"for\" or \"while\" statement fails then code part in \"else\" is executed. If break statement is executed inside for loop then the \"else\" part is skipped. Note that \"else\" part is executed even if there is a continue statement."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9ja3raQ4uLVb"
      },
      "source": [
        "# Prints out 0,1,2,3,4 and then it prints \"count value reached 5\"\n",
        "\n",
        "count=0\n",
        "while(count<5):\n",
        "    print(count)\n",
        "    count +=1\n",
        "else:\n",
        "    print(\"count value reached %d\" %(count))\n",
        "\n",
        "# Prints out 1,2,3,4\n",
        "for i in range(1, 10):\n",
        "    if(i%5==0):\n",
        "        break\n",
        "    print(i)\n",
        "else:\n",
        "    print(\"this is not printed because for loop is terminated because of break but not due to fail in condition\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **11.5-Looping control statements**<a name='loop_control'>"
      ],
      "metadata": {
        "id": "46OoZfLPII7c"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(1,11):\n",
        "    if i%2==1:\n",
        "        continue\n",
        "    print(i)"
      ],
      "metadata": {
        "id": "dkVw8KaGISxA",
        "outputId": "d7f39b2d-aa3f-4fd9-e694-18f43aeb3cd1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2\n",
            "4\n",
            "6\n",
            "8\n",
            "10\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(1,11):\n",
        "    if i%5==0:\n",
        "        break\n",
        "    print(i)"
      ],
      "metadata": {
        "id": "rAeuWuu9IW80",
        "outputId": "b29cbbb4-476b-4a46-e611-a6c1c22fccf7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1\n",
            "2\n",
            "3\n",
            "4\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(5):\n",
        "    pass\n",
        "\n",
        "print('Nothing done')"
      ],
      "metadata": {
        "id": "adFqLFhjIao0",
        "outputId": "09a5be9c-b7dd-4967-e4f3-2d2d401f9f55",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Nothing done\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qLh5SRAmuwaM"
      },
      "source": [
        "#**12-Functions**<a name='functions'></a>\n",
        "\n",
        "**What are Functions?**\n",
        "\n",
        "Functions are a convenient way to divide your code into useful blocks, allowing us to order our code, make it more readable, reuse it and save some time. Also functions are a key way to define interfaces so programmers can share their code.\n",
        "\n",
        "**How do you write functions in Python?**\n",
        "\n",
        "As we have seen on previous tutorials, Python makes use of blocks.\n",
        "A block is a area of code of written in the format of:\n",
        "\n",
        "block_head:\n",
        "\n",
        "    1st block line\n",
        "    \n",
        "    2nd block line\n",
        "    ...\n",
        "\n",
        "\n",
        "Where a block line is more Python code (even another block), and the block head is of the following format: block_keyword block_name(argument1,argument2, ...) Block keywords you already know are \"if\", \"for\", and \"while\".\n",
        "\n",
        "Functions in python are defined using the block keyword \"def\", followed with the function's name as the block's name. For example:\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nQdEeASZvWVb"
      },
      "source": [
        "def my_function():\n",
        "    print(\"Hello From My Function!\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HBlxgMQHvFKh"
      },
      "source": [
        "def my_function_with_args(username, greeting):\n",
        "    print(\"Hello, %s , From My Function!, I wish you %s\"%(username, greeting))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wTPbY8DpwMue"
      },
      "source": [
        "def sum_two_numbers(a, b):\n",
        "    return a + b"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def my_function():\n",
        "  print(\"Hello from a function\")"
      ],
      "metadata": {
        "id": "i5u3twwV56nt"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def my_function_with_args(username, greeting):\n",
        "    print(\"Hello, %s , From My Function!, I wish you %s\"%(username, greeting))"
      ],
      "metadata": {
        "id": "-6x0xvH96NWL"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3lJNUdzqwP7Y"
      },
      "source": [
        "##**12.1 Call function**<a name='call_functions'></a>\n",
        "Simply write the function's name followed by (), placing any required arguments within the brackets. For example, lets call the functions written above (in the previous example):"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HhO7omhEw8yM",
        "outputId": "c0cfafc3-3e5a-453f-e629-04a5c7322b99",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# print(a simple greeting)\n",
        "my_function()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Hello from a function\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oGuPF5M9xI8q",
        "outputId": "f8c884ee-636e-485f-c63b-28aca3de3f83",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "my_function_with_args(\"John Doe\", \"a great year!\")\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Hello, John Doe , From My Function!, I wish you a great year!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6Q2mEHjRxQ7Z",
        "outputId": "e07e9f0a-3903-4749-f4fb-7a22bbe16a78",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "sum_two_numbers(1, 2)\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**12.2 Arguments**<a name='arguments'></a>"
      ],
      "metadata": {
        "id": "JDyZIJOQ60a2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def my_function(fname):\n",
        "            print(fname + \" Refsnes\")\n",
        "\n",
        "my_function(\"Emil\")\n",
        "my_function(\"Tobias\")\n",
        "my_function(\"Linus\")"
      ],
      "metadata": {
        "id": "FqUouAP97HWq",
        "outputId": "e241f288-d759-4815-e87d-cc01447c4276",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Emil Refsnes\n",
            "Tobias Refsnes\n",
            "Linus Refsnes\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **12.3-Define a function with unlimited inputs**<a name='define_function'></a>"
      ],
      "metadata": {
        "id": "TNT8g2YE7PbN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# define a function (take max 2 inputs)\n",
        "def add(x,y):\n",
        " #add two numbers\n",
        " result=x+y\n",
        " print(f'Reuslt:{result}')"
      ],
      "metadata": {
        "id": "5qkkVGPv7brR"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#define a function (Take unlimited inputs\n",
        "\n",
        "def add (*args):\n",
        " # initialize result at 0\n",
        " result =0\n",
        " # iterate over args tuple\n",
        " for arg in arg:\n",
        "      result +=arg\n",
        " #print the result\n",
        " print (f'Result:{result}')"
      ],
      "metadata": {
        "id": "D42xZRA67_YN"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "add(1,2)"
      ],
      "metadata": {
        "id": "SR3REbIF7iOB",
        "outputId": "4e2623e5-f7ad-4b60-8300-ba257059f3c5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "UnboundLocalError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mUnboundLocalError\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-18-944f4051a32c>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0madd\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m<ipython-input-17-48d52d3f1fd4>\u001b[0m in \u001b[0;36madd\u001b[0;34m(*args)\u001b[0m\n\u001b[1;32m      5\u001b[0m  \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m  \u001b[0;31m# iterate over args tuple\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m  \u001b[0;32mfor\u001b[0m \u001b[0marg\u001b[0m \u001b[0;32min\u001b[0m \u001b[0marg\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      8\u001b[0m       \u001b[0mresult\u001b[0m \u001b[0;34m+=\u001b[0m\u001b[0marg\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m  \u001b[0;31m#print the result\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mUnboundLocalError\u001b[0m: local variable 'arg' referenced before assignment"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YmZFiymirTKT"
      },
      "source": [
        "#**13-Classes and Objects**<a name='class'></a>\n",
        "\n",
        "Objects are an encapsulation of variables and functions into a single entity. Objects get their variables and functions from classes. Classes are essentially a template to create your objects."
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **13.1-How to define a Class in Python?**<a name='define_class'></a>"
      ],
      "metadata": {
        "id": "5PBaefDCBI95"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "class ClassName:\n",
        "    # Class body"
      ],
      "metadata": {
        "id": "IMfl045mBWx2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Example**"
      ],
      "metadata": {
        "id": "j0F41p1uBeLN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "class MyClass:\n",
        "      x = 5"
      ],
      "metadata": {
        "id": "U9IOIwntBkcF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KkBbwaGDrun3"
      },
      "source": [
        "class MyClass:\n",
        "    variable = \"blah\"\n",
        "\n",
        "    def function(self):\n",
        "        print(\"This is a message inside the class.\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **13.2-Create Objects from Class in Python**<a name='define-object'></a>"
      ],
      "metadata": {
        "id": "NB-u-pwvCChI"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6kzj9a3bvJLW"
      },
      "source": [
        "We'll explain why you have to include that \"self\" as a parameter a little bit later. First, to assign the above class(template) to an object you would do the following:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AjOtlu4TvPJO"
      },
      "source": [
        "class MyClass:\n",
        "    variable = \"blah\"\n",
        "\n",
        "    def function(self):\n",
        "        print(\"This is a message inside the class.\")\n",
        "\n",
        "myobjectx = MyClass()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PkxO_bh8vZV6"
      },
      "source": [
        "Now the variable \"myobjectx\" holds an object of the class \"MyClass\" that contains the variable and the function defined within the class called \"MyClass\""
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "p1 = MyClass()\n",
        "print(p1.x)"
      ],
      "metadata": {
        "id": "BCKbXznwCPFy",
        "outputId": "9fa31928-e947-440b-fa0e-b191314769a7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "5\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Gzb6ddHVvjJ5"
      },
      "source": [
        "## **13.3 Accessing Object Variables**<a name='access-obj-variable'></a>\n",
        "To access the variable inside of the newly created object \"myobjectx\" you would do the following:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5zORsV5Uvx_P"
      },
      "source": [
        "class MyClass:\n",
        "    variable = \"blah\"\n",
        "\n",
        "    def function(self):\n",
        "        print(\"This is a message inside the class.\")\n",
        "\n",
        "myobjectx = MyClass()\n",
        "\n",
        "myobjectx.variable"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yi3yquRxwHGn"
      },
      "source": [
        "So for instance the below would output the string \"blah\":\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V_t2WQwKwMUg"
      },
      "source": [
        "class MyClass:\n",
        "    variable = \"blah\"\n",
        "\n",
        "    def function(self):\n",
        "        print(\"This is a message inside the class.\")\n",
        "\n",
        "myobjectx = MyClass()\n",
        "\n",
        "print(myobjectx.variable)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QUfyG--HwlkT"
      },
      "source": [
        "You can create multiple different objects that are of the same class(have the same variables and functions defined). However, each object contains independent copies of the variables defined in the class. For instance, if we were to define another object with the \"MyClass\" class and then change the string in the variable above:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3RSVIyuSwhJk"
      },
      "source": [
        "class MyClass:\n",
        "    variable = \"blah\"\n",
        "\n",
        "    def function(self):\n",
        "        print(\"This is a message inside the class.\")\n",
        "\n",
        "myobjectx = MyClass()\n",
        "myobjecty = MyClass()\n",
        "\n",
        "myobjecty.variable = \"yackity\"\n",
        "\n",
        "# Then print out both values\n",
        "print(myobjectx.variable)\n",
        "print(myobjecty.variable)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JTtkWqyL5aF0"
      },
      "source": [
        "##**13.4 Accessing Object Functions**<a name='access-obj-function'></a>\n",
        "To access a function inside of an object you use notation similar to accessing a variable:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nb4Gcnjo5rmf"
      },
      "source": [
        "class MyClass:\n",
        "    variable = \"blah\"\n",
        "\n",
        "    def function(self):\n",
        "        print(\"This is a message inside the class.\")\n",
        "\n",
        "myobjectx = MyClass()\n",
        "\n",
        "myobjectx.function()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tYMmgDot6HFU"
      },
      "source": [
        "We have a class defined for vehicles. Create two new vehicles called car1 and car2. Set car1 to be a red convertible worth $60,000.00 with a name of Fer, and car2 to be a blue van named Jump worth $10,000.00."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Wnf9WbrF6GN5"
      },
      "source": [
        "# define the Vehicle class\n",
        "class Vehicle:\n",
        "    name = \"\"\n",
        "    kind = \"car\"\n",
        "    color = \"\"\n",
        "    value = 100.00\n",
        "    def description(self):\n",
        "        desc_str = \"%s is a %s %s worth $%.2f.\" % (self.name, self.color, self.kind, self.value)\n",
        "        return desc_str\n",
        "\n",
        "# your code goes here\n",
        "car1 = Vehicle()\n",
        "car1.name = \"Fer\"\n",
        "car1.color = \"red\"\n",
        "car1.kind = \"convertible\"\n",
        "car1.value = 60000.00\n",
        "\n",
        "car2 = Vehicle()\n",
        "car2.name = \"Jump\"\n",
        "car2.color = \"blue\"\n",
        "car2.kind = \"van\"\n",
        "car2.value = 10000.00\n",
        "\n",
        "# test code\n",
        "print(car1.description())\n",
        "print(car2.description())"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Z-IEG6026_gb"
      },
      "source": [
        "# **14 Dictionaries**<a name='dictionary'></a>\n",
        "\n",
        "A dictionary is a data type similar to arrays, but works with keys and values instead of indexes. Each value stored in a dictionary can be accessed using a key, which is any type of object (a string, a number, a list, etc.) instead of using its index to address it.\n",
        "\n",
        "For example, a database of phone numbers could be stored using a dictionary like this:\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZZqBvB3iAIhK",
        "outputId": "908fdf1d-fa56-4f10-ff99-9b6ccfd6cb27",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "phonebook = {}\n",
        "phonebook[\"John\"] = 938477566\n",
        "phonebook[\"Jack\"] = 938377264\n",
        "phonebook[\"Jill\"] = 947662781\n",
        "print(phonebook)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'John': 938477566, 'Jack': 938377264, 'Jill': 947662781}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ufZ79qtTAZns"
      },
      "source": [
        "Alternatively, a dictionary can be initialized with the same values in the following notation:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Me86b5AhAbTM",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5d7617f3-4b9e-45f2-cf74-1cf5cd476d10"
      },
      "source": [
        "phonebook = {\n",
        "    \"John\" : 938477566,\n",
        "    \"Jack\" : 938377264,\n",
        "    \"Jill\" : 947662781\n",
        "}\n",
        "print(phonebook)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'John': 938477566, 'Jack': 938377264, 'Jill': 947662781}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **14.1-Creating a dictionary**<a name='create_dictionary'></a>"
      ],
      "metadata": {
        "id": "cjqhJuHlP_4Y"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# create a dictionary using {}\n",
        "person = {\"name\": \"Jessa\", \"country\": \"USA\", \"telephone\": 1178}\n",
        "print(person)\n",
        "# output {'name': 'Jessa', 'country': 'USA', 'telephone': 1178}"
      ],
      "metadata": {
        "id": "w-3OzDcLQdkQ",
        "outputId": "1b52fcbd-f5ac-4109-9726-84a03f644f7e",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'name': 'Jessa', 'country': 'USA', 'telephone': 1178}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# create a dictionary using dict()\n",
        "person = dict({\"name\": \"Jessa\", \"country\": \"USA\", \"telephone\": 1178})\n",
        "print(person)\n",
        "# output {'name': 'Jessa', 'country': 'USA', 'telephone': 1178}"
      ],
      "metadata": {
        "id": "66a3dxD2Qijn",
        "outputId": "6e10f517-f224-42b9-b166-9084a4b04ad4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'name': 'Jessa', 'country': 'USA', 'telephone': 1178}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# create a dictionary from sequence having each item as a pair\n",
        "person = dict([(\"name\", \"Mark\"), (\"country\", \"USA\"), (\"telephone\", 1178)])\n",
        "print(person)"
      ],
      "metadata": {
        "id": "cAh3Tw6uQ0TX",
        "outputId": "6ffc7532-e587-4fbe-9f16-7f9cfd0f93ac",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'name': 'Mark', 'country': 'USA', 'telephone': 1178}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# create dictionary with mixed keys keys\n",
        "# first key is string and second is an integer\n",
        "sample_dict = {\"name\": \"Jessa\", 10: \"Mobile\"}\n",
        "print(sample_dict)\n",
        "# output {'name': 'Jessa', 10: 'Mobile'"
      ],
      "metadata": {
        "id": "p24OjvtyQ45M",
        "outputId": "a79ff3fc-afe7-4eaf-87d1-74fe3c5a6417",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'name': 'Jessa', 10: 'Mobile'}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 14.2 **Common operation**<a name='common_operations'></a>"
      ],
      "metadata": {
        "id": "njGJa4mDQ9Qb"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Adding Items:**\n",
        "\n"
      ],
      "metadata": {
        "id": "hpWhQn1mRJhH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "my_dict = {}\n",
        "my_dict[\"gender\"] = \"Male\""
      ],
      "metadata": {
        "id": "onnH55MERP-_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rXs4sAo4AtM_"
      },
      "source": [
        "### **Iterating over dictionaries**\n",
        "\n",
        "Dictionaries can be iterated over, just like a list. However, a dictionary, unlike a list, does not keep the order of the values stored in it. To iterate over key value pairs, use the following syntax:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M1bfQ1xWT4yo"
      },
      "source": [
        "phonebook = {\"John\" : 938477566,\"Jack\" : 938377264,\"Jill\" : 947662781}\n",
        "for name, number in phonebook.items():\n",
        "    print(\"Phone number of %s is %d\" % (name, number))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ojkYULYyUGlx"
      },
      "source": [
        "## **14.3- Removing a value**<a name='removing_value'></a>\n",
        " To remove a specified index, use either one of the following notations:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aeMkNjqYUWFi",
        "outputId": "e87e9385-e720-4fd9-9035-c2d9beae7fa7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "phonebook = {\n",
        "   \"John\" : 938477566,\n",
        "   \"Jack\" : 938377264,\n",
        "   \"Jill\" : 947662781\n",
        "}\n",
        "del phonebook[\"John\"]\n",
        "print(phonebook)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'Jack': 938377264, 'Jill': 947662781}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Checking if a Key Exists:**\n",
        "\n"
      ],
      "metadata": {
        "id": "d67P1fw1RpVv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "if \"age\" in my_dict:\n",
        " print(\"Age is present.\")"
      ],
      "metadata": {
        "id": "99aHh6ZlRrvW"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "59NHXDwkUfEY"
      },
      "source": [
        "##**14.3 Exercise**<a name='exercise'></a>\n",
        "Add \"Jake\" to the phonebook with the phone number 938273443, and remove Jill from the phonebook.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GmEIe3-JUrr4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "outputId": "04bb18f4-1187-40e5-c1d5-f2a1cff55017"
      },
      "source": [
        "phonebook = {\n",
        "    \"John\" : 938477566,\n",
        "    \"Jack\" : 938377264,\n",
        "    \"Jill\" : 947662781\n",
        "}\n",
        "\n",
        "# write your code here\n",
        "phonebook[\"Jake\"] = 938273443\n",
        "del phonebook[\"Jill\"]\n",
        "\n",
        "# testing code\n",
        "if \"Jake\" in phonebook:\n",
        "    print(\"Jake is listed in the phonebook.\")\n",
        "if \"Jill\" not in phonebook:\n",
        "    print(\"Jill is not listed in the phonebook.\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Jake is listed in the phonebook.\n",
            "Jill is not listed in the phonebook.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **15- List**<a name='list'></a>"
      ],
      "metadata": {
        "id": "Os5Kh0aqS5mJ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **15.1 List creation**<a name='list_creation'></a>"
      ],
      "metadata": {
        "id": "6giGReoUTC7w"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "my_list = [1, 2, 3, 'hello', True]"
      ],
      "metadata": {
        "id": "AUgtmcRVTK7r"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mylist = []\n",
        "mylist.append(\"a\")\n",
        "mylist.append(\"b\")\n",
        "mylist.append(\"c\")\n",
        "print(mylist[0]) # prints 1\n",
        "print(mylist[1]) # prints 2\n",
        "print(mylist[2]) # prints 3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cvqvp3fmTVgk",
        "outputId": "33c45628-0172-42b6-a8d1-57d8f62d4032"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "a\n",
            "b\n",
            "c\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# prints out 1,2,3\n",
        "for x in mylist:\n",
        "    print(x)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DVe0MQshTajL",
        "outputId": "385aca71-2401-4b0a-8d72-019caed724ea"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "a\n",
            "b\n",
            "c\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Creating a List of numbers\n",
        "List = [10, 20, 14]\n",
        "print(\"\\nList of numbers: \")\n",
        "print(List)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ADb5wMqpTea0",
        "outputId": "f2cf360d-d3f6-4a04-e91a-7214f22ad4bd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "List of numbers: \n",
            "[10, 20, 14]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Creating a List of strings and accessing\n",
        "# using index\n",
        "List = [\"Geeks\", \"For\", \"Geeks\"]\n",
        "print(\"\\nList Items: \")\n",
        "print(List[0])\n",
        "print(List[2])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L3W-9vUfTjIm",
        "outputId": "4b21e6f2-39b6-4f78-87ae-6ec6cd2f92cd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "List Items: \n",
            "Geeks\n",
            "Geeks\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 15.2 **Basic Operations on Lists**<a name='basic_operation_list'></a>"
      ],
      "metadata": {
        "id": "iz3-ejydTrbw"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Accessing Elements:**"
      ],
      "metadata": {
        "id": "pCc95FOgTy2W"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Python program to demonstrate\n",
        "# accessing of element from list\n",
        "\n",
        "# Creating a List with\n",
        "# the use of multiple values\n",
        "List = [\"Geeks\", \"For\", \"Geeks\"]\n",
        "\n",
        "# accessing a element from the\n",
        "# list using index number\n",
        "print(\"Accessing a element from the list\")\n",
        "print(List[0])\n",
        "print(List[2])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ltUtpIEUT3BL",
        "outputId": "4a541526-6f58-4604-880e-b0ddb2f0df26"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accessing a element from the list\n",
            "Geeks\n",
            "Geeks\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "first_element = my_list[0]\n"
      ],
      "metadata": {
        "id": "emfqHGdyaq7Q"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Accessing an index which does not exist generates an exception (an error).\n",
        "mylist = [1,2,3]\n",
        "print(mylist[10])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 210
        },
        "id": "-FB-5utiawWa",
        "outputId": "a5927c4b-0c06-4638-808a-dd8e26747ef1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "IndexError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-8-936f97c60e85>\u001b[0m in \u001b[0;36m<cell line: 3>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m#Accessing an index which does not exist generates an exception (an error).\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mmylist\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmylist\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mIndexError\u001b[0m: list index out of range"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "my_list=list('abcc')\n",
        "my_list.index('c')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7AKdPlaga0aQ",
        "outputId": "bcfd6171-4863-49dc-8bd8-64ec40a7545f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "my_list.reverse()\n",
        "my_list"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9xom_UGPa7EI",
        "outputId": "851037e8-e01f-4f15-cd37-d8406ae92df3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['a', 'b', 'c', 'c']"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "lst1 =[1,2,3]\n",
        "list2= [4,5,6]\n",
        "lst1.append(list2)"
      ],
      "metadata": {
        "id": "Qwi1in_abDnT"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "lst1.extend (list2)"
      ],
      "metadata": {
        "id": "3P01TBDTbJRB"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 15.3**Accessing elements from a multi-dimensional list**<a name='access_element'></a>\n",
        "\n"
      ],
      "metadata": {
        "id": "px6ZNfKQbNK9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Creating a Multi-Dimensional List\n",
        "# (By Nesting a list inside a List)\n",
        "List = [['Geeks', 'For'], ['Geeks']]\n",
        "\n",
        "# accessing an element from the\n",
        "# Multi-Dimensional List using\n",
        "# index number\n",
        "print(\"Accessing a element from a Multi-Dimensional list\")\n",
        "print(List[0][1])\n",
        "print(List[1][0])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D_GOPfM9bUVR",
        "outputId": "a43b1920-2aa0-4434-9ca2-6ba3a3723577"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accessing a element from a Multi-Dimensional list\n",
            "For\n",
            "Geeks\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Slicing:**"
      ],
      "metadata": {
        "id": "EaERdSJgbZOJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "subset = my_list[1:4] # Retrieves elements at indices 1, 2, and 3\n",
        "subset"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iNB4uHy5bdSv",
        "outputId": "dab5ed96-be8f-4a41-8909-e5f4adf8a85f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['b', 'c', 'c']"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Modifying Elements:**\n",
        "\n"
      ],
      "metadata": {
        "id": "aPd8agxlbjED"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "my_list[2] = 'new_value'\n",
        "my_list"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7H10XtQmbnKQ",
        "outputId": "bdf9757e-b37a-4481-a59d-3b24f2f091c7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['a', 'b', 'new_value', 'c']"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 15.4**Adding and Removing Elements:**<a name='add_remove_element'></a>\n",
        "\n"
      ],
      "metadata": {
        "id": "cen3uxiFbud0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "my_list.append(4)\n",
        "my_list"
      ],
      "metadata": {
        "id": "KeftZQrgeBXB",
        "outputId": "973f0792-1687-4dcd-9123-d28eafdfbc00",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['a', 'b', 'new_value', 'c', 4, 4]"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "my_list.insert(2, 'inserted_value')\n",
        "my_list"
      ],
      "metadata": {
        "id": "v2e62URzeIQY",
        "outputId": "3d9a4ed3-f8ed-4d38-852f-062087e63133",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['a', 'b', 'inserted_value', 'new_value', 'c', 4, 4]"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "my_list.remove('hello')\n",
        "my_list"
      ],
      "metadata": {
        "id": "axjDmQG4ePTd",
        "outputId": "934584c8-90ac-4706-eee3-a103308388a1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 193
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "ValueError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-21-8cd96eee7ae9>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmy_list\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mremove\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'hello'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mmy_list\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mValueError\u001b[0m: list.remove(x): x not in list"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "opped_element = my_list.pop(1)"
      ],
      "metadata": {
        "id": "jttYdfcYeXJP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "opped_element"
      ],
      "metadata": {
        "id": "_WY9HkJNeau4",
        "outputId": "89025ab4-394e-4ccc-bb11-f857e7fefbf4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'b'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 15.5**Advanced List Operations:**<a name='advanced_list_operations'></a>"
      ],
      "metadata": {
        "id": "0GAr9tosegD7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "squares = [x**2 for x in range(5)]\n",
        "squares"
      ],
      "metadata": {
        "id": "ugEb6AhCeoTm",
        "outputId": "727caa5a-1729-465a-d568-f4959c7b71cf",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0, 1, 4, 9, 16]"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "list1 =[1,2,3]\n",
        "list2= [4,5,6]"
      ],
      "metadata": {
        "id": "b0jPaSLTe1rP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "combined_list = list1 + list2\n",
        "repeated_list = my_list * 3"
      ],
      "metadata": {
        "id": "e32c17hLeumX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "combined_list\n",
        "repeated_list"
      ],
      "metadata": {
        "id": "T4uAPNhue65H",
        "outputId": "1a5d9fa4-9eb5-4f55-a565-86d3c82f84a4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['a',\n",
              " 'inserted_value',\n",
              " 'new_value',\n",
              " 'c',\n",
              " 4,\n",
              " 4,\n",
              " 'a',\n",
              " 'inserted_value',\n",
              " 'new_value',\n",
              " 'c',\n",
              " 4,\n",
              " 4,\n",
              " 'a',\n",
              " 'inserted_value',\n",
              " 'new_value',\n",
              " 'c',\n",
              " 4,\n",
              " 4]"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GAUb2kydVPgm"
      },
      "source": [
        "#**16-Modules and Packages**<a name='module_package'></a>\n",
        "\n",
        "In programming, a module is a piece of software that has a specific functionality. For example, when building a ping pong game, one module would be responsible for the game logic, and\n",
        "another module would be responsible for drawing the game on the screen. Each module is a different file, which can be edited separately."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "d_idURy4UaYb"
      },
      "source": [
        "## **16.1 Writing modules**<a name='module_writing'></a>\n",
        "Modules in Python are simply Python files with a .py extension. The name of the module will be the name of the file. A Python module can have a set of functions, classes or variables defined and implemented. In the example above, we will have two files, we will have:\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Example 1**"
      ],
      "metadata": {
        "id": "AMrd1MOlIPMe"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# math_operations.py\n",
        "def add(x, y):\n",
        "    return x + y\n",
        "def subtract(x, y):\n",
        "   return x - y\n",
        "def multiply(x, y):\n",
        "   return x * y"
      ],
      "metadata": {
        "id": "JU31AZ_PIZuL"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# main.py\n",
        "import math_operations\n",
        "\n",
        "result_add = math_operations.add(5, 3)\n",
        "result_subtract = math_operations.subtract(8, 2)\n",
        "result_multiply = math_operations.multiply(4, 6)\n",
        "\n",
        "print(\"Addition:\", result_add)\n",
        "print(\"Subtraction:\", result_subtract)\n",
        "print(\"Multiplication:\", result_multiply)\n"
      ],
      "metadata": {
        "id": "ol8HPqksIr3_",
        "outputId": "be3a6c77-4a04-4ebd-8eae-290deae56998",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 383
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "ModuleNotFoundError",
          "evalue": "No module named 'math_operations'",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-3-eca060d76b45>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mmath_operations\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mresult_add\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmath_operations\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mresult_subtract\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmath_operations\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msubtract\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m8\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mresult_multiply\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmath_operations\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmultiply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m4\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m6\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'math_operations'",
            "",
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0;32m\nNOTE: If your import is failing due to a missing package, you can\nmanually install dependencies using either !pip or !apt.\n\nTo view examples of installing some common dependencies, click the\n\"Open Examples\" button below.\n\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n"
          ],
          "errorDetails": {
            "actions": [
              {
                "action": "open_url",
                "actionText": "Open Examples",
                "url": "/notebooks/snippets/importing_libraries.ipynb"
              }
            ]
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Example 2**"
      ],
      "metadata": {
        "id": "gyMn2OZUJhb7"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PRX0lF6qUont"
      },
      "source": [
        "mygame/\n",
        "mygame/game.py\n",
        "mygame/draw.py"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EaFsO-GlUxb9"
      },
      "source": [
        "The Python script game.py will implement the game. It will use the function draw_game from the file draw.py, or in other words, thedraw module, that implements the logic for drawing the game on the screen.\n",
        "\n",
        "Modules are imported from other modules using the import command. In this example, the game.py script may look something like this:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9vK1VQu1U-CH"
      },
      "source": [
        "# game.py\n",
        "# import the draw module\n",
        "import draw\n",
        "\n",
        "def play_game():\n",
        "    ...\n",
        "\n",
        "def main():\n",
        "    result = play_game()\n",
        "    draw.draw_game(result)\n",
        "\n",
        "# this means that if this script is executed, then\n",
        "# main() will be executed\n",
        "if __name__ == '__main__':\n",
        "    main()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-nJ2oA-BVE2S"
      },
      "source": [
        "The draw module may look something like this:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p9ovRIBbVItG"
      },
      "source": [
        "# draw.py\n",
        "\n",
        "def draw_game():\n",
        "    ...\n",
        "\n",
        "def clear_screen(screen):"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Lhd1HbEPjxPo"
      },
      "source": [
        "n this example, the game module imports the draw module, which enables it to use functions implemented in that module. The main function would use the local function play_game to run the game, and then draw the result of the game using a function implemented in the draw module called draw_game. To use the function draw_game from the draw module, we would need to specify in which module the function is implemented, using the dot operator. To reference the draw_game function from the game module, we would need to import the draw module and only then call draw.draw_game().\n",
        "\n",
        "When the import draw directive will run, the Python interpreter will look for a file in the directory which the script was executed from, by the name of the module with a .py prefix, so in our case it will try to look for draw.py. If it will find one, it will import it. If not, he will continue to look for built-in modules.\n",
        "\n",
        "You may have noticed that when importing a module, a .pyc file appears, which is a compiled Python file. Python compiles files into Python bytecode so that it won't have to parse the files each time modules are loaded. If a .pyc file exists, it gets loaded instead of the .py file, but this process is transparent to the user."
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Example 3**"
      ],
      "metadata": {
        "id": "HjFBPvXhJ5I_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# my_module.py\n",
        "def greet(name):\n",
        " return f\"Hello, {name}!\""
      ],
      "metadata": {
        "id": "9ogyIdalKCu3"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# main_script.py\n",
        "import my_module"
      ],
      "metadata": {
        "id": "e_rNhe_bKGNx"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "result = my_module.greet(\"Alice\")\n",
        "print(result)"
      ],
      "metadata": {
        "id": "8Vx0_OFrKJOa"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YXHl89mHkKoi"
      },
      "source": [
        "## **16.2 Importing module objects to the current namespace**<a name='importing_modules'></a>\n",
        "\n",
        "We may also import the function draw_game directly into the main script's namespace, by using the from command."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "x6DbDFaIkdLT"
      },
      "source": [
        "# game.py\n",
        "# import the draw module\n",
        "from draw import draw_game\n",
        "\n",
        "def main():\n",
        "    result = play_game()\n",
        "    draw_game(result)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DATAVdlrkiec"
      },
      "source": [
        "You may have noticed that in this example, draw_game does not precede with the name of the module it is imported from, because we've specified the module name in the import command.\n",
        "\n",
        "The advantages of using this notation is that it is easier to use the functions inside the current module because you don't need to specify which module the function comes from. However, any namespace cannot have two objects with the exact same name, so the import command may replace an existing object in the namespace."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "m6gF7cGmW1cG"
      },
      "source": [
        "## **16.3-Importing all objects from a module**<a name='importing_obj'></a>\n",
        "We may also use the import * command to import all objects from a specific module, like this:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UbUeXFHeXHap"
      },
      "source": [
        "# game.py\n",
        "# import the draw module\n",
        "from draw import *\n",
        "\n",
        "def main():\n",
        "    result = play_game()\n",
        "    draw_game(result)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sa1UxnJBXREh"
      },
      "source": [
        "## **16.4 Custom import name**<a name='custom_name'></a>\n",
        "\n",
        "We may also load modules under any name we want. This is useful when we want to import a module conditionally to use the same name in the rest of the code.\n",
        "\n",
        "For example, if you have two draw modules with slighty different names - you may do the following:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m2FGe5uMXgjc"
      },
      "source": [
        "# game.py\n",
        "# import the draw module\n",
        "if visual_mode:\n",
        "    # in visual mode, we draw using graphics\n",
        "    import draw_visual as draw\n",
        "else:\n",
        "    # in textual mode, we print out text\n",
        "    import draw_textual as draw\n",
        "\n",
        "def main():\n",
        "    result = play_game()\n",
        "    # this can either be visual or textual depending on visual_mode\n",
        "    draw.draw_game(result)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HDGVVOORYBCb"
      },
      "source": [
        "## **16.5 Module initialization**<a name='module_initial'></a>\n",
        "The first time a module is loaded into a running Python script, it is initialized by executing the code in the module once. If another module in your code imports the same module again, it will not be loaded twice but once only - so local variables inside the module act as a \"singleton\" - they are initialized only once.\n",
        "\n",
        "This is useful to know, because this means that you can rely on this behavior for initializing objects. For example:\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kGu4K-ieYQTu"
      },
      "source": [
        "# draw.py\n",
        "\n",
        "def draw_game():\n",
        "    # when clearing the screen we can use the main screen object initialized in this module\n",
        "    clear_screen(main_screen)\n",
        "    ...\n",
        "\n",
        "def clear_screen(screen):\n",
        "    ...\n",
        "\n",
        "class Screen():\n",
        "    ...\n",
        "\n",
        "# initialize main_screen as a singleton\n",
        "main_screen = Screen()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AtJRdeaLkRiP"
      },
      "source": [
        "## **16.6 Extending module load path**<a name='module_load_path'></a>\n",
        "\n",
        "There are a couple of ways we could tell the Python interpreter where to look for modules, aside from the default, which is the local directory and the built-in modules. You could either use the environment variable PYTHONPATH to specify additional directories to look for modules in, like this:\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V6SEZUHxkutg"
      },
      "source": [
        "PYTHONPATH=/foo python game.py"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SMpgZH_-k2e2"
      },
      "source": [
        "This will execute game.py, and will enable the script to load modules from the foo directory as well as the local directory.\n",
        "\n",
        "Another method is the sys.path.append function. You may execute it before running an import command:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FvfE-R31k4YI"
      },
      "source": [
        "sys.path.append(\"/foo\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "StuL1zFck_Qb"
      },
      "source": [
        "This will add the foo directory to the list of paths to look for modules in as well."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YJ74hlErlCGq"
      },
      "source": [
        "## **16.6 -Exploring built-in modules**<a name='built_in_modules'></a>\n",
        "\n",
        "Check out the full list of built-in modules in the Python standard library here.\n",
        "\n",
        "Two very important functions come in handy when exploring modules in Python - the dir and help functions.\n",
        "\n",
        "If we want to import the module urllib, which enables us to create read data from URLs, we simply import the module:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lA8yqbFMlZ6a"
      },
      "source": [
        "# import the library\n",
        "import urllib\n",
        "\n",
        "# use it\n",
        "urllib.urlopen(...)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HxyWYSYZlsjA"
      },
      "source": [
        "When we find the function in the module we want to use, we can read about it more using the help function, inside the Python interpreter:\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FQ9Kp7felu-K"
      },
      "source": [
        "help(urllib.urlopen)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1UQzdbvXl2IW"
      },
      "source": [
        "## **16.7 Writing packages**<a name='writing_packages'></a>\n",
        "\n",
        "Packages are namespaces which contain multiple packages and modules themselves. They are simply directories, but with a twist.\n",
        "\n",
        "Each package in Python is a directory which MUST contain a special file called __init__.py. This file can be empty, and it indicates that the directory it contains is a Python package, so it can be imported the same way a module can be imported.\n",
        "\n",
        "If we create a directory called foo, which marks the package name, we can then create a module inside that package called bar. We also must not forget to add the __init__.py file inside the foo directory.\n",
        "\n",
        "To use the module bar, we can import it in two ways"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "To create a package, you need to follow a specific directory structure. Consider the following example:"
      ],
      "metadata": {
        "id": "KKgy_iJLg97J"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "my_package/\n",
        " __init__.py\n",
        " module1.py\n",
        " module2.py"
      ],
      "metadata": {
        "id": "JBy9bSF-hCAJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Here, my_package is a package containing two modules, module1 and module2. The init.py file signifies that the directory should be treated as a package."
      ],
      "metadata": {
        "id": "6sB5SryIhDs4"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **16.8 Importing Packages:**<a name='import_packages'></a>"
      ],
      "metadata": {
        "id": "EQMJZziTie3J"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Once a package is created, you can import it into your Python scripts using the import statement. For example:"
      ],
      "metadata": {
        "id": "WjwBRqonilFa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import my_package.module1"
      ],
      "metadata": {
        "id": "7FcEyg0aiouR"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "You can also import specific functions or classes from a module within a package:"
      ],
      "metadata": {
        "id": "Gse4tT28ipwa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from my_package.module1 import function1"
      ],
      "metadata": {
        "id": "9sgw0NuvitAy"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "result = module1.function_from_module1()\n",
        "print(result)"
      ],
      "metadata": {
        "id": "cJ_vAzbCiwYE"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **17. File Handling**<a name='file_handling'></a>"
      ],
      "metadata": {
        "id": "5DJEvNLqllfj"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**14.1 Access Modes for Reading a File**\n",
        "\n",
        "The key function for working with files in Python is the open() function.\n",
        "The open() function takes two parameters; filename, and mode. There are four different methods (modes) for opening a file:\n",
        "\n",
        "\"r\" - Read - Default value. Opens a file for reading, error if the file does not exist\n",
        "\n",
        "\"a\" - Append - Opens a file for appending, creates the file if it does not exist\n",
        "\n",
        "\"w\" - Write - Opens a file for writing, creates the file if it does not exist\n",
        "\n",
        "\"x\" - Create - Creates the specified file, returns an error if the file exists\n",
        "\n",
        "Syntax:"
      ],
      "metadata": {
        "id": "x53-jKs7l3Pk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "f = open(\"demofile.txt\")"
      ],
      "metadata": {
        "id": "-aVCwpJZmKSZ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **17.1 Opening and Closing Files**<a name='open_close_file'></a>\n",
        "\n",
        "The first step in file handling is opening a file for reading, writing, or both. Python's open() function is used to open a file, specifying the file name and mode ('r' for reading, 'w' for writing, 'a' for appending, and more). It's essential to close the file using the close() method once you're done with it to free up system resources."
      ],
      "metadata": {
        "id": "BcHPekXQmN0k"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Open a file for reading\n",
        "file = open('example.txt', 'r')"
      ],
      "metadata": {
        "id": "uBTP4-TimZkl"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Read data from the file\n",
        "data = file.read()"
      ],
      "metadata": {
        "id": "AgZme7DTmoos"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Close the file\n",
        "file.close()"
      ],
      "metadata": {
        "id": "iB1ukj-VmsiJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **17.2 Reading from Files**<a name='read_files'></a>"
      ],
      "metadata": {
        "id": "dKfh-42SEagL"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Python offers various methods for reading data from files, such as read(), readline(), and readlines(). These methods allow you to read the entire file, one line at a time, or all lines into a list, respectively.\n",
        "\n",
        "The read () is used to return the entire file content and it accepts the optional size parameter that mentions the bytes to read from the file."
      ],
      "metadata": {
        "id": "0KO_3D1REigR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Read the entire file\n",
        "file = open('example.txt', 'r')\n",
        "data = file.read()\n",
        "file.close()"
      ],
      "metadata": {
        "id": "21GXQoopEmlZ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        " Using the readline() method, we can read a file line by line. by default, this method reads the first line in the file."
      ],
      "metadata": {
        "id": "63p9jjqaEoDQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Read one line at a time\n",
        "file = open('example.txt', 'r')\n",
        "line = file.readline()\n",
        "file.close()"
      ],
      "metadata": {
        "id": "JtsO0bjQEtKp"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "While we have seen how to extract the entire file contents using the readline() method, we can achieve the same using the readlines() method. This method read file line by line into a list."
      ],
      "metadata": {
        "id": "KGGd9WOfEuRo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Read all lines into a list\n",
        "file = open('example.txt', 'r')\n",
        "lines = file.readlines()\n",
        "file.close()"
      ],
      "metadata": {
        "id": "92nIBbjPEx9p"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##  **17.3 Writing to Files**<a name='writing_files'></a>"
      ],
      "metadata": {
        "id": "wjF4f5A1E4dx"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "To write data to a file, open it in write ('w') or append ('a') mode and use the write() method to write data to the file. You can also use the writelines() method to write a list of lines to the file."
      ],
      "metadata": {
        "id": "hvpliot0E0Qh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Write data to a file\n",
        "file = open('output.txt', 'w')\n",
        "file.write('Hello, World!')\n",
        "file.close()"
      ],
      "metadata": {
        "id": "LGDD0G96E-rp"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Append data to a file\n",
        "file = open('output.txt', 'a')\n",
        "file.write('\\nThis is a new line.')\n",
        "file.close()"
      ],
      "metadata": {
        "id": "A6GS3ZlqFB5R"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **17.4 Handling File Errors**<a name='errors'></a>"
      ],
      "metadata": {
        "id": "XKzhCgycFKU5"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "When working with files, it's crucial to handle potential errors gracefully. Python's try-except block can be used to catch and handle exceptions that may occur during file operations."
      ],
      "metadata": {
        "id": "_gVlSKfUFGbx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "try:\n",
        "file = open('nonexistent_file.txt', 'r')\n",
        "data = file.read()\n",
        "file.close()\n",
        "except FileNotFoundError:\n",
        "print(\"File not found!\")"
      ],
      "metadata": {
        "id": "wnvotzmwFE3R"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kEh-Uydfisx0"
      },
      "source": [
        "# **References**\n",
        "\n",
        "[[1] Learn Python](https://www.learnpython.org/en/Conditions)\n",
        "\n",
        "[[2] Real-Time Face Mask Detector with Python, OpenCV, Keras](https://data-flair.training/blogs/face-mask-detection-with-python/)\n",
        "\n",
        "[3] https://medium.com/mlpoint/numpy-for-machine-learning-211a3e58b574]\n",
        "\n",
        "[[4] Interesting Facts About Python Programming Language](https://pub.towardsai.net/8-interesting-facts-about-python-programming-language-ff8ccba88cad#3781)\n",
        "\n",
        "\n",
        "[20 Great Pandas Tricks For Data Science](https://towardsdatascience.com/20-great-pandas-tricks-for-data-science-3a6daed71da0)\n",
        "\n",
        "[Top 5 Python IDE’s For Data Science](https://preettheman.medium.com/top-python-ides-for-data-science-c49c6056cdb4)\n",
        "\n",
        "[Best extensions for JupyterLab!!](https://jlgjosue.medium.com/best-extensions-for-jupyterlab-185ab5f3e05c)\n",
        "\n",
        "[5 Useful Advanced Features of Python](https://python.plainenglish.io/5-useful-advanced-features-of-python-40f0d67fff84)\n",
        "\n",
        "[Quick Recap : 60 days of Data Science and Machine Learning Series](https://medium.com/coders-mojo/quick-recap-60-days-of-data-science-and-machine-learning-series-457ca0e98279)\n",
        "\n",
        "[Top 10 Python Frameworks for Web Development in 2022](https://enlear.academy/top-10-python-frameworks-for-web-development-in-2022-22b37bb03c02)\n",
        "\n",
        "[10 Tools I Wish I Knew When I Started Working with Python](https://python.plainenglish.io/10-tools-to-help-claw-your-way-back-to-sanity-while-coding-python-df0af160c33e)"
      ]
    }
  ]
}