examples/Notebook/Running%20Code.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Running Code"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First and foremost, the Jupyter Notebook is an interactive environment for writing and running code. The notebook is capable of running code in a wide range of languages. However, each notebook is associated with a single kernel.  This notebook is associated with the IPython kernel, therefore runs Python code."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Code cells allow you to enter and run code"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run a code cell using `Shift-Enter` or pressing the <button class='btn btn-default btn-xs'><i class=\"icon-step-forward fa fa-play\"></i></button> button in the toolbar above:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "a = 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10\n"
     ]
    }
   ],
   "source": [
    "print(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are two other keyboard shortcuts for running code:\n",
    "\n",
    "* `Alt-Enter` runs the current cell and inserts a new one below.\n",
    "* `Ctrl-Enter` run the current cell and enters command mode."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Managing the Kernel"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Code is run in a separate process called the Kernel.  The Kernel can be interrupted or restarted.  Try running the following cell and then hit the <button class='btn btn-default btn-xs'><i class='icon-stop fa fa-stop'></i></button> button in the toolbar above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import time\n",
    "time.sleep(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If the Kernel dies you will be prompted to restart it. Here we call the low-level system libc.time routine with the wrong argument via\n",
    "ctypes to segfault the Python interpreter:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "from ctypes import CDLL\n",
    "# This will crash a Linux or Mac system\n",
    "# equivalent calls can be made on Windows\n",
    "\n",
    "# Uncomment these lines if you would like to see the segfault\n",
    "\n",
    "# dll = 'dylib' if sys.platform == 'darwin' else 'so.6'\n",
    "# libc = CDLL(\"libc.%s\" % dll) \n",
    "# libc.time(-1)  # BOOM!!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cell menu"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The \"Cell\" menu has a number of menu items for running code in different ways. These includes:\n",
    "\n",
    "* Run and Select Below\n",
    "* Run and Insert Below\n",
    "* Run All\n",
    "* Run All Above\n",
    "* Run All Below"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Restarting the kernels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The kernel maintains the state of a notebook's computations. You can reset this state by restarting the kernel. This is done by clicking on the <button class='btn btn-default btn-xs'><i class='fa fa-repeat icon-repeat'></i></button> in the toolbar above."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## sys.stdout and sys.stderr"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The stdout and stderr streams are displayed as text in the output area."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hi, stdout\n"
     ]
    }
   ],
   "source": [
    "print(\"hi, stdout\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "hi, stderr\n"
     ]
    }
   ],
   "source": [
    "from __future__ import print_function\n",
    "print('hi, stderr', file=sys.stderr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Output is asynchronous"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All output is displayed asynchronously as it is generated in the Kernel. If you execute the next cell, you will see the output one piece at a time, not all at the end."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "1\n",
      "2\n",
      "3\n",
      "4\n",
      "5\n",
      "6\n",
      "7\n"
     ]
    }
   ],
   "source": [
    "import time, sys\n",
    "for i in range(8):\n",
    "    print(i)\n",
    "    time.sleep(0.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Large outputs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To better handle large outputs, the output area can be collapsed. Run the following cell and then single- or double- click on the active area to the left of the output:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "for i in range(50):\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Beyond a certain point, output will scroll automatically:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "3121748550315992231381597229793166305748598142664971150859156959625371738819765620120306103063491971159826931121406622895447975679288285306290175\n",
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      "199791907220223502808422222706762643567910281130558153654986045416023791284464999687699590596063486154228923591770023865308670443474450259602571263\n",
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      "799167628880894011233688890827050574271641124522232614619944181664095165137859998750798362384253944616915694367080095461234681773897801038410285055\n",
      "1598335257761788022467377781654101148543282249044465229239888363328190330275719997501596724768507889233831388734160190922469363547795602076820570111\n",
      "3196670515523576044934755563308202297086564498088930458479776726656380660551439995003193449537015778467662777468320381844938727095591204153641140223\n",
      "6393341031047152089869511126616404594173128996177860916959553453312761321102879990006386899074031556935325554936640763689877454191182408307282280447\n",
      "12786682062094304179739022253232809188346257992355721833919106906625522642205759980012773798148063113870651109873281527379754908382364816614564560895\n",
      "25573364124188608359478044506465618376692515984711443667838213813251045284411519960025547596296126227741302219746563054759509816764729633229129121791\n",
      "51146728248377216718956089012931236753385031969422887335676427626502090568823039920051095192592252455482604439493126109519019633529459266458258243583\n",
      "102293456496754433437912178025862473506770063938845774671352855253004181137646079840102190385184504910965208878986252219038039267058918532916516487167\n",
      "204586912993508866875824356051724947013540127877691549342705710506008362275292159680204380770369009821930417757972504438076078534117837065833032974335\n",
      "409173825987017733751648712103449894027080255755383098685411421012016724550584319360408761540738019643860835515945008876152157068235674131666065948671\n",
      "818347651974035467503297424206899788054160511510766197370822842024033449101168638720817523081476039287721671031890017752304314136471348263332131897343\n",
      "1636695303948070935006594848413799576108321023021532394741645684048066898202337277441635046162952078575443342063780035504608628272942696526664263794687\n"
     ]
    }
   ],
   "source": [
    "for i in range(500):\n",
    "    print(2**i - 1)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.1"
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 },
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}