{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Setting up a Python environment\n", "\n", "(c) 2022 Justin Bois. This work is licensed under a [Creative Commons Attribution License CC-BY 4.0](https://creativecommons.org/licenses/by/4.0/). All code contained herein is licensed under an [MIT license](https://opensource.org/licenses/MIT).\n", "\n", "This document was prepared at [Caltech](http://www.caltech.edu) with support financial support from the [Donna and Benjamin M. Rosen Bioengineering Center](http://rosen.caltech.edu).\n", "\n", "\n", "\n", "*This tutorial was generated from an Jupyter notebook. You can download the notebook [here](setting_up_python_environment.ipynb).*\n", "\n", "
\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this lesson, you will set up a Python computing environment for scientific computing. We will install [Anaconda](https://www.anaconda.com) with its associated package manager, `conda`. It has become the de facto package manager/distribution for scientific use.\n", "\n", "Before we get rolling with the Anaconda distribution, we have some considerations and installations to get out of the way first." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## macOS users: Install XCode\n", "\n", "If you are using macOS, you should install [XCode](https://developer.apple.com/xcode/), if you haven't already. It's a large piece of software, taking up about 5GB on your hard drive, so make sure you have enough space. You can install it through the App Store.\n", "\n", "After installing it, you need to open the program. Be sure to do that, for example by clicking on the XCode icon in your Applications folder. Upon opening XCode, it may perform more installations. After these are completed, you can close XCode." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Windows users: Install Chrome or Firefox\n", "\n", "We will be using [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) in this course. It is browser-based, and Chrome, Firefox, and Safari are supported. Microsoft Edge is **not**. Therefore, if you are a Windows user, you need to be sure you have either Chrome of Firefox installed." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Uninstalling Anaconda\n", "\n", "Unless you have experience with Anaconda and know how to set up environments, if you have previously installed Anaconda with a version of Python other than 3.9, you need to uninstall it, removing it completely from your computer. You can find instructions on how to do that from the [official uninstallation documentation](https://docs.anaconda.com/anaconda/install/uninstall/)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Downloading and installing Anaconda\n", "\n", "Downloading and installing Anaconda is simple. \n", "1. Go to the [Anaconda distribution homepage](https://www.anaconda.com/distribution/) and download the graphical installer. \n", "2. Be sure to download Anaconda for Python 3.9 for the appropriate operating system.\n", "3. Follow the on-screen instructions for installation. When prompted, be sure to \"Install for me only.\"\n", "4. You may be prompted for optional installations, like [PyCharm](https://www.jetbrains.com/pycharm/). You will not need these for the course.\n", "\n", "That's it! After you do that, you will have a functioning Python distribution." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Install node.js\n", "\n", "[node.js](https://nodejs.org/) is a platform that enables you to run JavaScript outside of the browser. We will not use it directly, but it needs to be installed for some of the more sophisticated JupyterLab functionality. Install node.js by downloading the appropriate installer for your machine [here](https://nodejs.org/en/download/)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Launching JupyterLab and a terminal\n", "\n", "After installing the Anaconda distribution, you should be able to launch the **Anaconda Navigator**. If you are using macOS, this is available in your `Applications` menu. If you are using Windows, you can do this from the Start menu. Launch Anaconda Navigator.\n", "\n", "We will be using JupyterLab throughout the course. You should see an option to launch JupyterLab. When you do that, a new browser window or tab will open with JupyterLab running. Within the JupyterLab window, you will have the option to launch a notebook, a console, a terminal, or a text editor. For the updating and installation of necessary packages, click on `Terminal` to launch a terminal. You will get a terminal window (probably black) with a bash prompt. We refer to this text interface in the terminal as the **command line**.\n", "\n", "If you prefer, you may use the terminal app of your operating system (PowerShell on Windows, or Terminal on a Mac) instead of JupyterLab's terminal. If you want to launch JupyterLab from the command line, simply type\n", "\n", " jupyter lab\n", " \n", "on the command line. If your default browser is not supported, you and instead use, e.g.,\n", "\n", " jupyter lab --browser=firefox" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Launching JupyterLab from the command line\n", "\n", "While launching JupyterLab from the Anaconda Navigator is fine, I generally prefer to launch it from the command line on my own machine. If you are on a Mac, open the Terminal program. You can do this hitting `Command + space bar` and searching for \"terminal.\" Using Windows, you should launch PowerShell. You can do this by hitting `Windows + R` and typing \"powershell\" in the text box.\n", "\n", "Once you have a terminal or PowerShell window open, you will have a prompt. At the prompt, type\n", "\n", " jupyter lab\n", " \n", "and you will have an instance of JupyterLab running in your browser. If you want to specify the browser, you can, for example, type\n", "\n", " jupyter lab --browser=firefox\n", " \n", "on the command line.\n", "\n", "It is up to you if you want to launch JupyterLab from the Anaconda Navigator or command line." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## The conda package manager\n", "\n", "conda is a package manager for keeping all of your packages up-to-date. It has plenty of functionality beyond our basic usage in class, which you can learn more about by reading the [docs](http://conda.pydata.org/docs/get-started.html). We will primarily be using conda to install and update packages.\n", "\n", "conda works from the command line. Now that you know how to get a command line prompt, you can start using conda. The first thing we'll do is update the packages that came with the Anaconda distribution. To do this, enter the following on the command line:\n", "\n", " conda update conda\n", " conda update --all\n", "\n", "If anything is out of date, you will be prompted to perform the updates, and press `y` to continue. (If everything is up to date, you will just see a list of all the installed packages.) They may even be some downgrades. This happens when there are package conflicts where one package requires an earlier version of another. conda is very smart and figures all of this out for you, so you can almost always say \"yes\" (or \"`y`\") to conda when it prompts you." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Installations\n", "\n", "There are a few installations that you should do to help with the class. First, you will need to allow Bokeh, our primary plotting package, to work with Jupyter notebooks.\n", "\n", " conda install -c bokeh jupyter_bokeh\n", " \n", "It is also nice to have some convenient color palettes available with the colorcet package.\n", "\n", " conda install colorcet\n", " \n", "We will use `pip` to install a few utilities we will make use of.\n", "\n", " pip install watermark blackcellmagic jupyterlab-spellchecker iqplot bi1x\n", "\n", "You should close your JupyterLab session and terminate Anaconda Navigator after you have completed the build. Relaunch Anaconda Navigator and launch a fresh JupyterLab instance. You are now all set!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Checking your distribution\n", "We'll now run a quick test to make sure things are working properly. We will make a quick plot that requires some of the scientific libraries we will use.\n", "\n", "Use the JupyterLab launcher (you can get a new launcher by clicking on the `+` icon on the left pane of your JupyterLab window) to launch a notebook. In the first cell (the box next to the `[ ]:` prompt), paste the code below. To run the code, press `Shift+Enter` while the cursor is active inside the cell. You should see a plot that looks like the one below. If you do, you have a functioning Python environment for scientific computing!" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
\n", " \n", " Loading BokehJS ...\n", "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", "(function(root) {\n", " function now() {\n", " return new Date();\n", " }\n", "\n", " const force = true;\n", "\n", " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", " root._bokeh_onload_callbacks = [];\n", " root._bokeh_is_loading = undefined;\n", " }\n", "\n", " const JS_MIME_TYPE = 'application/javascript';\n", " const HTML_MIME_TYPE = 'text/html';\n", " const EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", " const CLASS_NAME = 'output_bokeh rendered_html';\n", "\n", " /**\n", " * Render data to the DOM node\n", " */\n", " function render(props, node) {\n", " const script = document.createElement(\"script\");\n", " node.appendChild(script);\n", " }\n", "\n", " /**\n", " * Handle when an output is cleared or removed\n", " */\n", " function handleClearOutput(event, handle) {\n", " const cell = handle.cell;\n", "\n", " const id = cell.output_area._bokeh_element_id;\n", " const server_id = cell.output_area._bokeh_server_id;\n", " // Clean up Bokeh references\n", " if (id != null && id in Bokeh.index) {\n", " Bokeh.index[id].model.document.clear();\n", " delete Bokeh.index[id];\n", " }\n", "\n", " if (server_id !== undefined) {\n", " // Clean up Bokeh references\n", " const cmd_clean = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", " cell.notebook.kernel.execute(cmd_clean, {\n", " iopub: {\n", " output: function(msg) {\n", " const id = msg.content.text.trim();\n", " if (id in Bokeh.index) {\n", " Bokeh.index[id].model.document.clear();\n", " delete Bokeh.index[id];\n", " }\n", " }\n", " }\n", " });\n", " // Destroy server and session\n", " const cmd_destroy = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", " cell.notebook.kernel.execute(cmd_destroy);\n", " }\n", " }\n", "\n", " /**\n", " * Handle when a new output is added\n", " */\n", " function handleAddOutput(event, handle) {\n", " const output_area = handle.output_area;\n", " const output = handle.output;\n", "\n", " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", " if ((output.output_type != \"display_data\") || (!Object.prototype.hasOwnProperty.call(output.data, EXEC_MIME_TYPE))) {\n", " return\n", " }\n", "\n", " const toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", "\n", " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", " // store reference to embed id on output_area\n", " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", " }\n", " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", " const bk_div = document.createElement(\"div\");\n", " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", " const script_attrs = bk_div.children[0].attributes;\n", " for (let i = 0; i < script_attrs.length; i++) {\n", " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", " }\n", " // store reference to server id on output_area\n", " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", " }\n", " }\n", "\n", " function register_renderer(events, OutputArea) {\n", "\n", " function append_mime(data, metadata, element) {\n", " // create a DOM node to render to\n", " const toinsert = this.create_output_subarea(\n", " metadata,\n", " CLASS_NAME,\n", " EXEC_MIME_TYPE\n", " );\n", " this.keyboard_manager.register_events(toinsert);\n", " // Render to node\n", " const props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", " render(props, toinsert[toinsert.length - 1]);\n", " element.append(toinsert);\n", " return toinsert\n", " }\n", "\n", " /* Handle when an output is cleared or removed */\n", " events.on('clear_output.CodeCell', handleClearOutput);\n", " events.on('delete.Cell', handleClearOutput);\n", "\n", " /* Handle when a new output is added */\n", " events.on('output_added.OutputArea', handleAddOutput);\n", "\n", " /**\n", " * Register the mime type and append_mime function with output_area\n", " */\n", " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", " /* Is output safe? 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\\n\"+\n", " \"

\\n\"+\n", " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", " \"

\\n\"+\n", " \"\\n\"+\n", " \"\\n\"+\n", " \"from bokeh.resources import INLINE\\n\"+\n", " \"output_notebook(resources=INLINE)\\n\"+\n", " \"\\n\"+\n", " \"
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\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
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bokeh.plotting\n", "import bokeh.io\n", "\n", "bokeh.io.output_notebook()\n", "\n", "# Generate plotting values\n", "t = np.linspace(0, 2 * np.pi, 200)\n", "x = 16 * np.sin(t) ** 3\n", "y = 13 * np.cos(t) - 5 * np.cos(2 * t) - 2 * np.cos(3 * t) - np.cos(4 * t)\n", "\n", "p = bokeh.plotting.figure(height=250, width=275)\n", "p.line(x, y, color=\"red\", line_width=3)\n", "text = bokeh.models.Label(x=0, y=0, text=\"Bi 1x\", text_align=\"center\")\n", "p.add_layout(text)\n", "\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Computing environment" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Python implementation: CPython\n", "Python version : 3.9.7\n", "IPython version : 8.1.1\n", "\n", "numpy : 1.21.2\n", "bokeh : 2.4.2\n", "jupyterlab: 3.3.2\n", "\n" ] } ], "source": [ "%load_ext watermark\n", "%watermark -v -p numpy,bokeh,jupyterlab" ] } ], "metadata": { 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