python intro.ipynb

{
 "worksheets": [
  {
   "cells": [
    {
     "metadata": {},
     "cell_type": "heading",
     "source": "Data types",
     "level": 1
    },
    {
     "metadata": {},
     "cell_type": "heading",
     "source": "Integers and floating point numbers",
     "level": 2
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_int = 1",
     "prompt_number": 1,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "type(my_int)",
     "prompt_number": 2,
     "outputs": [
      {
       "text": "int",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 2
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_float = 1.5",
     "prompt_number": 3,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "type(my_float)",
     "prompt_number": 4,
     "outputs": [
      {
       "text": "float",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 4
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "Careful: if you divide an `int` by an `int`, an `int` will result (in Python 2 -- in Python 3, you will get a `float`)"
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "1 / 2",
     "prompt_number": 5,
     "outputs": [
      {
       "text": "0",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 5
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "If one of the two is a `float`, the result is a `float` too:"
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "1.0 / 2",
     "prompt_number": 6,
     "outputs": [
      {
       "text": "0.5",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 6
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "x = 1\ny = 2",
     "prompt_number": 7,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "You can force once of the two to a `float` like this:"
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "float(x) / y",
     "prompt_number": 8,
     "outputs": [
      {
       "text": "0.5",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 8
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "heading",
     "source": "Strings",
     "level": 2
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_string = 'hello'",
     "prompt_number": 9,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "type(my_string)",
     "prompt_number": 10,
     "outputs": [
      {
       "text": "str",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 10
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "Strings are _immutable_, that is, they cannot be changed once created.\n\nTo \"change\" a string, a new string has to be created:"
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_string.upper()",
     "prompt_number": 11,
     "outputs": [
      {
       "text": "'HELLO'",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 11
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_string",
     "prompt_number": 12,
     "outputs": [
      {
       "text": "'hello'",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 12
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_string = my_string.upper()",
     "prompt_number": 13,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_string",
     "prompt_number": 14,
     "outputs": [
      {
       "text": "'HELLO'",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 14
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "heading",
     "source": "Lists and tuples",
     "level": 2
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "Lists are ordered containers and can contain objects of any type."
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_list = [1, 2, 3, 4]",
     "prompt_number": 15,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "another_list = ['tic', 'tac', 'toe']",
     "prompt_number": 16,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "mixed_list = [1, 'tic', 1.5, my_list]",
     "prompt_number": 17,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "Lists are zero-indexed:"
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_list[0]  # This is the zero-th (first) element in my_list",
     "prompt_number": 18,
     "outputs": [
      {
       "text": "1",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 18
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "another_list[1]",
     "prompt_number": 19,
     "outputs": [
      {
       "text": "'tac'",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 19
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "Lists can be sliced:"
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "mixed_list[1:3]",
     "prompt_number": 20,
     "outputs": [
      {
       "text": "['tic', 1.5]",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 20
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "List define useful methods, for example to add an item to the end of the list:"
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_list.append(5)",
     "prompt_number": 21,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_list",
     "prompt_number": 22,
     "outputs": [
      {
       "text": "[1, 2, 3, 4, 5]",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 22
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "__Tuples__ are like lists, except that they cannot be changed once created (i.e. they are immutable).\n\nInstead of using square brackets `[]` to create a list, we use regular brackets `()` to create a tuple."
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_list = [1, 2, 3, 4]\n\nmy_tuple = (1, 2, 3, 4)",
     "prompt_number": 23,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "We cannot append to a tuple, because it cannot be changed:"
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_tuple.append(5)",
     "prompt_number": 24,
     "outputs": [
      {
       "output_type": "pyerr",
       "ename": "AttributeError",
       "evalue": "'tuple' object has no attribute 'append'",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-24-f2f40152e20d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmy_tuple\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[0;31mAttributeError\u001b[0m: 'tuple' object has no attribute 'append'"
       ]
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "heading",
     "source": "Dictionaries",
     "level": 2
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "Dictionaries store key-value pairs. The key can be anything that is immutable (i.e. cannot be changed)."
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_dict = {'x': 0.1, 'y': 1.0, 'z': 0.5}",
     "prompt_number": 25,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_dict['x']",
     "prompt_number": 26,
     "outputs": [
      {
       "text": "0.1",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 26
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "Dictionaries define useful methods, for example to get a list of all keys:"
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_dict.keys()",
     "prompt_number": 27,
     "outputs": [
      {
       "text": "['y', 'x', 'z']",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 27
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "Tuples can be keys of a dictionary (but not lists, because they are not immutable):"
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_other_dict = {(1, 1): 'a', (1, 2): 'b', (2, 1): 'c'}",
     "prompt_number": 28,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_other_dict[(1, 2)]",
     "prompt_number": 29,
     "outputs": [
      {
       "text": "'b'",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 29
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_other_dict.keys()  # The list of keys is a list of tuples",
     "prompt_number": 30,
     "outputs": [
      {
       "text": "[(1, 2), (1, 1), (2, 1)]",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 30
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "heading",
     "source": "Sets",
     "level": 2
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "Sets are unordered collections of unique items"
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_set = {1, 2, 3}",
     "prompt_number": 31,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_set",
     "prompt_number": 32,
     "outputs": [
      {
       "text": "{1, 2, 3}",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 32
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_set.add(1)",
     "prompt_number": 33,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_set",
     "prompt_number": 34,
     "outputs": [
      {
       "text": "{1, 2, 3}",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 34
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "Sets define set-theoretic operations like `union` and `intersection`."
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_other_set = {2, 3, 4, 5}\n\nmy_set.union(my_other_set)",
     "prompt_number": 35,
     "outputs": [
      {
       "text": "{1, 2, 3, 4, 5}",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 35
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "heading",
     "source": "Numpy arrays",
     "level": 2
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "Numpy arrays behave a bit like lists, but can be n-dimensional, and can do much more than lists (e.g. linear algebra)."
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "shape = [10, 3]",
     "prompt_number": 36,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "import numpy as np",
     "prompt_number": 37,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "np.ones(shape)",
     "prompt_number": 38,
     "outputs": [
      {
       "text": "array([[ 1.,  1.,  1.],\n       [ 1.,  1.,  1.],\n       [ 1.,  1.,  1.],\n       [ 1.,  1.,  1.],\n       [ 1.,  1.,  1.],\n       [ 1.,  1.,  1.],\n       [ 1.,  1.,  1.],\n       [ 1.,  1.,  1.],\n       [ 1.,  1.,  1.],\n       [ 1.,  1.,  1.]])",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 38
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "random_array = np.random.random(shape)",
     "prompt_number": 39,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "random_array",
     "prompt_number": 40,
     "outputs": [
      {
       "text": "array([[ 0.81558278,  0.28267059,  0.03731748],\n       [ 0.84822616,  0.45256917,  0.96159072],\n       [ 0.58127966,  0.03889386,  0.04851698],\n       [ 0.03606012,  0.14678589,  0.54226015],\n       [ 0.93301754,  0.43294688,  0.18199496],\n       [ 0.62606184,  0.0745122 ,  0.63058669],\n       [ 0.02635198,  0.59102882,  0.93651475],\n       [ 0.81019223,  0.0833387 ,  0.76386045],\n       [ 0.26544052,  0.26141225,  0.4512097 ],\n       [ 0.70762875,  0.14864612,  0.36470545]])",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 40
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "Accessing items in an array works just like in lists, except that more dimensions are possible:"
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "random_array[0, 1]  # 0th row, 1st column",
     "prompt_number": 41,
     "outputs": [
      {
       "text": "0.28267059224803359",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 41
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "random_array[0, :]  # Get 0th row across all columns",
     "prompt_number": 42,
     "outputs": [
      {
       "text": "array([ 0.81558278,  0.28267059,  0.03731748])",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 42
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "heading",
     "source": "Other data types",
     "level": 2
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "See https://docs.python.org/2/library/datatypes.html"
    },
    {
     "metadata": {},
     "cell_type": "heading",
     "source": "Control structures",
     "level": 1
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "my_list = ['a', 'b', 'c']",
     "prompt_number": 43,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "for i in my_list:\n    print i",
     "prompt_number": 46,
     "outputs": [
      {
       "output_type": "stream",
       "text": "a\nb\nc\n",
       "stream": "stdout"
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "i  # Note that i remains defined after the loop",
     "prompt_number": 47,
     "outputs": [
      {
       "text": "'c'",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 47
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "Another way to iterate through the list (this time iterating through the indices and the items at the same time):"
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "for index, item in enumerate(my_list):\n    print index, ' ', item",
     "prompt_number": 48,
     "outputs": [
      {
       "output_type": "stream",
       "text": "0   a\n1   b\n2   c\n",
       "stream": "stdout"
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "Another approach would be with a while loop, but this is more wordy and less idiomatic:"
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "i = 0\nwhile i < len(my_list):\n    print my_list[i]\n    i += 1",
     "prompt_number": 49,
     "outputs": [
      {
       "output_type": "stream",
       "text": "a\nb\nc\n",
       "stream": "stdout"
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "heading",
     "source": "Speed comparison",
     "level": 2
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "long_list = range(100000)",
     "prompt_number": 50,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "long_list[0:10]",
     "prompt_number": 51,
     "outputs": [
      {
       "text": "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 51
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "%%timeit\n\nfor index, value in enumerate(long_list):\n    long_list[index] = long_list[index] + 1",
     "prompt_number": 52,
     "outputs": [
      {
       "output_type": "stream",
       "text": "100 loops, best of 3: 18 ms per loop\n",
       "stream": "stdout"
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "long_array = np.arange(100000)",
     "prompt_number": 53,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "%%timeit\n\nlong_array1 = long_array + 1",
     "prompt_number": 54,
     "outputs": [
      {
       "output_type": "stream",
       "text": "10000 loops, best of 3: 74.5 µs per loop\n",
       "stream": "stdout"
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "Or get 100000 random numbers:"
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "%%timeit\n\nrand_array = np.random.random(100000)",
     "prompt_number": 55,
     "outputs": [
      {
       "output_type": "stream",
       "text": "1000 loops, best of 3: 1.14 ms per loop\n",
       "stream": "stdout"
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "`np.dot` for matrix multiplication:"
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "np.dot(np.random.random([3, 2]), np.random.random(2))",
     "prompt_number": 56,
     "outputs": [
      {
       "text": "array([ 0.66785091,  0.55662799,  0.29531817])",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 56
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "heading",
     "source": "Defining functions",
     "level": 1
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "def add(a, b):\n    c = a + b\n    return c",
     "prompt_number": 57,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "add(10, 20)",
     "prompt_number": 58,
     "outputs": [
      {
       "text": "30",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 58
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "c  # c is only defined inside the function",
     "prompt_number": 59,
     "outputs": [
      {
       "output_type": "pyerr",
       "ename": "NameError",
       "evalue": "name 'c' is not defined",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-59-64be77f1f9b3>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mc\u001b[0m  \u001b[0;31m# c is only defined inside the function\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[0;31mNameError\u001b[0m: name 'c' is not defined"
       ]
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "markdown",
     "source": "A more advanced function example where one argument (`b`) is optional and gets a default value:"
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "import random",
     "prompt_number": 60,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "def add(a, b=None):\n    \"\"\"Returns the sum of `a` and `b`.\n    \n    If `b` is not given, is is set to a random number between 0\n    and 10.\n    \n    \"\"\"\n    if not b:\n        b = random.randint(0, 10)\n    c = a + b\n    return c",
     "prompt_number": 61,
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "add(1)",
     "prompt_number": 62,
     "outputs": [
      {
       "text": "11",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 62
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "add(1, 10)",
     "prompt_number": 63,
     "outputs": [
      {
       "text": "11",
       "output_type": "pyout",
       "metadata": {},
       "prompt_number": 63
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "add(b=10)  # This does not work because b is optional, but a must be given",
     "prompt_number": 64,
     "outputs": [
      {
       "output_type": "pyerr",
       "ename": "TypeError",
       "evalue": "add() takes at least 1 argument (1 given)",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-64-445ffe25f0be>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0madd\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mb\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# This does not work because b is optional, but a must be given\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[0;31mTypeError\u001b[0m: add() takes at least 1 argument (1 given)"
       ]
      }
     ],
     "language": "python",
     "trusted": true,
     "collapsed": false
    },
    {
     "metadata": {},
     "cell_type": "code",
     "input": "",
     "outputs": [],
     "language": "python",
     "trusted": true,
     "collapsed": false
    }
   ],
   "metadata": {}
  }
 ],
 "metadata": {
  "name": "",
  "signature": "sha256:97cb6615c697fdee3d5056b220c51c09fd5faa42aacd1422cdb5efe02aded526"
 },
 "nbformat": 3
}