'''

Python 2.7 Quick Reference

https://github.com/justmarkham/python-reference

By Kevin Markham ([email protected])

http://dataschool.io

Table of Contents:

Imports

Data Types

Math

Comparisons and Boolean Operations

Conditional Statements

Lists

Tuples

Strings

Dictionaries

Sets

Defining Functions

Anonymous (Lambda) Functions

For Loops and While Loops

Comprehensions

Map, Reduce, Filter

'''

### IMPORTS ###

# 'generic import' of math module

import math

math.sqrt(25)

# import a function

from math import sqrt

sqrt(25) # no longer have to reference the module

# import multiple functions at once

from math import cos, floor

# import all functions in a module (generally discouraged)

from os import *

# define an alias

import numpy as np

# show all functions in math module

dir(math)

### DATA TYPES ###

# determine the type of an object

type(2) # returns 'int'

type(2.0) # returns 'float'

type('two') # returns 'str'

type(True) # returns 'bool'

type(None) # returns 'NoneType'

# check if an object is of a given type

isinstance(2.0, int) # returns False

isinstance(2.0, (int, float)) # returns True

# convert an object to a given type

float(2)

int(2.9)

str(2.9)

# zero, None, and empty containers are converted to False

bool(0)

bool(None)

bool('') # empty string

bool([]) # empty list

bool({}) # empty dictionary

# non-empty containers and non-zeros are converted to True

bool(2)

bool('two')

bool([2])

### MATH ###

# basic operations

10 + 4 # add (returns 14)

10 - 4 # subtract (returns 6)

10 * 4 # multiply (returns 40)

10 ** 4 # exponent (returns 10000)

10 / 4 # divide (returns 2 because both types are 'int')

10 / float(4) # divide (returns 2.5)

5 % 4 # modulo (returns 1) - also known as the remainder

# force '/' in Python 2.x to perform 'true division' (unnecessary in Python 3.x)

from __future__ import division

10 / 4 # true division (returns 2.5)

10 // 4 # floor division (returns 2)

### COMPARISONS AND BOOLEAN OPERATIONS ###

# comparisons (these return True)

5 > 3

5 >= 3

5 != 3

5 == 5

# boolean operations (these return True)

5 > 3 and 6 > 3

5 > 3 or 5 < 3

not False

False or not False and True # evaluation order: not, and, or

### CONDITIONAL STATEMENTS ###

# if statement

if x > 0:

print 'positive'

# if/else statement

if x > 0:

print 'positive'

else:

print 'zero or negative'

# if/elif/else statement

if x > 0:

print 'positive'

elif x == 0:

print 'zero'

else:

print 'negative'

# single-line if statement (sometimes discouraged)

if x > 0: print 'positive'

# single-line if/else statement (sometimes discouraged)

# known as a 'ternary operator'

'positive' if x > 0 else 'zero or negative'

### LISTS ###

## properties: ordered, iterable, mutable, can contain multiple data types

# create an empty list (two ways)

empty_list = []

empty_list = list()

# create a list

simpsons = ['homer', 'marge', 'bart']

# examine a list

simpsons[0] # print element 0 ('homer')

len(simpsons) # returns the length (3)

# modify a list (does not return the list)

simpsons.append('lisa') # append element to end

simpsons.extend(['itchy', 'scratchy']) # append multiple elements to end

simpsons.insert(0, 'maggie') # insert element at index 0 (shifts everything right)

simpsons.remove('bart') # searches for first instance and removes it

simpsons.pop(0) # removes element 0 and returns it

del simpsons[0] # removes element 0 (does not return it)

simpsons[0] = 'krusty' # replace element 0

# concatenate lists (slower than 'extend' method)

neighbors = simpsons + ['ned','rod','todd']

# find elements in a list

simpsons.count('lisa') # counts the number of instances

simpsons.index('itchy') # returns index of first instance

# list slicing [start:end:stride]

weekdays = ['mon','tues','wed','thurs','fri']

weekdays[0] # element 0

weekdays[0:3] # elements 0, 1, 2

weekdays[:3] # elements 0, 1, 2

weekdays[3:] # elements 3, 4

weekdays[-1] # last element (element 4)

weekdays[::2] # every 2nd element (0, 2, 4)

weekdays[::-1] # backwards (4, 3, 2, 1, 0)

# alternative method for returning the list backwards

list(reversed(weekdays))

# sort a list in place (modifies but does not return the list)

simpsons.sort()

simpsons.sort(reverse=True) # sort in reverse

simpsons.sort(key=len) # sort by a key

# return a sorted list (but does not modify the original list)

sorted(simpsons)

sorted(simpsons, reverse=True)

sorted(simpsons, key=len)

# insert into an already sorted list, and keep it sorted

num = [10, 20, 40, 50]

from bisect import insort

insort(num, 30)

# create a second reference to the same list

same_num = num

same_num[0] = 0 # modifies both 'num' and 'same_num'

# copy a list (two ways)

new_num = num[:]

new_num = list(num)

# examine objects

id(num) == id(same_num) # returns True

id(num) == id(new_num) # returns False

num is same_num # returns True

num is new_num # returns False

num == same_num # returns True

num == new_num # returns True (their contents are equivalent)

### TUPLES ###

## like lists, but they don't change size

## properties: ordered, iterable, immutable, can contain multiple data types

# create a tuple

digits = (0, 1, 'two') # create a tuple directly

digits = tuple([0, 1, 'two']) # create a tuple from a list

zero = (0,) # trailing comma is required to indicate it's a tuple

# examine a tuple

digits[2] # returns 'two'

len(digits) # returns 3

digits.count(0) # counts the number of instances of that value (1)

digits.index(1) # returns the index of the first instance of that value (1)

# elements of a tuple cannot be modified

digits[2] = 2 # throws an error

# concatenate tuples

digits = digits + (3, 4)

# create a single tuple with elements repeated (also works with lists)

(3, 4) * 2 # returns (3, 4, 3, 4)

# sort a list of tuples

tens = [(20, 60), (10, 40), (20, 30)]

sorted(tens) # sorts by first element in tuple, then second element

# returns [(10, 40), (20, 30), (20, 60)]

# tuple unpacking

bart = ('male', 10, 'simpson') # create a tuple

(sex, age, surname) = bart # assign three values at once

### STRINGS ###

## properties: iterable, immutable

# create a string

s = str(42) # convert another data type into a string

s = 'I like you'

# examine a string

s[0] # returns 'I'

len(s) # returns 10

# string slicing like lists

s[:6] # returns 'I like'

s[7:] # returns 'you'

s[-1] # returns 'u'

# basic string methods (does not modify the original string)

s.lower() # returns 'i like you'

s.upper() # returns 'I LIKE YOU'

s.startswith('I') # returns True

s.endswith('you') # returns True

s.isdigit() # returns False (returns True if every character in the string is a digit)

s.find('like') # returns index of first occurrence (2), but doesn't support regex

s.find('hate') # returns -1 since not found

s.replace('like','love') # replaces all instances of 'like' with 'love'

# split a string into a list of substrings separated by a delimiter

s.split(' ') # returns ['I','like','you']

s.split() # same thing

s2 = 'a, an, the'

s2.split(',') # returns ['a',' an',' the']

# join a list of strings into one string using a delimiter

stooges = ['larry','curly','moe']

' '.join(stooges) # returns 'larry curly moe'

# concatenate strings

s3 = 'The meaning of life is'

s4 = '42'

s3 + ' ' + s4 # returns 'The meaning of life is 42'

s3 + ' ' + str(42) # same thing

# remove whitespace from start and end of a string

s5 = ' ham and cheese '

s5.strip() # returns 'ham and cheese'

# string substitutions: all of these return 'raining cats and dogs'

'raining %s and %s' % ('cats','dogs') # old way

'raining {} and {}'.format('cats','dogs') # new way

'raining {arg1} and {arg2}'.format(arg1='cats',arg2='dogs') # named arguments

# string formatting

# more examples: http://mkaz.com/2012/10/10/python-string-format/

'pi is {:.2f}'.format(3.14159) # returns 'pi is 3.14'

# normal strings versus raw strings

print 'first line\nsecond line' # normal strings allow for escaped characters

print r'first line\nfirst line' # raw strings treat backslashes as literal characters

### DICTIONARIES ###

## properties: unordered, iterable, mutable, can contain multiple data types

## made up of key-value pairs

## keys must be unique, and can be strings, numbers, or tuples

## values can be any type

# create an empty dictionary (two ways)

empty_dict = {}

empty_dict = dict()

# create a dictionary (two ways)

family = {'dad':'homer', 'mom':'marge', 'size':6}

family = dict(dad='homer', mom='marge', size=6)

# convert a list of tuples into a dictionary

list_of_tuples = [('dad','homer'), ('mom','marge'), ('size', 6)]

family = dict(list_of_tuples)

# examine a dictionary

family['dad'] # returns 'homer'

len(family) # returns 3

family.keys() # returns list: ['dad', 'mom', 'size']

family.values() # returns list: ['homer', 'marge', 6]

family.items() # returns list of tuples:

# [('dad', 'homer'), ('mom', 'marge'), ('size', 6)]

'mom' in family # returns True

'marge' in family # returns False (only checks keys)

# modify a dictionary (does not return the dictionary)

family['cat'] = 'snowball' # add a new entry

family['cat'] = 'snowball ii' # edit an existing entry

del family['cat'] # delete an entry

family['kids'] = ['bart', 'lisa'] # value can be a list

family.pop('dad') # removes an entry and returns the value ('homer')

family.update({'baby':'maggie', 'grandpa':'abe'}) # add multiple entries

# accessing values more safely with 'get'

family['mom'] # returns 'marge'

family.get('mom') # same thing

family['grandma'] # throws an error

family.get('grandma') # returns None

family.get('grandma', 'not found') # returns 'not found' (the default)

# accessing a list element within a dictionary

family['kids'][0] # returns 'bart'

family['kids'].remove('lisa') # removes 'lisa'

# string substitution using a dictionary

'youngest child is %(baby)s' % family # returns 'youngest child is maggie'

### SETS ###

## like dictionaries, but with keys only (no values)

## properties: unordered, iterable, mutable, can contain multiple data types

## made up of unique elements (strings, numbers, or tuples)

# create an empty set

empty_set = set()

# create a set

languages = {'python', 'r', 'java'} # create a set directly

snakes = set(['cobra', 'viper', 'python']) # create a set from a list

# examine a set

len(languages) # returns 3

'python' in languages # returns True

# set operations

languages & snakes # returns intersection: {'python'}

languages | snakes # returns union: {'cobra', 'r', 'java', 'viper', 'python'}

languages - snakes # returns set difference: {'r', 'java'}

snakes - languages # returns set difference: {'cobra', 'viper'}

# modify a set (does not return the set)

languages.add('sql') # add a new element

languages.add('r') # try to add an existing element (ignored, no error)

languages.remove('java') # remove an element

languages.remove('c') # try to remove a non-existing element (throws an error)

languages.discard('c') # removes an element if present, but ignored otherwise

languages.pop() # removes and returns an arbitrary element

languages.clear() # removes all elements

languages.update('go', 'spark') # add multiple elements (can also pass a list or set)

# get a sorted list of unique elements from a list

sorted(set([9, 0, 2, 1, 0])) # returns [0, 1, 2, 9]

### DEFINING FUNCTIONS ###

# define a function with no arguments and no return values

def print_text():

print 'this is text'

# call the function

print_text()

# define a function with one argument and no return values

def print_this(x):

print x

# call the function

print_this(3) # prints 3

n = print_this(3) # prints 3, but doesn't assign 3 to n

# because the function has no return statement

# define a function with one argument and one return value

def square_this(x):

return x**2

# include an optional docstring to describe the effect of a function

def square_this(x):

"""Return the square of a number."""

return x**2

# call the function

square_this(3) # prints 9

var = square_this(3) # assigns 9 to var, but does not print 9

# define a function with two 'positional arguments' (no default values) and

# one 'keyword argument' (has a default value)

def calc(a, b, op='add'):

if op == 'add':

return a + b

elif op == 'sub':

return a - b

else:

print 'valid operations are add and sub'

# call the function

calc(10, 4, op='add') # returns 14

calc(10, 4, 'add') # also returns 14: unnamed arguments are inferred by position

calc(10, 4) # also returns 14: default for 'op' is 'add'

calc(10, 4, 'sub') # returns 6

calc(10, 4, 'div') # prints 'valid operations are add and sub'

# use 'pass' as a placeholder if you haven't written the function body

def stub():

pass

# return two values from a single function

def min_max(nums):

return min(nums), max(nums)

# return values can be assigned to a single variable as a tuple

nums = [1, 2, 3]

min_max_num = min_max(nums) # min_max_num = (1, 3)

# return values can be assigned into multiple variables using tuple unpacking

min_num, max_num = min_max(nums) # min_num = 1, max_num = 3

### ANONYMOUS (LAMBDA) FUNCTIONS ###

## primarily used to temporarily define a function for use by another function

# define a function the "usual" way

def squared(x):

return x**2

# define an identical function using lambda

squared = lambda x: x**2

# sort a list of strings by the last letter (without using lambda)

simpsons = ['homer', 'marge', 'bart']

def last_letter(word):

return word[-1]

sorted(simpsons, key=last_letter)

# sort a list of strings by the last letter (using lambda)

sorted(simpsons, key=lambda word: word[-1])

### FOR LOOPS AND WHILE LOOPS ###

# range returns a list of integers

range(0, 3) # returns [0, 1, 2]: includes first value but excludes second value

range(3) # same thing: starting at zero is the default

range(0, 5, 2) # returns [0, 2, 4]: third argument specifies the 'stride'

# for loop (not recommended)

fruits = ['apple', 'banana', 'cherry']

for i in range(len(fruits)):

print fruits[i].upper()

# alternative for loop (recommended style)

for fruit in fruits:

print fruit.upper()

# use xrange when iterating over a large sequence to avoid actually creating the integer list in memory

for i in xrange(10**6):

pass

# iterate through two things at once (using tuple unpacking)

family = {'dad':'homer', 'mom':'marge', 'size':6}

for key, value in family.items():

print key, value

# use enumerate if you need to access the index value within the loop

for index, fruit in enumerate(fruits):

print index, fruit

# for/else loop

for fruit in fruits:

if fruit == 'banana':

print "Found the banana!"

break # exit the loop and skip the 'else' block

else:

# this block executes ONLY if the for loop completes without hitting 'break'

print "Can't find the banana"

# while loop

count = 0

while count < 5:

print "This will print 5 times"

count += 1 # equivalent to 'count = count + 1'

### COMPREHENSIONS ###

# for loop to create a list of cubes

nums = [1, 2, 3, 4, 5]

cubes = []

for num in nums:

cubes.append(num**3)

# equivalent list comprehension

cubes = [num**3 for num in nums] # [1, 8, 27, 64, 125]

# for loop to create a list of cubes of even numbers

cubes_of_even = []

for num in nums:

if num % 2 == 0:

cubes_of_even.append(num**3)

# equivalent list comprehension

# syntax: [expression for variable in iterable if condition]

cubes_of_even = [num**3 for num in nums if num % 2 == 0] # [8, 64]

# for loop to cube even numbers and square odd numbers

cubes_and_squares = []

for num in nums:

if num % 2 == 0:

cubes_and_squares.append(num**3)

else:

cubes_and_squares.append(num**2)

# equivalent list comprehension (using a ternary expression)

# syntax: [true_condition if condition else false_condition for variable in iterable]

cubes_and_squares = [num**3 if num % 2 == 0 else num**2 for num in nums] # [1, 8, 9, 64, 25]

# for loop to flatten a 2d-matrix

matrix = [[1, 2], [3, 4]]

items = []

for row in matrix:

for item in row:

items.append(item)

# equivalent list comprehension

items = [item for row in matrix

for item in row] # [1, 2, 3, 4]

# set comprehension

fruits = ['apple', 'banana', 'cherry']

unique_lengths = {len(fruit) for fruit in fruits} # {5, 6}

# dictionary comprehension

fruit_lengths = {fruit:len(fruit) for fruit in fruits} # {'apple': 5, 'banana': 6, 'cherry': 6}

fruit_indices = {fruit:index for index, fruit in enumerate(fruits)} # {'apple': 0, 'banana': 1, 'cherry': 2}

### MAP, REDUCE, FILTER ###

# 'map' applies a function to every element of a sequence and returns a list

simpsons = ['homer', 'marge', 'bart']

map(len, simpsons) # returns [5, 5, 4]

map(lambda word: word[-1], simpsons) # returns ['r', 'e', 't']

# equivalent list comprehensions

[len(word) for word in simpsons]

[word[-1] for word in simpsons]

# 'reduce' applies a binary function to the first two elements of a sequence,

# then repeats with the result and the next element, through the end of the sequence

reduce(lambda x, y: x + y, range(4)) # (((0+1)+2)+3) = 6

# 'filter' returns a sequence containing the items from the original sequence

# for which the condition is True

filter(lambda x: x % 2 == 0, range(5)) # returns [0, 2, 4]