Learn Python X in Y

Single line comments start with a number symbol.

""" Multiline strings can be written
using three "s, and are often used
as comments
"""

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1. Primitive Datatypes and Operators

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You have numbers

3 # => 3

Math is what you would expect

1 + 1 # => 2
8 - 1 # => 7
10 * 2 # => 20
35 / 5 # => 7

Division is a bit tricky. It is integer division and floors the results

automatically.

5 / 2 # => 2

To fix division we need to learn about floats.

2.0 # This is a float
11.0 / 4.0 # => 2.75 ahhh...much better

Result of integer division truncated down both for positive and negative.

5 // 3 # => 1
5.0 // 3.0 # => 1.0 # works on floats too
-5 // 3 # => -2
-5.0 // 3.0 # => -2.0

Modulo operation

7 % 3 # => 1

Exponentiation (x to the yth power)

2**4 # => 16

Enforce precedence with parentheses

(1 + 3) * 2 # => 8

Boolean Operators

Note "and" and "or" are case-sensitive

True and False #=> False
False or True #=> True

Note using Bool operators with ints

0 and 2 #=> 0
-5 or 0 #=> -5
0 == False #=> True
2 == True #=> False
1 == True #=> True

negate with not

not True # => False
not False # => True

Equality is ==

1 == 1 # => True
2 == 1 # => False

Inequality is !=

1 != 1 # => False
2 != 1 # => True

More comparisons

1 < 10 # => True
1 > 10 # => False
2 <= 2 # => True
2 >= 2 # => True

Comparisons can be chained!

1 < 2 < 3 # => True
2 < 3 < 2 # => False

Strings are created with " or '

"This is a string."
'This is also a string.'

Strings can be added too!

"Hello " + "world!" # => "Hello world!"

... or multiplied

"Hello" * 3 # => "HelloHelloHello"

A string can be treated like a list of characters

"This is a string"[0] # => 'T'

% can be used to format strings, like this:

"%s can be %s" % ("strings", "interpolated")

A newer way to format strings is the format method.

This method is the preferred way

"{0} can be {1}".format("strings", "formatted")

You can use keywords if you don't want to count.

"{name} wants to eat {food}".format(name="Bob", food="lasagna")

None is an object

None # => None

Don't use the equality "==" symbol to compare objects to None

Use "is" instead

"etc" is None # => False
None is None # => True

The 'is' operator tests for object identity. This isn't

very useful when dealing with primitive values, but is

very useful when dealing with objects.

None, 0, and empty strings/lists all evaluate to False.

All other values are True

bool(0) # => False
bool("") # => False

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2. Variables and Collections

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Python has a print statement, in all 2.x versions but removed from 3.

print "I'm Python. Nice to meet you!"

Python also has a print function, available in versions 2.7 and 3...

but for 2.7 you need to add the import (uncommented):

from future import print_function

print("I'm also Python! ")

No need to declare variables before assigning to them.

some_var = 5 # Convention is to use lower_case_with_underscores
some_var # => 5

Accessing a previously unassigned variable is an exception.

See Control Flow to learn more about exception handling.

some_other_var # Raises a name error

if can be used as an expression

"yahoo!" if 3 > 2 else 2 # => "yahoo!"

Lists store sequences

li = []

You can start with a prefilled list

other_li = [4, 5, 6]

Add stuff to the end of a list with append

li.append(1) # li is now [1]
li.append(2) # li is now [1, 2]
li.append(4) # li is now [1, 2, 4]
li.append(3) # li is now [1, 2, 4, 3]

Remove from the end with pop

li.pop() # => 3 and li is now [1, 2, 4]

Let's put it back

li.append(3) # li is now [1, 2, 4, 3] again.

Access a list like you would any array

li[0] # => 1

Assign new values to indexes that have already been initialized with =

li[0] = 42
li[0] # => 42
li[0] = 1 # Note: setting it back to the original value

Look at the last element

li[-1] # => 3

Looking out of bounds is an IndexError

li[4] # Raises an IndexError

You can look at ranges with slice syntax.

(It's a closed/open range for you mathy types.)

li[1:3] # => [2, 4]

Omit the beginning

li[2:] # => [4, 3]

Omit the end

li[:3] # => [1, 2, 4]

Select every second entry

li[::2] # =>[1, 4]

Revert the list

li[::-1] # => [3, 4, 2, 1]

Use any combination of these to make advanced slices

li[start:end:step]

Remove arbitrary elements from a list with "del"

del li[2] # li is now [1, 2, 3]

You can add lists

li + other_li # => [1, 2, 3, 4, 5, 6]

Note: values for li and for other_li are not modified.

Concatenate lists with "extend()"

li.extend(other_li) # Now li is [1, 2, 3, 4, 5, 6]

Check for existence in a list with "in"

1 in li # => True

Examine the length with "len()"

len(li) # => 6

Tuples are like lists but are immutable.

tup = (1, 2, 3)
tup[0] # => 1
tup[0] = 3 # Raises a TypeError

You can do all those list thingies on tuples too

len(tup) # => 3
tup + (4, 5, 6) # => (1, 2, 3, 4, 5, 6)
tup[:2] # => (1, 2)
2 in tup # => True

You can unpack tuples (or lists) into variables

a, b, c = (1, 2, 3) # a is now 1, b is now 2 and c is now 3

Tuples are created by default if you leave out the parentheses

d, e, f = 4, 5, 6

Now look how easy it is to swap two values

e, d = d, e # d is now 5 and e is now 4

Dictionaries store mappings

empty_dict = {}

Here is a prefilled dictionary

filled_dict = {"one": 1, "two": 2, "three": 3}

Look up values with []

filled_dict["one"] # => 1

Get all keys as a list with "keys()"

filled_dict.keys() # => ["three", "two", "one"]

Note - Dictionary key ordering is not guaranteed.

Your results might not match this exactly.

Get all values as a list with "values()"

filled_dict.values() # => [3, 2, 1]

Note - Same as above regarding key ordering.

Check for existence of keys in a dictionary with "in"

"one" in filled_dict # => True
1 in filled_dict # => False

Looking up a non-existing key is a KeyError

filled_dict["four"] # KeyError

Use "get()" method to avoid the KeyError

filled_dict.get("one") # => 1
filled_dict.get("four") # => None

The get method supports a default argument when the value is missing

filled_dict.get("one", 4) # => 1
filled_dict.get("four", 4) # => 4

note that filled_dict.get("four") is still => None

(get doesn't set the value in the dictionary)

set the value of a key with a syntax similar to lists

filled_dict["four"] = 4 # now, filled_dict["four"] => 4

"setdefault()" inserts into a dictionary only if the given key isn't present

filled_dict.setdefault("five", 5) # filled_dict["five"] is set to 5
filled_dict.setdefault("five", 6) # filled_dict["five"] is still 5

Sets store ... well sets (which are like lists but can contain no duplicates)

empty_set = set()

Initialize a "set()" with a bunch of values

some_set = set([1, 2, 2, 3, 4]) # some_set is now set([1, 2, 3, 4])

order is not guaranteed, even though it may sometimes look sorted

another_set = set([4, 3, 2, 2, 1]) # another_set is now set([1, 2, 3, 4])

Since Python 2.7, {} can be used to declare a set

filled_set = {1, 2, 2, 3, 4} # => {1, 2, 3, 4}

Add more items to a set

filled_set.add(5) # filled_set is now {1, 2, 3, 4, 5}

Do set intersection with &

other_set = {3, 4, 5, 6}
filled_set & other_set # => {3, 4, 5}

Do set union with |

filled_set | other_set # => {1, 2, 3, 4, 5, 6}

Do set difference with -

{1, 2, 3, 4} - {2, 3, 5} # => {1, 4}

Check for existence in a set with in

2 in filled_set # => True
10 in filled_set # => False

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3. Control Flow

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Let's just make a variable

some_var = 5

Here is an if statement. Indentation is significant in python!

prints "some_var is smaller than 10"

if some_var > 10:
print("some_var is totally bigger than 10.")
elif some_var < 10: # This elif clause is optional.
print("some_var is smaller than 10.")
else: # This is optional too.
print("some_var is indeed 10.")

"""
For loops iterate over lists
prints:
dog is a mammal
cat is a mammal
mouse is a mammal
"""
for animal in ["dog", "cat", "mouse"]:
# You can use % to interpolate formatted strings
print("%s is a mammal" % animal)

"""
"range(number)" returns a list of numbers
from zero to the given number
prints:
0
1
2
3
"""
for i in range(4):
print(i)

"""
While loops go until a condition is no longer met.
prints:
0
1
2
3
"""
x = 0
while x < 4:
print(x)
x += 1 # Shorthand for x = x + 1

Handle exceptions with a try/except block

Works on Python 2.6 and up:

try:
# Use "raise" to raise an error
raise IndexError("This is an index error")
except IndexError as e:
pass # Pass is just a no-op. Usually you would do recovery here.
except (TypeError, NameError):
pass # Multiple exceptions can be handled together, if required.
else: # Optional clause to the try/except block. Must follow all except blocks
print "All good!" # Runs only if the code in try raises no exceptions

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4. Functions

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Use "def" to create new functions

def add(x, y):
print("x is %s and y is %s" % (x, y))
return x + y # Return values with a return statement

Calling functions with parameters

add(5, 6) # => prints out "x is 5 and y is 6" and returns 11

Another way to call functions is with keyword arguments

add(y=6, x=5) # Keyword arguments can arrive in any order.

You can define functions that take a variable number of

positional args, which will be interpreted as a tuple if you do not use the *

def varargs(*args):
return args

varargs(1, 2, 3) # => (1, 2, 3)

You can define functions that take a variable number of

keyword args, as well, which will be interpreted as a map if you do not use **

def keyword_args(**kwargs):
return kwargs

Let's call it to see what happens

keyword_args(big="foot", loch="ness") # => {"big": "foot", "loch": "ness"}

You can do both at once, if you like

def all_the_args(*args, **kwargs):
print(args)
print(kwargs)
"""
all_the_args(1, 2, a=3, b=4) prints:
(1, 2)
{"a": 3, "b": 4}
"""

When calling functions, you can do the opposite of args/kwargs!

Use * to expand positional args and use ** to expand keyword args.

args = (1, 2, 3, 4)
kwargs = {"a": 3, "b": 4}
all_the_args(args) # equivalent to foo(1, 2, 3, 4)
all_the_args(kwargs) # equivalent to foo(a=3, b=4)
all_the_args(args, **kwargs) # equivalent to foo(1, 2, 3, 4, a=3, b=4)

you can pass args and kwargs along to other functions that take args/kwargs

by expanding them with * and ** respectively

def pass_all_the_args(*args, kwargs):
all_the_args(args, kwargs)
print varargs(args)
print keyword_args(kwargs)

Function Scope

x = 5

def setX(num):
# Local var x not the same as global variable x
x = num # => 43
print x # => 43

def setGlobalX(num):
global x
print x # => 5
x = num # global var x is now set to 6
print x # => 6

setX(43)
setGlobalX(6)

Python has first class functions

def create_adder(x):
def adder(y):
return x + y
return adder

add_10 = create_adder(10)
add_10(3) # => 13

There are also anonymous functions

(lambda x: x > 2)(3) # => True

There are built-in higher order functions

map(add_10, [1, 2, 3]) # => [11, 12, 13]
filter(lambda x: x > 5, [3, 4, 5, 6, 7]) # => [6, 7]

We can use list comprehensions for nice maps and filters

[add_10(i) for i in [1, 2, 3]] # => [11, 12, 13]
[x for x in [3, 4, 5, 6, 7] if x > 5] # => [6, 7]

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5. Classes

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We subclass from object to get a class.

class Human(object):

# A class attribute. It is shared by all instances of this class
species = "H. sapiens"

# Basic initializer, this is called when this class is instantiated.
# Note that the double leading and trailing underscores denote objects
# or attributes that are used by python but that live in user-controlled
# namespaces. You should not invent such names on your own.
def __init__(self, name):
    # Assign the argument to the instance's name attribute
    self.name = name

# An instance method. All methods take "self" as the first argument
def say(self, msg):
    return "%s: %s" % (self.name, msg)

# A class method is shared among all instances
# They are called with the calling class as the first argument
@classmethod
def get_species(cls):
    return cls.species

# A static method is called without a class or instance reference
@staticmethod
def grunt():
    return "*grunt*"

Instantiate a class

i = Human(name="Ian")
print(i.say("hi")) # prints out "Ian: hi"

j = Human("Joel")
print(j.say("hello")) # prints out "Joel: hello"

Call our class method

i.get_species() # => "H. sapiens"

Change the shared attribute

Human.species = "H. neanderthalensis"
i.get_species() # => "H. neanderthalensis"
j.get_species() # => "H. neanderthalensis"

Call the static method

Human.grunt() # => "grunt"

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6. Modules

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You can import modules

import math
print(math.sqrt(16)) # => 4

You can get specific functions from a module

from math import ceil, floor
print(ceil(3.7)) # => 4.0
print(floor(3.7)) # => 3.0

You can import all functions from a module.

Warning: this is not recommended

from math import *

You can shorten module names

import math as m
math.sqrt(16) == m.sqrt(16) # => True

you can also test that the functions are equivalent

from math import sqrt
math.sqrt == m.sqrt == sqrt # => True

Python modules are just ordinary python files. You

can write your own, and import them. The name of the

module is the same as the name of the file.

You can find out which functions and attributes

defines a module.

import math
dir(math)

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7. Advanced

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Generators help you make lazy code

def double_numbers(iterable):
for i in iterable:
yield i + i

A generator creates values on the fly.

Instead of generating and returning all values at once it creates one in each

iteration. This means values bigger than 15 wont be processed in

double_numbers.

Note xrange is a generator that does the same thing range does.

Creating a list 1-900000000 would take lot of time and space to be made.

xrange creates an xrange generator object instead of creating the entire list

like range does.

We use a trailing underscore in variable names when we want to use a name that

would normally collide with a python keyword

xrange_ = xrange(1, 900000000)

will double all numbers until a result >=30 found

for i in double_numbers(xrange_):
print(i)
if i >= 30:
break

Decorators

in this example beg wraps say

Beg will call say. If say_please is True then it will change the returned

message

from functools import wraps

def beg(target_function):
@wraps(target_function)
def wrapper(*args, *kwargs):
msg, say_please = target_function(args, **kwargs)
if say_please:
return "{} {}".format(msg, "Please! I am poor :(")
return msg

return wrapper

@beg
def say(say_please=False):
msg = "Can you buy me a beer?"
return msg, say_please

print(say()) # Can you buy me a beer?
print(say(say_please=True)) # Can you buy me a beer? Please! I am poor :(