setup.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction and Setup\n",
    "\n",
    "* [NLTK-Book-Resource Repository](https://github.com/BetoBob/NLTK-Book-Resource)\n",
    "* [NLTK-Book-Resource Table of Contents](https://github.com/BetoBob/NLTK-Book-Resource#table-of-contents)\n",
    "\n",
    "This notebook will teach you how install the resources required to use the resources in this repository."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Program Details\n",
    "\n",
    "The contents of this repository will teach students how to set up an environment to run python code for learning NLTK and to learn more Data Science concepts in the future. Each chapter of the NLTK book has a set of [Jupyter Notebooks](https://jupyter.org/) that includes:\n",
    "\n",
    "1. a **Notes and Examples** notebook with runnable code from examples provided in the book\n",
    "\n",
    "2. an **Exercises** notebook to work on course material\n",
    "\n",
    "3. selected **Exercise Solutions** to review challenging material\n",
    "\n",
    "It's intended students use the **Notes and Examples** page as they read the text to understand how the python code is run, and to edit python code to have a better conceptual understanding of what the code is doing. Tips and references to modern resources such as datasets, Python libraries, APIs and tutorials will be given throughout these notes as well. Students are also encouraged to try the chapter exercises in the **Exercises** notebook, and use the **Exercise Solutions** notebooks to understand more challenging problems."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## What Are Jupyter Notebooks?\n",
    "\n",
    "A Jupyter Notebook is a computational enviornment that allows you to write and run code. It also allows you to make detailed documentation alongside your code. This setup page, in fact, is a jupyter notebook! \n",
    "\n",
    "Jupyter Notebooks have two main components: code cells and markdown cells. The text you are reading here is a markdown cell. Markdown is a simple way of writing documentation. If you click this markdown cell twice, you will be able to edit this markdown text. \n",
    "\n",
    "* [Markdown Cheat Sheet](https://www.markdownguide.org/cheat-sheet/)\n",
    "\n",
    "The other component, *code cells*, can run python code and will display the code's output. To run a code cell such as the one below, click on it and hit the run button. Alternatively you can use a run shortcut, such as:\n",
    "* `Shift + Enter` on Windows\n",
    "* `Command + Enter` on Mac\n",
    "\n",
    "Try running the code cell below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "2 + 3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Python and Jupyter Notebooks will be explained more in the book readings and corresponding chapter notes provided in this repository. There are two ways you can run the Jupyter Notebooks in this repository. First there is **Google Colab**, a google service that allows you run Jupyter Notebooks in a browser without having to download any software. The second is through **Anaconda**, a free package of data science tools you can download to run NLTK and Jupyter Notebooks.\n",
    "\n",
    "It is recommended that you use Anaconda while using this repository because there are certain features like reading large files that can be more difficult to do on Google Colab. However, if you prefer not to use Anaconda or want to try these Notebooks before deciding if **Anocanda** is worth the [5 GB minimum download](https://docs.anaconda.com/anaconda/install/), you will be able to run most of the coding examples through Google Colab. A special note will be made in the notebooks for code that cannot be run in Google Colab."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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\n",
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"400\"\n",
       "            height=\"300\"\n",
       "            src=\"https://www.youtube.com/embed/2eCHD6f_phE\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.YouTubeVideo at 0x2a7c4bd6588>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import YouTubeVideo\n",
    "YouTubeVideo('2eCHD6f_phE')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Option 1: Using Google Colab\n",
    "\n",
    "You can run notebooks in Google Colab through the provided links on the [NLTK-Book-Resource Table of Contents](https://github.com/BetoBob/NLTK-Book-Resource#table-of-contents). This allows you to edit and run all of the notebooks in a web browser. Google Colab has the NLTK library pre-installed, but you will have to need to download the text files used in the coding examples (which takes a little over 5 seconds to load). \n",
    "\n",
    "With a Google account, you can save your work in Google Drive. Simply click `File > Save a copy in Drive` and your jupyter notebook will be stored as a file like a Google Doc. To better understand the features of Google Colab, I reccomend checking out the **Google Colab Features** Notebook below.\n",
    "\n",
    "* [Overview of Colaboratory Features](https://colab.research.google.com/notebooks/basic_features_overview.ipynb)\n",
    "* [NLTK-Book-Resource Table of Contents](https://github.com/BetoBob/NLTK-Book-Resource#table-of-contents)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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\n",
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"400\"\n",
       "            height=\"300\"\n",
       "            src=\"https://www.youtube.com/embed/inN8seMm7UI\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.YouTubeVideo at 0x2a7c4aacc48>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import YouTubeVideo\n",
    "YouTubeVideo('inN8seMm7UI')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How to Use Google Colab\n",
    "\n",
    "A detailed tutorial on how to use Colab Notebooks is provided in the [Overview of Colaboratory Features](https://colab.research.google.com/notebooks/basic_features_overview.ipynb) notebook. However, you will only need to use a handful of these features.\n",
    "\n",
    "It is highly reccomended that you read this following two sections of the [Overview of Colaboratory Features](https://colab.research.google.com/notebooks/basic_features_overview.ipynb) notebook:\n",
    "* Cells\n",
    "* Integration with Drive\n",
    "\n",
    "The **Cells** section discusses how to edit Jupyter Notebooks and run the code in them. The **Integration with Drive** section discusses how to save Colab Notebooks after using them.\n",
    "\n",
    "If a code cell is taking too long to run, press the stop button to the left of the cell. This pauses the notebook's **runtime** and stops the code from running. Try using the stop button on this code cell below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sleeping\n",
      "Done Sleeping\n"
     ]
    }
   ],
   "source": [
    "import time\n",
    "print(\"Sleeping\")\n",
    "time.sleep(30) # this tells the program to wait 30 seconds\n",
    "print(\"Done Sleeping\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When you run a code cell for the first time in a Colab notebook, the Colab notebook's **runtime** will begin. This runtime is responsible for running the python code you execute in the cells and saves variables you create. If a code cell cannot stop running or you would like to remove all the variables you created in the runtime, select `Runtime > Restart Runtime` (or `CTRL M`)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Option 2: Using Anocanda on your Machine\n",
    "\n",
    "If you want to work on the notebook files locally on your computer, you can use install Anocanda. This is the most reccomended option for this course. It's a free and convenient data science toolkit that includes Jupyter Notebooks, Python and popular data science libraries. It is available on Windows, Mac and Linux. Select the appropriate installer for your system and use the default installation options:\n",
    "\n",
    "* [Anocanda Individual Edition Download Page](https://www.anaconda.com/products/individual)\n",
    "\n",
    "If you are comfortable using the terminal, you can also download Jupyter Notebooks seperately using Python pip. This will not include some of the Python libraries that Anaconda provides, but these can also be easily installed with pip when you need them.\n",
    "\n",
    "`python -m pip install jupyter`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Download the Jupyter Notebooks\n",
    "\n",
    "Next you will want to download the files from the [NLTK-Book-Resource Repository](https://github.com/BetoBob/NLTK-Book-Resource). This can be done by clicking the **code** button at the top right-hand side of the repository and selecting **Download Zip**. Alternatively, you can download the ZIP file directly with this link:\n",
    "\n",
    "* [Click Here to Download Repository](https://github.com/BetoBob/NLTK-Book-Resource/archive/master.zip)\n",
    "\n",
    "<center><img src=\"./notes/img/download.png\" alt=\"drawing\" width=\"500\"/></center>\n",
    "\n",
    "Unzip the files and move the `NLTK-Book-Resource-master` folder to a location easy to find such as the `Documents` folder."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Opening Jupyter Notebooks\n",
    "\n",
    "Jupyter Notebooks are stored as `.ipynb` files. They are stored in each Chapter's folder (01 - 11). This is the naming convention for each type of Jupyter Notebook (where `#` is the chapter number):\n",
    "\n",
    "| Type                   | File Name           | Description                                                  |\n",
    "| ---------------------- | ------------------- | ------------------------------------------------------------ |\n",
    "| **Notes and Examples** | `#_notes.ipynb`     | notebook with runnable code from examples provided in the book as well as tips and resources to accompany the text |\n",
    "| **Exercises**          | `#_exercises.ipynb` | notebook to work on chapter exercises                        |\n",
    "| **Exercise Solutions** | `#_solutions.ipyb`  | selected solutions to review challenging material            |\n",
    "\n",
    "\n",
    "#### Windows\n",
    "\n",
    "Once Anaconda and the NLTK-Book-Resource files are downloaded, simply search `Jupyter` in the start menu and select the Jupyter Notebook app.\n",
    "\n",
    "<img src=\"./notes/img/jupyter_app.png\" alt=\"drawing\" width=\"500\"/>\n",
    "\n",
    "Your default web browser will open with a `localhost` url and a Jupyter Notebook terminal will appear. Do not close the terminal until you are finished running and saving your code. Your computer's file system will be shown. Select the `NLTK-Book-Resource-master` and then choose the `.ipynb` file you wish to run.\n",
    "\n",
    "<img src=\"./notes/img/file_struct2.png\" alt=\"drawing\" width=\"800\"/>\n",
    "\n",
    "#### Mac and Linux\n",
    "\n",
    "* open terminal in folder location\n",
    "* type `jupter notebook` in terminal"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Installing NLTK\n",
    "\n",
    "The final step is to install `nltk` and its resources. NLTK is a **python library**, which is a set of tools you can download to do specific tasks in python. You can install python libraries using the `pip install` command below! **pip** is the python library manager.\n",
    "\n",
    "Run the cell below to install NLTK!\n",
    "\n",
    "* `Shift + Enter` on Windows\n",
    "* `Command + Enter` on Mac"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install nltk"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You will also need to download the NLTK text resources. This includes text data like books and articles that will be analyzed in exercises. Run the cell below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import nltk\n",
    "nltk.download('book')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You are now ready to begin reading the chapters and using the Jupyter Notebooks! Read the [Chapter 1 Notes](http://www.nltk.org/book/ch01) and run the examples in the `1_exercises.ipynb` notebook."
   ]
  }
 ],
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