Intro to Python
Class 3
Review
- Functions - calls, definitions, returns, arguments
- Conditions - if, elif, else
- Loops - while, for
What we will cover today
- More Functions
- Method calls
- Lists and dictionaries
- Python builtin functions
More with Functions
Functions can also call other functions.
One can use this to break up tasks into small pieces that rely on others to do their work.
from math import sqrt
def absolute_difference(value_a, value_b):
return abs(value_a - value_b)
def find_width_height(x1, y1, x2, y2):
width = absolute_difference(x1, x2)
height = absolute_difference(y1, y2)
return width, height
def get_hypotenuse(a, b):
return sqrt(a ** 2 + b ** 2)
def get_area_rectangle(width, height):
return width * height
def print_area_and_hypotenuse(x1, y1, x2, y2):
width, height = find_width_height(x1, y1, x2, y2)
area = get_area_rectangle(width, height)
hypotenuse = get_hypotenuse(width, height)
print 'Area of the rectangle is:'
print area
print 'The diagonal of the rectangle is:'
print hypotenuse
Function Composition
Function composition is when the output of one function acts as the input of another
from math import sqrt
def find_width_height(x1, y1, x2, y2):
return abs(x1 - x2), abs(y1 - y2)
def get_hypotenuse(a, b):
return sqrt(a ** 2 + b ** 2)
def print_hypotenuse(x1, y1, x2, y2):
print 'The diagonal of the rectangle is:'
print get_hypotenuse(find_width_height(x1, y1, x2, y2))
# f(g(x))
# is the same as:
# y = g(x)
# f(y)
Method Calls
A method is like a function but it is "bound" to an object.
For example, the integers and strings we've been using have methods attached to them
We can use the dir() function to see the methods of an object and help() to see what they do.
a = 4
print dir(a)
name = 'caleb'
sentence = 'the quick brown fox did the thing with the thing'
print dir(name)
print name.capitalize()
print sentence.count('the')
help(name.upper)
Let's Develop It
Open a Python shell and define a string varaible
Use 'dir(string_variable)' and the help() function to explore the various methods
Hint: Like functions, some methods take arguments and others don't
Hint: Use help() on a method. It will tell you the arguments to use and the expected behavior
Hint: Don't be afraid of errors. They seem to be in a foreign language but they are there to help you. Read them carefully.
Lists
A list is an ordered collection of elements
In Python, a list is defined using `[ ]` with elements separated by commas, as in the following example
words = ['list', 'of', 'strings']
A list can, but doesn't have to be of all one type. A list of one type is homogenous as opposed to a list of multiple types, which is heterogeneous.
# heterogenous list
words = [0, 'list', 'of', 3, 'strings', 'and', 'numbers']
List Methods
Lists have several methods, the most useful of which is `append`
A list can be created as an empty list and have values added to it with `append`
to_dos = []
to_dos.append('buy soy milk')
to_dos.append('install git')
print to_dos
Therefore, lists are mutable
This means that a list can change values during the duration of a program
Iteration
Lists and many other collections are iterable.
Once defined, we can iterate on them, performing an action with each element
shipping_cost = 2.5
prices = [3, 4, 5.25]
costs = []
for price in prices:
costs.append(price + shipping_cost)
for cost in costs:
print cost
Indexing
An element can also be obtained from a list through indexing
This allows us to obtain an element without iterating through the entire collection if we just want one value.
To index on a collection, follow it immediately with `[index]`. (index here is a number, variable or expression)
numbers = [10, 20, 30]
print numbers[0]
Indexing continued
Lists and other collections in Python are zero indexed. This means that the number 0 refers to first element in the list.
to_dos = [
'install git', 'read email', 'make lunch',
]
print to_dos[0]
print to_dos[1]
print to_dos[-1]
Negative numbers mean "go back from the end this many". e.g. -1 is the last element, -2 is the penultimate
An IndexError results if an index exceeds the length of the list minus 1
Dictionaries
A dictionary (sometimes called a "hashmap") is a collection of key/value pairs, defined with '{}'
menu_categories = {
'food': 'stuff you eat',
'beverage': 'stuff you drink',
}
Think of words in a dictionary. The words are keys and the definitions are values.
This dictionary would be indexed with strings such as 'food' and 'beverage' instead of integers like in a list
Indexing on Dictionaries
Dictionaries aren't literally just for definitions. They represent a group of mappings. A mapping might be: menu items -> costs.
We can also index on dictionaries.
The most common indexes are strings, but they can be whatever type the keys are.
menu = {
'tofu': 4,
}
tofu_cost = menu['tofu']
Indexing on a key that doesn't exist results in a KeyError
If you aren't certain a key is present, you can use the 'get' method
Dictionary Methods
Some of the most essential methods are 'keys', 'values' and 'items'
menu = {
'tofu': 4,
'pizza': 8,
'baguette': 3,
}
print menu.keys()
print menu.values()
print menu.items()
print menu.get('pizza')
print menu.get('water')
print menu.get('juice', 5)
'get' will return None if the key isn't present or a default value if provided.
Tuples
Tuples are like lists, but they are immutable. They are particularly good at storing collections of a fixed and predictable size. Use '()' to define tuples
An x, y coordinate pair, or the RGB values of a color are good candidates for tuples.
point = (0, 1)
x = point_a[0]
y = point_a[1]
# or, even better
point = (0, 1)
x, y = point_a
Tuple Example
Remember the geometry functions earlier? Some of these can be simplified using tuples
def find_width_height(point_a, point_b):
x_a, y_a = point_a
x_b, y_b = point_b
return abs(x_a - x_b), abs(y_a - y_b)
point_a = (5, 0)
point_b = (10, 4)
dimensions = find_width_height(point_a, point_b)
N.B. - In the example, the function returns a tuple. In some contexts the parenthesis around a tuple are not strictly required
Sets
Sets are unordered collections whose elements are unique. Therefore, adding a value to a set that already has it, does nothing.
Sets can be created with comma separated elements enclosed in '{}' in Python 2.7. Very often, one will make a list and use the set() function
set_a = set([0, 3, 7])
set_b = set([0, 4, 7])
# .add() is like .append() but for sets
print set_a.add(4)
# or in 2.7
set_a = {0, 3, 7} # and so on
Sets have nice methods for reasoning about their relationship to other sets. (Think Venn Diagram)
The in operator
The `in` operator is used to determine if an element is in a given collection
For dictionaries, the keys are searched for the element.
color = (255, 255, 0)
if 0 in color:
print '0 is in the color'
menu = {'tofu': 4}
print 'tofu' in menu
names = ['Mary', 'Martha', 'George']
george_present = 'George' in names
Let's Develop It
Write a program that opens a text file and does some processing.
- The program should take a word as input and determine if the word appears in the file
- The program should use at least one function to do its work and you should be able to import this function in a Python shell and call it with a word and filename
- Use the functions from helpers.py to help with reading in the lines and/or words of the file
- Download a book in plain text from Project Gutenburg and put it into the same directory as your python file.
The next slide has some code and other resources that should help you get started
Let's Develop It- Example Code
from helpers import generate_cleaned_lines
def is_word_in_file(word, filename):
for line in generate_cleaned_lines(filename):
# line will be a string of each line of the file in order
# Your code goes here.
# Your code should do something with the word and line variables and assign the value to a variable for returning
input_word = raw_input("Enter a word to search for:")
answer = is_word_in_file(input_word, 'pride.txt')
# Display the answer in some meaningful way
I have used Pride and Prejudice from Project Gutenburg with my example code. You can click this link and copy/paste the text into a new text file called 'pride.txt' and save it in the same folder as your code
Lists of ... Lists
Lists can contain not only numbers or strings, but also other lists.
Such a structure is said to be nested
The following is a list of lists:
game_board = [
['O', 'X', ' '],
[' ', 'X', ' '],
[' ', ' ', ' '],
]
This can be indexed successively with game_board[0][1]
Nested Lists continued
A list can be appended to a list as well
mary_to_dos = ['eat', 'work', 'pick up laundry', 'care for baby', 'sleep']
fran_to_dos = ['eat', 'work', 'call plumber', 'sleep']
baby_to_dos = ['eat', 'sleep']
all_to_dos = []
all_to_dos.append(mary_to_dos)
all_to_dos.append(fran_to_dos)
all_to_dos.append(baby_to_dos)
print all_to_dos
for to_dos in all_to_dos:
for to_do in to_dos:
print to_do
What if we want to flatten the to do's?
What if we want the to do's to be unique?
Lists of Dictionaries
One of the most common and useful nested data structures, is a list of dictionaries
card_a = {
'suit': 'spades',
'number': 4,
}
card_b = {
'suit': 'hearts',
'number': 8,
}
hand = [card_a, card_b]
print 'The hand contains:'
for card in hand:
print 'A', card['number'], 'of', card['suit']
Dictionary of Lists
A dictionary can also contain values that are themselves other collections, such as lists.
Let's revisit the group of to do lists and find a better representation:
mary_to_dos = ['eat', 'work', 'pick up laundry', 'care for baby', 'sleep']
fran_to_dos = ['eat', 'work', 'call plumber', 'sleep']
baby_to_dos = ['eat', 'sleep']
all_to_dos = {
'mary': mary_to_dos,
'fran': fran_to_dos,
'baby': baby_to_dos,
}
for name, to_dos in all_to_dos.items():
print name, 'needs to: ', to_dos
# Changing this later can be accomplished with
all_to_dos['baby'].append('cry')
Now the to do lists can be indexed or modified by name
Means of Combination
Lists, dictionaries, sets, tuples, and other collections are all a means of combination.
They can be freely combined to create the data structure needed for a particular problem
Eg. A list of dictionaries with lists
all_tweets = [
{
'author': 'mary',
'handle': '@hadalittlelamb',
'date': '2013-01-22',
'tweets': [
'at Loco Pops enjoying a Raspberry Sage popsicle',
'Learning Python is so much fun',
],
},
]
Builtins for collections
Python provides several functions that help us work with these collections.
| len() | Given a collection, return its length |
| range() | Create a list of integers in the range provided. |
| sorted() | Given a collection, returns a sorted copy of that collection |
| enumerate() | Returns a list of (index, element) from the list |
| zip() | Given one or more iterables, returns a list of tuples with an element from each iterable |
Examples of using Builtins
# Using len() - Determines length
print len([1, 2])
# range() - Quickly creates a list of integers
print range(5)
print range(5, 10)
print range(0, 10, 2)
print range(9, -1, -1)
# sorted() - Sort a given list
grades = [93, 100, 60]
grades = sorted(grades)
print grades
Builtins Examples continued
# enumerate() - Obtain the index of the element in the loop
print 'To Do:'
to_dos = ['work', 'sleep', 'work']
for index, item in enumerate(to_dos):
print '{0}. {1}'.format(index + 1, item)
print list(enumerate(to_dos))
# zip()
widths = [10, 15, 20]
heights = [5, 8, 12]
for width, height in zip(widths, heights):
print 'Area is {0}'.format(width * height)
Let's Develop It
Write a program that expands on your previous one. If it is unfinished, feel free to finish the original exercise first. To expand on it, choose one of the following:
- Determine how many times the user provided word appears in the file and/or what lines it appears on
- Change the program so that it counts the number of times each word occurs. E.g. A dictionary of all words in the file, whose values are a count of their occurrences
- Use boilerplate.py to help you improve the reusability of the program. (The comments in that file should explain the how and why)
Resources for this and the previous exercise are provided on the next slide for convenience
Resources
- Helper functions are in helpers.py
- Download a book in plain text from Project Gutenburg and put it into the same directory as your python file.
- You can use this link for Pride and Prejudice. Click this link and copy/paste the text into a new text file called 'pride.txt' and save it in the same folder as your code
from helpers import generate_cleaned_lines
def is_word_in_file(word, filename):
for line in generate_cleaned_lines(filename):
# line will be a string of each line of the file in order
# Your code goes here. Do something with the word and line variables
return result
input_word = raw_input("Enter a word to search for:")
answer = is_word_in_file(input_word, 'pride.txt')
# Display the answer in some meaningful way