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zingalezingale
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update for class
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‎lectures/01-python/python-datatypes.ipynb‎

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"cells": [
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{
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"metadata": {
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},
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{
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"cell_type": "code",
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"metadata": {
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"collapsed": false
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"outputs": [
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{
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"data": {
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"text/plain": [
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"7"
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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"source": [
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‎lectures/01-python/python-functions.ipynb‎

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"# functions"
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]
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{
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"cell_type": "raw",
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"metadata": {},
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"source": [
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"Functions are used to organize program flow, especially to allow us to easily do commonly needed tasks over and over again. We've already used a lot of functions, such as those that work on lists (`append()` and `pop()`) or strings (like `replace()`). Here we see how to write our own functions"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"A function takes arguments, listed in the `()` and returns a value. Even if you don't explictly give a return value, one will be return (e.g., `None`). \n",
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"\n",
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"Here's a simple example of a function that takes a single argument, `i`"
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]
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},
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{
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"cell_type": "code",
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"functions are one place where scope comes into play. A function has its own namespace. If a variable is not defined in that function, then it will look to the namespace from where it was called to see if that variable exists there. "
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"functions are one place where _scope_ comes into play. A function has its own _namespace_. If a variable is not defined in that function, then it will look to the namespace from where it was called to see if that variable exists there. \n",
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"\n",
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"However, you should avoid this as much as possible (variables that persist across namespaces are called global variables)."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"functions always return a value -- if one is not explicitly given, then they return None, otherwise, they can return values (even multiple values) of any type"
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"By default, python will let you read from a global, but not update it."
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]
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{
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"metadata": {
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"collapsed": false
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"in function outer = -100.0\n",
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"outside, outer = 1.0\n"
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]
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}
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],
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"source": [
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"outer = 1.0\n",
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"\n",
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"def update():\n",
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" # uncomment this to allow us to access outer in the calling namespace\n",
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" # global outer\n",
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" outer = -100.0\n",
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" print(\"in function outer = {}\".format(outer))\n",
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" \n",
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"update()\n",
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"print(\"outside, outer = {}\".format(outer))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"functions always return a value -- if one is not explicitly given, then they return None, otherwise, they can return values (even multiple values) of any type"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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},
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"name": "stdout",
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"print(a)"
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]
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"None is a special quantity in python (analogous to `null` in some other languages). We can test on `None` -- the preferred manner is to use `is`:"
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]
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},
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"cell_type": "code",
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"we didn't do anything\n"
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]
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}
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],
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"source": [
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"def do_nothing():\n",
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" pass\n",
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"\n",
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"a = do_nothing()\n",
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"if a is None:\n",
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" print(\"we didn't do anything\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## More Complex Functions\n",
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"\n",
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"Here's a more complex example. We return a pair of variables -- in python this is done by packing them into a tuple and then unpacking on the calling end. Also note the _docstring_ here."
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]
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},
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"cell_type": "code",
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"execution_count": 9,
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@@ -162,9 +256,9 @@
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" a, b = b, a+b\n",
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" return result, len(result)\n",
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"\n",
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"list, n = fib2(250)\n",
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"fib, n = fib2(250)\n",
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"print(n)\n",
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"print(list)"
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"print(fib)"
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},
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"source": [
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"it is important to note that python evaluates the optional arguments once--when the function is defined. This means that if you make the default an empty object, for instance, it will persist across all calls.\n",
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"\n",
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"** This is one of the most common errors for beginners **"
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"** This is one of the most common errors for beginners **\n",
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"\n",
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"Here's an example of trying to initialize to an empty list:"
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]
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"cell_type": "markdown",
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"instead do"
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"Notice that each call does not create its own separate list. Instead a single empty list was created when the function was first processed, and this list persists in memory as the default value for the optional argument `L`. \n",
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"\n",
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"If we want a unique list created each time (e.g., a separate place in memory), we instead do"
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"execution_count": 13,
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"metadata": {
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"print(fnew(3))"
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]
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Notice that the same `None` that we saw previously comes into play here. "
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"source": [
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"Lambdas are \"disposible\" functions. These are small, nameless functions that are often used as arguments in other functions.\n",
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"\n",
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"Ex, from the official tutorial:"
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"Ex, from the official tutorial: we have a list of tuples. We want to sort the list based on the second item in the tuple. The `sort` method can take a `key` optional argument that tells us how to interpret the list item for sorting"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {
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"collapsed": true
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},
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"cell_type": "code",
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"execution_count": 15,
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"metadata": {
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"collapsed": false
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"[(4, 'four'), (1, 'one'), (3, 'three'), (2, 'two')]"
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]
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},
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"execution_count": 4,
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"execution_count": 15,
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"metadata": {},
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},
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"cell_type": "code",
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"execution_count": 16,
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" 9216]"
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"execution_count": 16,
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.4.3"
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"version": "3.5.2"
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}
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},
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"nbformat": 4,

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