07 Comprehensions and Functional Programming.ipynb

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   "source": [
    "**What you learn:**\n",
    "\n",
    "In this notebook you will learn about functional programming in Python. This includes list comprehensions, map(), unpacking (*-operator), zip(). \n",
    "\n",
    "Jens Dittrich, [Big Data Analytics Group](https://bigdata.uni-saarland.de/), [CC-BY-SA](https://creativecommons.org/licenses/by-sa/4.0/legalcode)\n",
    "\n",
    "This notebook is available on https://github.com/BigDataAnalyticsGroup/python."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### List comprehensions:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A standard for-loop:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "1\n",
      "2\n",
      "3\n",
      "4\n"
     ]
    }
   ],
   "source": [
    "# Syntax:\n",
    "# for item in list:\n",
    "#    expression\n",
    "for n in range(5):\n",
    "    print(n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 2, 3, 4]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "list(range(5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**vs**\n",
    "\n",
    "a list comprehension:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['0 hallo welt!',\n",
       " '1 hallo welt!',\n",
       " '2 hallo welt!',\n",
       " '3 hallo welt!',\n",
       " '4 hallo welt!']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "# Syntax:\n",
    "# [expression for item in list]\n",
    "#    \n",
    "[str(n)+\" hallo welt!\" for n in range(5)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A standard for-loop with an if-clause:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0  is even\n",
      "2  is even\n",
      "4  is even\n"
     ]
    }
   ],
   "source": [
    "# Syntax:\n",
    "# for item in list:\n",
    "#    if condition:\n",
    "#        expression\n",
    "for n in range(5):\n",
    "    if n%2 == 0:\n",
    "        print(n, \" is even\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**vs**\n",
    "\n",
    "a list comprehension with an if-clause:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 2, 4]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Syntax:\n",
    "# [expression for item in list if condition]\n",
    "#    \n",
    "ar = [n for n in range(5) if n%2 == 0]\n",
    "ar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "output 4\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[4]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def r(f):\n",
    "    print(\"output\",f)\n",
    "    return f\n",
    "# Syntax:\n",
    "# [expression for item in list if condition]\n",
    "#    \n",
    "[r(t) for t in ar if t == 4]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "PS: obviously if the if-clause is just about odd/even numbers or iterating over integers with a fixed offset, we could do this much easier:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 2, 4]"
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     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "[i for i in range(0,5,2)]"
   ]
  },
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   "cell_type": "code",
   "execution_count": 8,
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     "execution_count": 8,
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   ],
   "source": [
    "# Syntax:\n",
    "# range(start_including [, end_excluding [, stepsize]])\n",
    "list(range(0,5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### map()\n",
    "\n",
    "map() is useful to map sequences of items. Do not confuse `map()` with the data structure `map` (aka dictionary) we introduced [in a previous notebook](https://github.com/BigDataAnalyticsGroup/python/blob/master/04%20Sets%20and%20Maps.ipynb).\n",
    "\n",
    "The difference is: map(key) -> value is a function mapping input keys to values.\n",
    "\n",
    "The data structure `map` (aka dictionary created through foo={}) does something similar, however, only **for a predefined and materialized set of key/value-pairs**.\n",
    "\n",
    "In other words, a dictionary, for any given key can only return a value iff that key is present in the dictionary. In contrast, the more general `map()` is simply a function signature that is typically implemented by using code to map values to keys.\n",
    "\n",
    "Of course you could use a dictionary to implement a map()-function."
   ]
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   "cell_type": "code",
   "execution_count": 9,
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     "execution_count": 9,
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   "source": [
    "ar = [0, 1, 2, 3, 4]\n",
    "ar"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "map() using a lambda-function to map keys to their squares:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 4, 9, 16]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "squared2 = list(map(lambda x: x**2, ar))\n",
    "squared2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "map() using a named function to map keys to their squares:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 4, 9, 16]"
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     },
     "execution_count": 11,
     "metadata": {},
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    }
   ],
   "source": [
    "def pow2(x):\n",
    "    return x**2\n",
    "\n",
    "squared = list(map(pow2, ar))\n",
    "squared"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 4, 9, 16]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "squared"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Unpacking and the *-operator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "my_list: [1, 2, 3, 4]\n",
      "*my_list: 1 2 3 4\n",
      "1 2 3 4\n"
     ]
    }
   ],
   "source": [
    "my_list = [1, 2, 3, 4] \n",
    "\n",
    "def foo(a, b, c, d): \n",
    "    print(a, b, c, d) \n",
    "  \n",
    "print(\"my_list:\", my_list)\n",
    "print(\"*my_list:\", *my_list)\n",
    "\n",
    "# unpack my_list into four arguments:\n",
    "foo(*my_list)  # equivalent to: foo(my_list[0], my_list[1], my_list[2], my_list[3] )\n",
    "\n",
    "#fun(my_list) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Example usage:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# define two lists:\n",
    "l1 = range(5)\n",
    "l2 = range(6,11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "range(0, 5)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "range"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(l1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "we obtain an object of type range but we want to have a list!\n",
    "\n",
    "how do we obtain a list?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 2, 3, 4]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# using a comprehension:\n",
    "[i for i in l1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([0, 1, 2, 3, 4], [6, 7, 8, 9, 10])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# using the star-operator and list brackets []\n",
    "[*l1], [*l2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### zip():"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0, 6), (1, 7), (2, 8), (3, 9), (4, 10)]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# zip the two lists together:\n",
    "zipped = zip(l1,l2)\n",
    "[i for i in zipped]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0, 6), (1, 7), (2, 8), (3, 9), (4, 10)]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# or using star:\n",
    "zipped = zip(l1,l2)\n",
    "[*zipped]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that the star-operator draws the elements from its input: so if you use the star on the same object again, the resulting list will be empty!\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[*zipped]"
   ]
  }
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