getting_started_julia/julia_environment.ipynb

{
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<a id='julia-environment'></a>\n",
    "<div id=\"qe-notebook-header\" style=\"text-align:right;\">\n",
    "        <a href=\"https://quantecon.org/\" title=\"quantecon.org\">\n",
    "                <img style=\"width:250px;display:inline;\" src=\"https://assets.quantecon.org/img/qe-menubar-logo.svg\" alt=\"QuantEcon\">\n",
    "        </a>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Interacting with Julia"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Contents\n",
    "\n",
    "- [Interacting with Julia](#Interacting-with-Julia)  \n",
    "  - [Overview](#Overview)  \n",
    "  - [Using Jupyter](#Using-Jupyter)  \n",
    "  - [Using the REPL](#Using-the-REPL)  \n",
    "  - [(Optional) Adding Jupyter to the Path](#%28Optional%29-Adding-Jupyter-to-the-Path)  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overview\n",
    "\n",
    "In this lecture we’ll start examining different features of the Julia and Jupyter environments"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using Jupyter\n",
    "\n",
    "\n",
    "<a id='ipython-notebook'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Getting Started\n",
    "\n",
    "Recall that the easiest way to get started with these notebooks is to follow the [cloning instructions](https://lectures.quantecon.org/getting_started.html#clone-lectures) earlier\n",
    "\n",
    "To summarize, if on a desktop you should clone the notebooks repository <https://github.com/quantecon/quantecon-notebooks-julia>, then in a Julia REPL type"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hide-output": false
   },
   "source": [
    "```julia\n",
    "using IJulia; jupyterlab()\n",
    "```\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hint: Julia will remember the last commands in the REPL, so you can use up-arrow to restart JupyterLab\n",
    "\n",
    "Alternatively, if you are using an online Jupyter, then you can directly open a new notebook\n",
    "\n",
    "Finally, if you installed Jupyter separately or have added [added Jupyter to the Path](#add-jupyter-to-path) then `cd` to the folder location in a terminal, and run"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hide-output": false
   },
   "source": [
    "```text\n",
    "jupyter lab\n",
    "```\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Regardless, your web browser should open to a page that looks something like this\n",
    "\n",
    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/jl/_static/figures/starting_nb_julia.png\" style=\"width:100%;height:100%\">\n",
    "\n",
    "  \n",
    "The page you are looking at is called the “dashboard”\n",
    "\n",
    "If you click on “Julia 1.x.x” you should have the option to start a Julia notebook\n",
    "\n",
    "Here’s what your Julia notebook should look like\n",
    "\n",
    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/jl/_static/figures/nb2_julia.png\" style=\"width:100%;height:100%\">\n",
    "\n",
    "  \n",
    "The notebook displays an *active cell*, into which you can type Julia commands"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Notebook Basics\n",
    "\n",
    "Notice that in the previous figure the cell is surrounded by a blue border\n",
    "\n",
    "This means that the cell is selected, and double-clicking will place it in edit mode\n",
    "\n",
    "As a result, you can type in Julia code and it will appear in the cell\n",
    "\n",
    "When you’re ready to execute these commands, hit `Shift-Enter`\n",
    "\n",
    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/jl/_static/figures/nb3_julia.png\" style=\"width:100%;height:100%\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Modal Editing\n",
    "\n",
    "The next thing to understand about the Jupyter notebook is that it uses a *modal* editing system\n",
    "\n",
    "This means that the effect of typing at the keyboard **depends on which mode you are in**\n",
    "\n",
    "The two modes are\n",
    "\n",
    "1. Edit mode  \n",
    "  \n",
    "  - Indicated by a green border around one cell, as in the pictures above  \n",
    "  - Whatever you type appears as is in that cell  \n",
    "  \n",
    "1. Command mode  \n",
    "  \n",
    "  - The green border is replaced by a blue border  \n",
    "  - Key strokes are interpreted as commands — for example, typing b adds a new cell below  the current one  \n",
    "  \n",
    "\n",
    "\n",
    "(To learn about other commands available in command mode, go to “Keyboard Shortcuts” in the “Help” menu)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Switching modes\n",
    "\n",
    "- To switch to command mode from edit mode, hit the `Esc` key  \n",
    "- To switch to edit mode from command mode, hit `Enter` or click in a cell  \n",
    "\n",
    "\n",
    "The modal behavior of the Jupyter notebook is a little tricky at first but very efficient when you get used to it"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Working with Files\n",
    "\n",
    "To run an existing Julia file using the notebook you can copy and paste the contents into a cell in the notebook\n",
    "\n",
    "If it’s a long file, however, you have the alternative of\n",
    "\n",
    "1. Saving the file in your **present working directory**  \n",
    "1. Executing `include(\"filename\")` in a cell  \n",
    "\n",
    "\n",
    "The present working directory can be found by executing the command `pwd()`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plots\n",
    "\n",
    "Note that if you’re using a JupyterHub setup, you will need to first run"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "hide-output": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32m\u001b[1mActivated\u001b[0m /home/qebuild/repos/lecture-source-jl/_build/website/jupyter/Project.toml\u001b[39m\n",
      "\u001b[36m\u001b[1mInfo\u001b[0m quantecon-notebooks-julia 0.1.0 activated, 0.2.0 requested\u001b[39m\n"
     ]
    }
   ],
   "source": [
    "using InstantiateFromURL\n",
    "github_project(\"QuantEcon/quantecon-notebooks-julia\", version = \"0.2.0\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "in a new cell (i.e., `Shift + Enter`)\n",
    "\n",
    "This might take 15-20 minutes depending on your setup, as it installs a large set of packages for our use\n",
    "\n",
    "Run the following cell"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "hide-output": false
   },
   "outputs": [
    {
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"
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "using Plots\n",
    "gr(fmt=:png);\n",
    "plot(sin, -2π, 2π, label=\"sin(x)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You’ll see something like this (although the style of plot depends on your\n",
    "installation)\n",
    "\n",
    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/jl/_static/figures/nb4_julia.png\" style=\"width:100%;height:100%\">\n",
    "\n",
    "  \n",
    "**Note**: The “time-to-first-plot” in Julia takes a while, since it needs to compile many functions - but is almost instantaneous the second time you run the cell"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Working with the Notebook\n",
    "\n",
    "Let’s go over some more Jupyter notebook features — enough so that we can press ahead with programming"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Tab Completion\n",
    "\n",
    "Tab completion in Jupyter makes it easy to find Julia commands and functions available\n",
    "\n",
    "For example if you type `rep` and hit the tab key you’ll get a list of all\n",
    "commands that start with `rep`\n",
    "\n",
    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/jl/_static/figures/nb5_julia.png\" style=\"width:100%;height:100%\">\n",
    "\n",
    "  \n",
    "\n",
    "<a id='gs-help'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Getting Help\n",
    "\n",
    "To get help on the Julia function such as `repeat`, enter `? repeat`\n",
    "\n",
    "Documentation should now appear in the browser\n",
    "\n",
    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/jl/_static/figures/repeatexample.png\" style=\"width:100%;height:100%\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Other Content\n",
    "\n",
    "In addition to executing code, the Jupyter notebook allows you to embed text, equations, figures and even videos in the page\n",
    "\n",
    "For example, here we enter a mixture of plain text and LaTeX instead of code\n",
    "\n",
    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/jl/_static/figures/nb6_julia.png\" style=\"width:100%;height:100%\">\n",
    "\n",
    "  \n",
    "Next we `Esc` to enter command mode and then type `m` to indicate that we\n",
    "are writing [Markdown](http://daringfireball.net/projects/markdown/), a mark-up language similar to (but simpler than) LaTeX\n",
    "\n",
    "(You can also use your mouse to select `Markdown` from the `Code` drop-down box just below the list of menu items)\n",
    "\n",
    "Now we `Shift + Enter` to produce this\n",
    "\n",
    "<img src=\"https://s3-ap-southeast-2.amazonaws.com/lectures.quantecon.org/jl/_static/figures/nb7_julia.png\" style=\"width:100%;height:100%\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Inserting unicode (e.g. Greek letters)\n",
    "\n",
    "Julia supports the use of [unicode characters](https://docs.julialang.org/en/v1/manual/unicode-input/)\n",
    "such as `α` and `β` in your code\n",
    "\n",
    "Unicode characters can be typed quickly in Jupyter using the `tab` key\n",
    "\n",
    "Try creating a new code cell and typing `\\alpha`, then hitting the `tab` key on your keyboard"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Shell Commands\n",
    "\n",
    "You can execute shell commands (system commands) in Jupyter by prepending a semicolon\n",
    "\n",
    "For example, `; ls` will execute the UNIX style shell command `ls`,\n",
    "which — at least for UNIX style operating systems — lists the\n",
    "contents of the current working directory\n",
    "\n",
    "These shell commands are handled by your default system shell and hence are platform specific"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Package Operations\n",
    "\n",
    "You can execute package operations in the notebook by prepending a `]`\n",
    "\n",
    "For example, `] st` will give the status of installed packages in the current environment\n",
    "\n",
    "**Note**: Cells where you use `;` and `]` must not have any other instructions in them (i.e., they should be one-liners)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sharing Notebooks\n",
    "\n",
    "Notebook files are just text files structured in [JSON](https://en.wikipedia.org/wiki/JSON) and typically end with `.ipynb`\n",
    "\n",
    "A notebook can easily be saved and shared between users — you just need to\n",
    "pass around the `ipynb` file\n",
    "\n",
    "To open an existing `ipynb` file, import it from the dashboard (the first\n",
    "browser page that opens when you start Jupyter notebook) and run the cells or edit as discussed above\n",
    "\n",
    "The Jupyter organization has a site for sharing notebooks called [nbviewer](http://nbviewer.jupyter.org/)\n",
    "which provides a static HTML representations of notebooks\n",
    "\n",
    "QuantEcon also hosts the [QuantEcon Notes](http://notes.quantecon.org/) website, where you can upload and share your notebooks with other economists and the QuantEcon community\n",
    "\n",
    "\n",
    "<a id='julia-repl'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using the REPL\n",
    "\n",
    "As we saw in the [desktop installation](https://lectures.quantecon.org/getting_started.html#intro-repl), the REPL is a Julia specific terminal\n",
    "\n",
    "It becomes increasingly important as you learn Julia, and you will find it to be a useful tool for interacting with Julia and installing packages\n",
    "\n",
    "As a reminder, to open the REPL on your desktop, either\n",
    "\n",
    "1. Navigating to Julia through your menus or desktop icons (Windows, Mac), or  \n",
    "1. Opening a terminal and typing `julia` (Linux)  \n",
    "\n",
    "\n",
    "If you are using a JupyterHub installation, you can start the REPL in JupyterLab by choosing\n",
    "\n",
    "1. Choose “New Launcher”  \n",
    "1. Choose a `Julia` Console  \n",
    "\n",
    "\n",
    "We examine the REPL and its different modes in more detail in the [tools and editors](https://lectures.quantecon.org/more_julia/tools_editors.html#repl-main) lecture\n",
    "\n",
    "\n",
    "<a id='add-jupyter-to-path'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## (Optional) Adding Jupyter to the Path\n",
    "\n",
    "If you [installed Jupyter using Julia](https://lectures.quantecon.org/getting_started.html#jupyter-installation), then you may find it convenient to add it to your system path\n",
    "in order to launch JupyterLab without running a Julia terminal.\n",
    "\n",
    "The default location for the Jupyter binaries is relative to the `.julia` folder (e.g., `\"C:\\Users\\USERNAME\\.julia\\conda\\3\\Scripts` on Windows)\n",
    "\n",
    "You can find the directory in a Julia REPL using by executing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hide-output": false
   },
   "source": [
    "```julia\n",
    "] add Conda\n",
    "using Conda\n",
    "Conda.SCRIPTDIR\n",
    "```\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On Linux/OSX, you could add that path to your `.bashrc`\n",
    "\n",
    "On Windows, to add directly to the path, type `;` to enter shell mode and then execute"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hide-output": false
   },
   "source": [
    "```julia\n",
    "setx PATH \"$(Conda.SCRIPTDIR);%PATH%\"\n",
    "```\n"
   ]
  }
 ],
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