hinterland-pyladies.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "IPython Notebook\n",
    "=========\n",
    "\n",
    "Catherine Devlin\n",
    "----------------\n",
    "\n",
    "* catherine.devlin@gmail.com\n",
    "* catherinedevlin.blogspot.com\n",
    "\n",
    "Hinterland PyLadies\n",
    "------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## \"Interactive\" Python?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "* Command completion\n",
    "* %lsmagic\n",
    "* %pfile"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## One year, at PyCon..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "* Awarded [2012 Free Software Award](http://www.fsf.org/news/2012-free-software-award-winners-announced-2)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## What sorcery is this?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "* IPython kernel\n",
    "* Webpage with JavaScript"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Amp up your introspection\n",
    "-------------------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ok\n"
     ]
    }
   ],
   "source": [
    "import re\n",
    "import requests\n",
    "print('ok')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "requests.get??"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "%p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "print("
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "%quickref"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Break out of your shell"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "047-validator.shis a great file!\n",
      "PandasTour.ipynbis a great file!\n",
      "Untitled.ipynbis a great file!\n",
      "Untitled1.ipynbis a great file!\n",
      "demos.ipynbis a great file!\n",
      "make_presentation.ipynbis a great file!\n",
      "make_slides.shis a great file!\n",
      "presentation.ipynbis a great file!\n",
      "pyladies.ipynbis a great file!\n",
      "serve.shis a great file!\n"
     ]
    }
   ],
   "source": [
    "my_directory = !ls\n",
    "for itm in my_directory:\n",
    "    print(itm + 'is a great file!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PandasTour.ipynb         demos.ipynb              presentation.ipynb\r\n",
      "Untitled.ipynb           make_presentation.ipynb  pyladies.ipynb\r\n"
     ]
    }
   ],
   "source": [
    "ls"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "!head Unt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Run not-Python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "IF THAT'S YOUR THING\n"
     ]
    }
   ],
   "source": [
    "%%ruby\n",
    "say = \"if that's your thing\"\n",
    "puts say.upcase"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Run bash scripts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "XKCDify.py\n",
      "d3js.ipynb\n",
      "demos.ipynb\n",
      "demo_wak.ipynb\n",
      "make_presentation.ipynb\n",
      "presentation.ipynb\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ls: cannot access *.ipy: No such file or directory\n"
     ]
    }
   ],
   "source": [
    "%%bash\n",
    "for ext in py ipy ipynb; do\n",
    "  ls *.$ext\n",
    "done"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Don't run bash scripts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['demos.ipynb',\n",
       " 'make_presentation.ipynb',\n",
       " 'Measuring g with an inclined plane.ipynb',\n",
       " 'Music.ipynb',\n",
       " 'presentation.ipynb']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "files = !ls *.ipynb\n",
    "files"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Hybrid scripts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "presentation.reveal.html\n",
      "ls: cannot access *.ipy: No such file or directory\n",
      "demos.ipynb\t\t\t\t  Music.ipynb\n",
      "make_presentation.ipynb\t\t\t  presentation.ipynb\n",
      "Measuring g with an inclined plane.ipynb\n"
     ]
    }
   ],
   "source": [
    "for ext in ('html', 'ipy', 'ipynb'):\n",
    "    !ls *.{ext}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "make_presentation.ipynb\r\n"
     ]
    }
   ],
   "source": [
    "!rm -f *.ipynb.2\n",
    "!ls *_*.ipynb*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Fits the way you experiment"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "### Matches experimental workflow\n",
    "\n",
    "### Keep your experiments"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Revolutionize Your Shared Workflow"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "> “Man is by nature a social animal; an individual who is unsocial naturally and not accidentally is either beneath \n",
    "> our notice or more than human. Society is something that precedes the individual. Anyone who either cannot lead \n",
    "> the common life or is so self-sufficient as not to need to, and therefore does not partake of society, is either \n",
    "> a beast or a god. ”\n",
    "> \n",
    "> ― Aristotle, Politics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Rich output"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Expressive documentation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Executable, always-updated book"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "[Probablistic Programming & Bayesian Methods for Hackers](http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/) by  Cameron Davidson-Pilon"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Math / Latex"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Inline TeX in Markdown: $\\sqrt{3x-1}+(1+x)^2$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$$F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx$$"
      ],
      "text/plain": [
       "<IPython.core.display.Math at 0x25b3750>"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Math\n",
    "Math(r'F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Social coding"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Give a presentation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "    ipython nbconvert --format reveal presentation.ipynb\n",
    "    cd nbconvert_build\n",
    "    python -m SimpleHTTPServer 8000 &\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Requires IPython 1.0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### nbviewer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Every notebook is a JSON file with \".ipynb\" extension"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\r\n",
      " \"metadata\": {\r\n",
      "  \"name\": \"\"\r\n",
      " },\r\n",
      " \"nbformat\": 3,\r\n",
      " \"nbformat_minor\": 0,\r\n",
      " \"worksheets\": [\r\n",
      "  {\r\n",
      "   \"cells\": [\r\n",
      "    {\r\n"
     ]
    }
   ],
   "source": [
    "!head presentation.ipynb"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "* nbviewer.ipython.org/url/*.ipynb-url* serves it publicly!\n",
    "* or nbviewer.ipython.org/*gist-number,\n",
    "* downloadable"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "#### Example: PyOhio video downloads\n",
    "\n",
    "[catherinedevlin.pythoneers.com/pyohio-videos.ipynb](http://catherinedevlin.pythoneers.com/pyohio-videos.ipynb)\n",
    "\n",
    "[nbviewer.ipython.org/url/catherinedevlin.pythoneers.com/pyohio-videos.ipynb](http://nbviewer.ipython.org/url/catherinedevlin.pythoneers.com/pyohio-videos.ipynb)\n",
    "\n",
    "[https://gist.github.com/catherinedevlin/5636516](https://gist.github.com/catherinedevlin/5636516)\n",
    "\n",
    "[http://nbviewer.ipython.org/5636516](http://nbviewer.ipython.org/5636516)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### [wakari](https://www.wakari.io/) by Continuum Analytics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Share a [link to a workbook](https://prod-vz-7.wakari.io:9028/notebook_relative/ipython-talk-pyohio2013/presentation.ipynb)\n",
    "\n",
    "or a [link to a bundle](https://www.wakari.io/sharing/bundle/catherine_devlin/ipython-talk-pyohio2013)\n",
    "\n",
    "... and your collaborators *don't even need Python*..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Go learn this"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "* This presentation: https://github.com/catherinedevlin/ipython-pyohio2013-talk\n",
    "* [Gallery](https://github.com/ipython/ipython/wiki/A-gallery-of-interesting-IPython-Notebooks)\n",
    "* [Videos](http://pyvideo.org/search?models=videos.video&q=ipython)\n",
    "* [IPython In Depth](https://github.com/ipython/ipython-in-depth)\n",
    "* don't forget `%quickref`, `%lsmagic`\n",
    "* catherine.devlin@gmail.com for questions (or job offers!)"
   ]
  }
 ],
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   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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