learnxinyminutes-docs/python.html.markdown

language	author	author_url
python	Louie Dinh	http://ldinh.ca

Python was created by Guido Van Rossum in the early 90's. It is now one of the most popular languages in existence. I fell in love with Python for it's syntactic clarity. It's basically executable pseudocode.

Note: This article applies to Python 2.7 specifically, but should be applicable to Python 2.x. Look for another tour of Python 3 soon!

# Single line comments start with a hash.
""" Multiline comments can we written
    using three "'s
"""

####################################################
## 1. Primitive Datatypes and Operators
####################################################

# You have numbers
3 #=> 3

# Math is what you would expect
1 + 1 #=> 2
8 - 1 #=> 9
10 * 2 #=> 20
35 / 5 #=> 7

# Division is a bit tricky. It is integer division and floors the results
# automatically.
11 / 4 #=> 2

# Enforce precedence with parentheses
(1 + 3) * 2 #=> 8

# Boolean values are primitives
True
False

# negate with not
not True #=> False
not False #=> True


# Equality is ==
1 == 1 #=> True
2 == 1 #=> False

# Strings are created with " or '
"This is a string."
'This is also a string.'

# Strings can be added too!
"Hello " + "world!" #=> "Hello world!"

# A string can be treated like a list of characters
"This is a string"[0] #=> 'T'

# None is an object
None #=> None


####################################################
## 2. Variables and Collections
####################################################

# Printing is pretty easy
print "I'm Python. Nice to meet you!"


# 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
some_other_var  # Will raise a NameError


# 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]

# Access a list like you would any array
li[0] #=> 1
# Looking out of bounds is an IndexError
li[4] # Raises an IndexError

# Remove 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: li and other_li is left alone

# 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


# 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
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
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


# Sets store ... well sets
empty_set = set()
# Initialize a set with a bunch of values
filled_set = set([1,2,2,3,4]) # filled_set is now set([1, 2, 3, 4])

# Add more items to a set
filled_set.add(5) # filled_set is now set([1, 2, 3, 4, 5])

# Do set intersection with &
other_set = set([3, 4, 5 ,6])
filled_set & other_set #=> set([3, 4, 5])

# Do set union with |
filled_set | other_set #=> set([1, 2, 3, 4, 5, 6])

# Check for existence in a set with in
2 in filled_set #=> True
10 in filled_set #=> False


####################################################
## 3. Control Flow
####################################################

# 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 

"""
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
try:
    raise IndexError("This is an index error")  # Use raise to raise an error
except IndexError as e:
    pass    # Pass is just a no-op. Usually you would do recovery here.


####################################################
## 4. Functions
####################################################

# 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) #=> 11 and prints out "x is 5 and y is 6"
# 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 arguments
def varargs(*args):
    return args

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


# You can define functions that take a variable number of keyword arguments
def keyword_args(**kwargs):
    return kwargs

# Let's call it to see what happens
keyword_args(big="foot", loch="ness") #=> {"big": "foot", "loch": "ness"}


# 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]

####################################################
## 5. Classes
####################################################

# 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
    def __init__(self, name):
        # Assign the argument to the instance's name attribute
        self.name = name

    # A 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

    # Static methods are called without a class or instance reference
    @staticmethod
    def grunt():
        return "*grunt*"


# Instantiate a class
h = Human(name="Harry")
print h.say("hi")     # prints out "Harry: hi"

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

# Call our class method
h.get_species() #=> "H. sapiens"

# Change the shared attribute
h.species = "H. neanderthalensis"
h.get_species() #=> "H. neanderthalensis"
i.get_species() #=> "H. neanderthalensis"

# Call the static method
Human.grunt() #=> "*grunt*"