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----
-language: python3
-contributors:
- - ["Louie Dinh", "http://pythonpracticeprojects.com"]
- - ["Steven Basart", "http://github.com/xksteven"]
- - ["Andre Polykanine", "https://github.com/Oire"]
- - ["Zachary Ferguson", "http://github.com/zfergus2"]
- - ["evuez", "http://github.com/evuez"]
-filename: learnpython3.py
----
-
-Python was created by Guido Van Rossum in the early 90s. It is now one of the most popular
-languages in existence. I fell in love with Python for its syntactic clarity. It's basically
-executable pseudocode.
-
-Feedback would be highly appreciated! You can reach me at [@louiedinh](http://twitter.com/louiedinh) or louiedinh [at] [google's email service]
-
-Note: This article applies to Python 3 specifically. Check out [here](http://learnxinyminutes.com/docs/python/) if you want to learn the old Python 2.7
-
-```python
-
-# Single line comments start with a number symbol.
-
-""" Multiline strings can be written
- using three "s, and are often used
- as comments
-"""
-
-####################################################
-## 1. Primitive Datatypes and Operators
-####################################################
-
-# You have numbers
-3 # => 3
-
-# Math is what you would expect
-1 + 1 # => 2
-8 - 1 # => 7
-10 * 2 # => 20
-35 / 5 # => 7.0
-
-# 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
-
-# The result of division is always a float
-10.0 / 3 # => 3.3333333333333335
-
-# Modulo operation
-7 % 3 # => 1
-
-# Exponentiation (x**y, x to the yth power)
-2**4 # => 16
-
-# Enforce precedence with parentheses
-(1 + 3) * 2 # => 8
-
-# Boolean values are primitives (Note: the capitalization)
-True
-False
-
-# negate with not
-not True # => False
-not False # => True
-
-# 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
-
-# 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
-
-# (is vs. ==) is checks if two variables refer to the same object, but == checks
-# if the objects pointed to have the same values.
-a = [1, 2, 3, 4] # Point a at a new list, [1, 2, 3, 4]
-b = a # Point b at what a is pointing to
-b is a # => True, a and b refer to the same object
-b == a # => True, a's and b's objects are equal
-b = [1, 2, 3, 4] # Point b at a new list, [1, 2, 3, 4]
-b is a # => False, a and b do not refer to the same object
-b == a # => True, a's and b's objects are equal
-
-# Strings are created with " or '
-"This is a string."
-'This is also a string.'
-
-# Strings can be added too! But try not to do this.
-"Hello " + "world!" # => "Hello world!"
-# Strings can be added without using '+'
-"Hello " "world!" # => "Hello world!"
-
-# A string can be treated like a list of characters
-"This is a string"[0] # => 'T'
-
-# You can find the length of a string
-len("This is a string") # => 16
-
-# .format can be used to format strings, like this:
-"{} can be {}".format("Strings", "interpolated") # => "Strings can be interpolated"
-
-# You can repeat the formatting arguments to save some typing.
-"{0} be nimble, {0} be quick, {0} jump over the {1}".format("Jack", "candle stick")
-# => "Jack be nimble, Jack be quick, Jack jump over the candle stick"
-
-# You can use keywords if you don't want to count.
-"{name} wants to eat {food}".format(name="Bob", food="lasagna") # => "Bob wants to eat lasagna"
-
-# If your Python 3 code also needs to run on Python 2.5 and below, you can also
-# still use the old style of formatting:
-"%s can be %s the %s way" % ("Strings", "interpolated", "old") # => "Strings can be interpolated the old way"
-
-
-# None is an object
-None # => None
-
-# Don't use the equality "==" symbol to compare objects to None
-# Use "is" instead. This checks for equality of object identity.
-"etc" is None # => False
-None is None # => True
-
-# None, 0, and empty strings/lists/dicts all evaluate to False.
-# All other values are True
-bool(0) # => False
-bool("") # => False
-bool([]) # => False
-bool({}) # => False
-
-
-####################################################
-## 2. Variables and Collections
-####################################################
-
-# Python has a print function
-print("I'm Python. Nice to meet you!") # => I'm Python. Nice to meet you!
-
-# By default the print function also prints out a newline at the end.
-# Use the optional argument end to change the end character.
-print("Hello, World", end="!") # => Hello, World!
-
-# Simple way to get input data from console
-input_string_var = input("Enter some data: ") # Returns the data as a string
-# Note: In earlier versions of Python, input() method was named as raw_input()
-
-# No need to declare variables before assigning to them.
-# Convention is to use lower_case_with_underscores
-some_var = 5
-some_var # => 5
-
-# Accessing a previously unassigned variable is an exception.
-# See Control Flow to learn more about exception handling.
-some_unknown_var # Raises a NameError
-
-# if can be used as an expression
-# Equivalent of C's '?:' ternary operator
-"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
-# 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]
-# Return a reversed copy of the list
-li[::-1] # => [3, 4, 2, 1]
-# Use any combination of these to make advanced slices
-# li[start:end:step]
-
-# Make a one layer deep copy using slices
-li2 = li[:] # => li2 = [1, 2, 4, 3] but (li2 is li) will result in false.
-
-# Remove arbitrary elements from a list with "del"
-del li[2] # li is now [1, 2, 3]
-
-# Remove first occurrence of a value
-li.remove(2) # li is now [1, 3]
-li.remove(2) # Raises a ValueError as 2 is not in the list
-
-# Insert an element at a specific index
-li.insert(1, 2) # li is now [1, 2, 3] again
-
-# Get the index of the first item found matching the argument
-li.index(2) # => 1
-li.index(4) # Raises a ValueError as 4 is not in the list
-
-# You can add lists
-# Note: values for li and for other_li are not modified.
-li + other_li # => [1, 2, 3, 4, 5, 6]
-
-# 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
-
-# Note that a tuple of length one has to have a comma after the last element but
-# tuples of other lengths, even zero, do not.
-type((1)) # => <class 'int'>
-type((1,)) # => <class 'tuple'>
-type(()) # => <class 'tuple'>
-
-# You can do most of the list operations 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
-# You can also do extended unpacking
-a, *b, c = (1, 2, 3, 4) # a is now 1, b is now [2, 3] and c is now 4
-# 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}
-
-# Note keys for dictionaries have to be immutable types. This is to ensure that
-# the key can be converted to a constant hash value for quick look-ups.
-# Immutable types include ints, floats, strings, tuples.
-invalid_dict = {[1,2,3]: "123"} # => Raises a TypeError: unhashable type: 'list'
-valid_dict = {(1,2,3):[1,2,3]} # Values can be of any type, however.
-
-# Look up values with []
-filled_dict["one"] # => 1
-
-# Get all keys as an iterable with "keys()". We need to wrap the call in list()
-# to turn it into a list. We'll talk about those later. Note - Dictionary key
-# ordering is not guaranteed. Your results might not match this exactly.
-list(filled_dict.keys()) # => ["three", "two", "one"]
-
-
-# Get all values as an iterable with "values()". Once again we need to wrap it
-# in list() to get it out of the iterable. Note - Same as above regarding key
-# ordering.
-list(filled_dict.values()) # => [3, 2, 1]
-
-
-# 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
-
-# "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
-
-# Adding to a dictionary
-filled_dict.update({"four":4}) # => {"one": 1, "two": 2, "three": 3, "four": 4}
-#filled_dict["four"] = 4 #another way to add to dict
-
-# Remove keys from a dictionary with del
-del filled_dict["one"] # Removes the key "one" from filled dict
-
-# From Python 3.5 you can also use the additional unpacking options
-{'a': 1, **{'b': 2}} # => {'a': 1, 'b': 2}
-{'a': 1, **{'a': 2}} # => {'a': 2}
-
-
-
-# Sets store ... well sets
-empty_set = set()
-# Initialize a set with a bunch of values. Yeah, it looks a bit like a dict. Sorry.
-some_set = {1, 1, 2, 2, 3, 4} # some_set is now {1, 2, 3, 4}
-
-# Similar to keys of a dictionary, elements of a set have to be immutable.
-invalid_set = {[1], 1} # => Raises a TypeError: unhashable type: 'list'
-valid_set = {(1,), 1}
-
-# Can set new variables to a set
-filled_set = some_set
-
-# Add one more item to the 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}
-
-# Do set symmetric difference with ^
-{1, 2, 3, 4} ^ {2, 3, 5} # => {1, 4, 5}
-
-# Check if set on the left is a superset of set on the right
-{1, 2} >= {1, 2, 3} # => False
-
-# Check if set on the left is a subset of set on the right
-{1, 2} <= {1, 2, 3} # => True
-
-# Check for existence in a set with in
-2 in filled_set # => True
-10 in filled_set # => False
-
-
-
-####################################################
-## 3. Control Flow and Iterables
-####################################################
-
-# 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 format() to interpolate formatted strings
- print("{} is a mammal".format(animal))
-
-"""
-"range(number)" returns an iterable of numbers
-from zero to the given number
-prints:
- 0
- 1
- 2
- 3
-"""
-for i in range(4):
- print(i)
-
-"""
-"range(lower, upper)" returns an iterable of numbers
-from the lower number to the upper number
-prints:
- 4
- 5
- 6
- 7
-"""
-for i in range(4, 8):
- print(i)
-
-"""
-"range(lower, upper, step)" returns an iterable of numbers
-from the lower number to the upper number, while incrementing
-by step. If step is not indicated, the default value is 1.
-prints:
- 4
- 6
-"""
-for i in range(4, 8, 2):
- 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
-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
-finally: # Execute under all circumstances
- print("We can clean up resources here")
-
-# Instead of try/finally to cleanup resources you can use a with statement
-with open("myfile.txt") as f:
- for line in f:
- print(line)
-
-# Python offers a fundamental abstraction called the Iterable.
-# An iterable is an object that can be treated as a sequence.
-# The object returned the range function, is an iterable.
-
-filled_dict = {"one": 1, "two": 2, "three": 3}
-our_iterable = filled_dict.keys()
-print(our_iterable) # => dict_keys(['one', 'two', 'three']). This is an object that implements our Iterable interface.
-
-# We can loop over it.
-for i in our_iterable:
- print(i) # Prints one, two, three
-
-# However we cannot address elements by index.
-our_iterable[1] # Raises a TypeError
-
-# An iterable is an object that knows how to create an iterator.
-our_iterator = iter(our_iterable)
-
-# Our iterator is an object that can remember the state as we traverse through it.
-# We get the next object with "next()".
-next(our_iterator) # => "one"
-
-# It maintains state as we iterate.
-next(our_iterator) # => "two"
-next(our_iterator) # => "three"
-
-# After the iterator has returned all of its data, it gives you a StopIterator Exception
-next(our_iterator) # Raises StopIteration
-
-# You can grab all the elements of an iterator by calling list() on it.
-list(filled_dict.keys()) # => Returns ["one", "two", "three"]
-
-
-####################################################
-## 4. Functions
-####################################################
-
-# Use "def" to create new functions
-def add(x, y):
- print("x is {} and y is {}".format(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 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, as well
-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 tuples and use ** to expand kwargs.
-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)
-
-# Returning multiple values (with tuple assignments)
-def swap(x, y):
- return y, x # Return multiple values as a tuple without the parenthesis.
- # (Note: parenthesis have been excluded but can be included)
-
-x = 1
-y = 2
-x, y = swap(x, y) # => x = 2, y = 1
-# (x, y) = swap(x,y) # Again parenthesis have been excluded but can be included.
-
-# Function Scope
-x = 5
-
-def set_x(num):
- # Local var x not the same as global variable x
- x = num # => 43
- print (x) # => 43
-
-def set_global_x(num):
- global x
- print (x) # => 5
- x = num # global var x is now set to 6
- print (x) # => 6
-
-set_x(43)
-set_global_x(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
-(lambda x, y: x ** 2 + y ** 2)(2, 1) # => 5
-
-# There are built-in higher order functions
-list(map(add_10, [1, 2, 3])) # => [11, 12, 13]
-list(map(max, [1, 2, 3], [4, 2, 1])) # => [4, 2, 3]
-
-list(filter(lambda x: x > 5, [3, 4, 5, 6, 7])) # => [6, 7]
-
-# We can use list comprehensions for nice maps and filters
-# List comprehension stores the output as a list which can itself be a nested list
-[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]
-
-# You can construct set and dict comprehensions as well.
-{x for x in 'abcddeef' if x not in 'abc'} # => {'d', 'e', 'f'}
-{x: x**2 for x in range(5)} # => {0: 0, 1: 1, 2: 4, 3: 9, 4: 16}
-
-
-####################################################
-## 5. Modules
-####################################################
-
-# You can import modules
-import math
-print(math.sqrt(16)) # => 4.0
-
-# 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
-
-# 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)
-
-# If you have a Python script named math.py in the same
-# folder as your current script, the file math.py will
-# be loaded instead of the built-in Python module.
-# This happens because the local folder has priority
-# over Python's built-in libraries.
-
-
-####################################################
-## 6. Classes
-####################################################
-
-# We use the "class" operator to get a class
-class Human:
-
- # 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. Methods(or objects or attributes) like: __init__, __str__,
- # __repr__ etc. are called magic methods (or sometimes called dunder methods)
- # 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
-
- # Initialize property
- self.age = 0
-
- # An instance method. All methods take "self" as the first argument
- def say(self, msg):
- print ("{name}: {message}".format(name=self.name, message=msg))
-
- # Another instance method
- def sing(self):
- return 'yo... yo... microphone check... one two... one two...'
-
- # 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*"
-
- # A property is just like a getter.
- # It turns the method age() into an read-only attribute
- # of the same name.
- @property
- def age(self):
- return self._age
-
- # This allows the property to be set
- @age.setter
- def age(self, age):
- self._age = age
-
- # This allows the property to be deleted
- @age.deleter
- def age(self):
- del self._age
-
-
-# When a Python interpreter reads a source file it executes all its code.
-# This __name__ check makes sure this code block is only executed when this
-# module is the main program.
-if __name__ == '__main__':
- # Instantiate a class
- i = Human(name="Ian")
- i.say("hi") # "Ian: hi"
- j = Human("Joel")
- j.say("hello") # "Joel: hello"
- # i and j are instances of type Human, or in other words: they are Human objects
-
- # Call our class method
- i.say(i.get_species()) # "Ian: H. sapiens"
- # Change the shared attribute
- Human.species = "H. neanderthalensis"
- i.say(i.get_species()) # => "Ian: H. neanderthalensis"
- j.say(j.get_species()) # => "Joel: H. neanderthalensis"
-
- # Call the static method
- print(Human.grunt()) # => "*grunt*"
- print(i.grunt()) # => "*grunt*"
-
- # Update the property for this instance
- i.age = 42
- # Get the property
- i.say(i.age) # => 42
- j.say(j.age) # => 0
- # Delete the property
- del i.age
- # i.age # => this would raise an AttributeError
-
-
-####################################################
-## 6.1 Multiple Inheritance
-####################################################
-
-# Another class definition
-class Bat:
-
- species = 'Baty'
-
- def __init__(self, can_fly=True):
- self.fly = can_fly
-
- # This class also has a say method
- def say(self, msg):
- msg = '... ... ...'
- return msg
-
- # And its own method as well
- def sonar(self):
- return '))) ... ((('
-
-if __name__ == '__main__':
- b = Bat()
- print(b.say('hello'))
- print(b.fly)
-
-# To take advantage of modularization by file you could place the classes above in their own files,
-# say, human.py and bat.py
-
-# to import functions from other files use the following format
-# from "filename-without-extension" import "function-or-class"
-
-# superhero.py
-from human import Human
-from bat import Bat
-
-# Batman inherits from both Human and Bat
-class Batman(Human, Bat):
-
- # Batman has its own value for the species class attribute
- species = 'Superhero'
-
- def __init__(self, *args, **kwargs):
- # Typically to inherit attributes you have to call super:
- #super(Batman, self).__init__(*args, **kwargs)
- # However we are dealing with multiple inheritance here, and super()
- # only works with the next base class in the MRO list.
- # So instead we explicitly call __init__ for all ancestors.
- # The use of *args and **kwargs allows for a clean way to pass arguments,
- # with each parent "peeling a layer of the onion".
- Human.__init__(self, 'anonymous', *args, **kwargs)
- Bat.__init__(self, *args, can_fly=False, **kwargs)
- # override the value for the name attribute
- self.name = 'Sad Affleck'
-
- def sing(self):
- return 'nan nan nan nan nan batman!'
-
-
-if __name__ == '__main__':
- sup = Batman()
-
- # Instance type checks
- if isinstance(sup, Human):
- print('I am human')
- if isinstance(sup, Bat):
- print('I am bat')
- if type(sup) is Batman:
- print('I am Batman')
-
- # Get the Method Resolution search Order used by both getattr() and super().
- # This attribute is dynamic and can be updated
- print(Batman.__mro__) # => (<class '__main__.Batman'>, <class 'human.Human'>, <class 'bat.Bat'>, <class 'object'>)
-
- # Calls parent method but uses its own class attribute
- print(sup.get_species()) # => Superhero
-
- # Calls overloaded method
- print(sup.sing()) # => nan nan nan nan nan batman!
-
- # Calls method from Human, because inheritance order matters
- sup.say('I agree') # => Sad Affleck: I agree
-
- # Call method that exists only in 2nd ancestor
- print(sup.sonar()) # => ))) ... (((
-
- # Inherited class attribute
- sup.age = 100
- print(sup.age)
-
- # Inherited attribute from 2nd ancestor whose default value was overridden.
- print('Can I fly? ' + str(sup.fly))
-
-
-
-####################################################
-## 7. Advanced
-####################################################
-
-# Generators help you make lazy code.
-def double_numbers(iterable):
- for i in iterable:
- yield i + i
-
-# Generators are memory-efficient because they only load the data needed to
-# process the next value in the iterable. This allows them to perform
-# operations on otherwise prohibitively large value ranges.
-# NOTE: `range` replaces `xrange` in Python 3.
-for i in double_numbers(range(1, 900000000)): # `range` is a generator.
- print(i)
- if i >= 30:
- break
-
-# Just as you can create a list comprehension, you can create generator
-# comprehensions as well.
-values = (-x for x in [1,2,3,4,5])
-for x in values:
- print(x) # prints -1 -2 -3 -4 -5 to console/terminal
-
-# You can also cast a generator comprehension directly to a list.
-values = (-x for x in [1,2,3,4,5])
-gen_to_list = list(values)
-print(gen_to_list) # => [-1, -2, -3, -4, -5]
-
-
-# Decorators
-# In this example `beg` wraps `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 :(
-```
-
-## Ready For More?
-
-### Free Online
-
-* [Automate the Boring Stuff with Python](https://automatetheboringstuff.com)
-* [Ideas for Python Projects](http://pythonpracticeprojects.com)
-* [The Official Docs](http://docs.python.org/3/)
-* [Hitchhiker's Guide to Python](http://docs.python-guide.org/en/latest/)
-* [Python Course](http://www.python-course.eu/index.php)
-* [First Steps With Python](https://realpython.com/learn/python-first-steps/)
-* [A curated list of awesome Python frameworks, libraries and software](https://github.com/vinta/awesome-python)
-* [30 Python Language Features and Tricks You May Not Know About](http://sahandsaba.com/thirty-python-language-features-and-tricks-you-may-not-know.html)
-* [Official Style Guide for Python](https://www.python.org/dev/peps/pep-0008/)
-* [Python 3 Computer Science Circles](http://cscircles.cemc.uwaterloo.ca/)
-* [Dive Into Python 3](http://www.diveintopython3.net/index.html)
-* [A Crash Course in Python for Scientists](http://nbviewer.jupyter.org/gist/anonymous/5924718)