{
 "metadata": {
  "name": "",
  "signature": "sha256:f15d31b87dc7552f72199959115a79a0ea0f08ec0a58e46a5016c4393da78f6b"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Install iPython"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Installation is easy. Optional: Use an enviroment like virtualenv to install the python code.\n",
      "\n",
      "Install with pip: `pip install iPython`\n",
      "\n",
      "Or download and install a scientific package, which delivers a lot of useful python libraries:\n",
      "\n",
      "- Anaconda http://continuum.io/downloads\n",
      "- Enthought Canopy https://www.enthought.com/\n"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Basics"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##Cells"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# this is a cell"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# in a cell you can run python code\n",
      "a = 10\n",
      "b = 20\n",
      "a + b"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 2,
       "text": [
        "30"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "raw",
     "metadata": {},
     "source": [
      "Or use a cell to write your documentation by using markdown."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Tab\n",
      "Tab completion is quite powerful in iPython."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##Suppress"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You can supres the output with a ;"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "a + b;"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##History"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "_"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "30"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "a"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "10"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "__"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "30"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "_i"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "u'__'"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "In[3]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "u'a + b;'"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Out[2]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "30"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%history -l 10"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "a\n",
        "__\n",
        "_i\n",
        "In[3]\n",
        "Out[2]\n",
        "%history \u2013l 10\n",
        "%history \u2013l 10\n",
        "%history \u2013l\n",
        "%history?\n",
        "%history -l [10]\n"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##Help"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import sys\n",
      "sys?"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%ls?"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 17
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Use shift tab over a function name to see the declaration information."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##Shell commands"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You can use the shell command (e.g. bash) with a `!`"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!ls"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "01_numpy.ipynb\r\n",
        "02_audio.ipynb\r\n",
        "03_R.ipynb\r\n",
        "04_Cython.ipynb\r\n",
        "DataLab_final_logo__ColourURL_--UPDATED.png\r\n",
        "Pandas.ipynb\r\n",
        "Untitled0.ipynb\r\n",
        "aapl_ohlc.csv\r\n",
        "deepscore_cnn.py\r\n",
        "\u001b[34mdeepscore_simple_1\u001b[m\u001b[m\r\n",
        "mnist.pkl.gz\r\n",
        "mnist.py\r\n",
        "mnist.pyc\r\n",
        "mnist_conv.py\r\n",
        "png2pickle.ipynb\r\n",
        "title.ipynb\r\n"
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Assigne to a python variable."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "files = !ls\n",
      "files"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 20,
       "text": [
        "['01_numpy.ipynb',\n",
        " '02_audio.ipynb',\n",
        " '03_R.ipynb',\n",
        " '04_Cython.ipynb',\n",
        " 'DataLab_final_logo__ColourURL_--UPDATED.png',\n",
        " 'Pandas.ipynb',\n",
        " 'Untitled0.ipynb',\n",
        " 'aapl_ohlc.csv',\n",
        " 'deepscore_cnn.py',\n",
        " 'deepscore_simple_1',\n",
        " 'mnist.pkl.gz',\n",
        " 'mnist.py',\n",
        " 'mnist.pyc',\n",
        " 'mnist_conv.py',\n",
        " 'png2pickle.ipynb',\n",
        " 'title.ipynb']"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Rich content"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "IPython uses the full potential of modern web techonologies.\n",
      "\n",
      "In Python, objects can declare their textual representation using the `__repr__` method. IPython expands on this idea and allows objects to declare other, richer representations including:\n",
      "\n",
      "- HTML\n",
      "- JSON\n",
      "- PNG\n",
      "- JPEG\n",
      "- SVG\n",
      "- LaTeX"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import HTML\n",
      "\n",
      "HTML('<iframe src=http://dlab.zhaw.ch width=800 height=350></iframe>')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<iframe src=http://dlab.zhaw.ch width=800 height=350></iframe>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 26,
       "text": [
        "<IPython.core.display.HTML at 0x10680ce10>"
       ]
      }
     ],
     "prompt_number": 26
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import Image\n",
      "Image('DataLab_final_logo__ColourURL_--UPDATED.png')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "png": "iVBORw0KGgoAAAANSUhEUgAABn8AAAFECAYAAADmwiuKAAAACXBIWXMAABcSAAAXEgFnn9JSAAAA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\nCkbBKBgFo2AUDGEAEGAACEUK0FCB6MgAAAAASUVORK5CYII=\n",
       "prompt_number": 28,
       "text": [
        "<IPython.core.display.Image at 0x105b8e210>"
       ]
      }
     ],
     "prompt_number": 28
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Publish\n",
      "\n",
      "Store your Notebook in a git repository and point the NDViewer to it.\n",
      "\n",
      "NDViewer http://nbviewer.ipython.org/"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#Collaboration"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from datetime import timedelta\n",
      "from IPython.display import YouTubeVideo\n",
      "YouTubeVideo('F4rFuIb1Ie4', start=int(timedelta(hours=0, minutes=44, seconds=32).total_seconds()))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "\n",
        "        <iframe\n",
        "            width=\"400\"\n",
        "            height=300\"\n",
        "            src=\"https://www.youtube.com/embed/F4rFuIb1Ie4?start=2672\"\n",
        "            frameborder=\"0\"\n",
        "            allowfullscreen\n",
        "        ></iframe>\n",
        "        "
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 36,
       "text": [
        "<IPython.lib.display.YouTubeVideo at 0x105b98850>"
       ]
      }
     ],
     "prompt_number": 36
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}