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diff --git a/python.html.markdown b/python.html.markdown index 0cc33a80..2fc266eb 100644 --- a/python.html.markdown +++ b/python.html.markdown @@ -1,32 +1,22 @@ --- -language: python +language: Python contributors: - - ["Louie Dinh", "http://ldinh.ca"] - - ["Amin Bandali", "https://aminb.org"] + - ["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"] - - ["asyne", "https://github.com/justblah"] - - ["habi", "http://github.com/habi"] - ["Rommel Martinez", "https://ebzzry.io"] + - ["Roberto Fernandez Diaz", "https://github.com/robertofd1995"] + - ["caminsha", "https://github.com/caminsha"] filename: learnpython.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. +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 2.7 specifically, but should be applicable -to Python 2.x. Python 2.7 is reaching end of life and will stop being -maintained in 2020, it is though recommended to start learning Python with -Python 3. For Python 3.x, take a look at the [Python 3 tutorial](http://learnxinyminutes.com/docs/python3/). - -It is also possible to write Python code which is compatible with Python 2.7 -and 3.x at the same time, using Python [`__future__` imports](https://docs.python.org/2/library/__future__.html). `__future__` imports -allow you to write Python 3 code that will run on Python 2, so check out the -Python 3 tutorial. +Note: This article applies to Python 3 specifically. Check out [here](http://learnxinyminutes.com/docs/pythonlegacy/) if you want to learn the old Python 2.7 ```python @@ -34,67 +24,72 @@ Python 3 tutorial. """ Multiline strings can be written using three "s, and are often used - as comments + as documentation. """ #################################################### -# 1. Primitive Datatypes and Operators +## 1. Primitive Datatypes and Operators #################################################### # You have numbers 3 # => 3 # Math is what you would expect -1 + 1 # => 2 -8 - 1 # => 7 +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 +35 / 5 # => 7.0 -# 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 +# Integer division rounds down for both positive and negative numbers. +5 // 3 # => 1 +-5 // 3 # => -2 +5.0 // 3.0 # => 1.0 # works on floats too -5.0 // 3.0 # => -2.0 -# Note that we can also import division module(Section 6 Modules) -# to carry out normal division with just one '/'. -from __future__ import division - -11 / 4 # => 2.75 ...normal division -11 // 4 # => 2 ...floored division +# The result of division is always a float +10.0 / 3 # => 3.3333333333333335 # Modulo operation 7 % 3 # => 1 -# Exponentiation (x to the yth power) -2 ** 4 # => 16 +# Exponentiation (x**y, x to the yth power) +2**3 # => 8 # Enforce precedence with parentheses +1 + 3 * 2 # => 7 (1 + 3) * 2 # => 8 +# Boolean values are primitives (Note: the capitalization) +True # => True +False # => 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 +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 +# True and False are actually 1 and 0 but with different keywords +True + True # => 2 +True * 8 # => 8 +False - 5 # => -5 -# negate with not -not True # => False -not False # => True +# Comparison operators look at the numerical value of True and False +0 == False # => True +1 == True # => True +2 == True # => False +-5 != False # => True + +# Using boolean logical operators on ints casts them to booleans for evaluation, but their non-cast value is returned +# Don't mix up with bool(ints) and bitwise and/or (&,|) +bool(0) # => False +bool(4) # => True +bool(-6) # => True +0 and 2 # => 0 +-5 or 0 # => -5 # Equality is == 1 == 1 # => True @@ -110,93 +105,88 @@ not False # => True 2 <= 2 # => True 2 >= 2 # => True -# Comparisons can be chained! +# Seeing whether a value is in a range +1 < 2 and 2 < 3 # => True +2 < 3 and 3 < 2 # => False +# Chaining makes this look nicer 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! +# 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!" - -# ... or multiplied -"Hello" * 3 # => "HelloHelloHello" +# String literals (but not variables) can be concatenated without using '+' +"Hello " "world!" # => "Hello world!" # A string can be treated like a list of characters -"This is a string"[0] # => 'T' +"Hello world!"[0] # => 'H' # You can find the length of a string len("This is a string") # => 16 -# String formatting with % -# Even though the % string operator will be deprecated on Python 3.1 and removed -# later at some time, it may still be good to know how it works. -x = 'apple' -y = 'lemon' -z = "The items in the basket are %s and %s" % (x, y) +# You can also format using f-strings or formatted string literals (in Python 3.6+) +name = "Reiko" +f"She said her name is {name}." # => "She said her name is Reiko" +# You can basically put any Python statement inside the braces and it will be output in the string. +f"{name} is {len(name)} characters long." # => "Reiko is 5 characters long." -# A newer way to format strings is the format method. -# This method is the preferred way -"{} is a {}".format("This", "placeholder") -"{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 +# Use "is" instead. This checks for equality of object identity. "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. - -# Any object can be used in a Boolean context. -# The following values are considered falsey: -# - None -# - zero of any numeric type (e.g., 0, 0L, 0.0, 0j) -# - empty sequences (e.g., '', (), []) -# - empty containers (e.g., {}, set()) -# - instances of user-defined classes meeting certain conditions -# see: https://docs.python.org/2/reference/datamodel.html#object.__nonzero__ -# -# All other values are truthy (using the bool() function on them returns True). -bool(0) # => False -bool("") # => False +None is None # => True +# None, 0, and empty strings/lists/dicts/tuples all evaluate to False. +# All other values are True +bool(0) # => False +bool("") # => False +bool([]) # => False +bool({}) # => False +bool(()) # => False #################################################### -# 2. Variables and Collections +## 2. Variables and Collections #################################################### -# Python has a print statement -print "I'm Python. Nice to meet you!" # => I'm Python. Nice to meet you! +# 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 string. +print("Hello, World", end="!") # => Hello, World! # Simple way to get input data from console -input_string_var = raw_input( - "Enter some data: ") # Returns the data as a string -input_var = input("Enter some data: ") # Evaluates the data as python code -# Warning: Caution is recommended for input() method usage -# Note: In python 3, input() is deprecated and raw_input() is renamed to input() - -# No need to declare variables before assigning to them. -some_var = 5 # Convention is to use lower_case_with_underscores +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() + +# There are no declarations, only assignments. +# 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_other_var # Raises a name error +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!" +"yay!" if 0 > 1 else "nay!" # => "nay!" # Lists store sequences li = [] @@ -204,21 +194,17 @@ li = [] 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] +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] +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. +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 +li[0] # => 1 # Look at the last element li[-1] # => 3 @@ -226,39 +212,39 @@ li[-1] # => 3 li[4] # Raises an IndexError # You can look at ranges with slice syntax. +# The start index is included, the end index is not # (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] -# Reverse a copy of the list -li[::-1] # => [3, 4, 2, 1] +li[1:3] # Return list from index 1 to 3 => [2, 4] +li[2:] # Return list starting from index 2 => [4, 3] +li[:3] # Return list from beginning until index 3 => [1, 2, 4] +li[::2] # Return list selecting every second entry => [1, 4] +li[::-1] # Return list in reverse order => [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] -# 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] - # Remove first occurrence of a value -li.remove(2) # li is now [1, 3, 4, 5, 6] +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, 4, 5, 6] again +li.insert(1, 2) # li is now [1, 2, 3] again -# Get the index of the first item found +# Get the index of the first item found matching the argument li.index(2) # => 1 -li.index(7) # Raises a ValueError as 7 is not in the list +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 @@ -266,82 +252,109 @@ li.index(7) # Raises a ValueError as 7 is not in the list # Examine the length with "len()" len(li) # => 6 + # Tuples are like lists but are immutable. tup = (1, 2, 3) -tup[0] # => 1 +tup[0] # => 1 tup[0] = 3 # Raises a TypeError -# You can do all those list thingies on tuples too -len(tup) # => 3 +# 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 +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 -d, e, f = 4, 5, 6 # you can leave out the parentheses +# 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 -g = 4, 5, 6 # => (4, 5, 6) +d, e, f = 4, 5, 6 # tuple 4, 5, 6 is unpacked into variables d, e and f +# respectively such that d = 4, e = 5 and f = 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 + +# Dictionaries store mappings from keys to values 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 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 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 - for Python +# versions <3.7, dictionary key ordering is not guaranteed. Your results might +# not match the example below exactly. However, as of Python 3.7, dictionary +# items maintain the order at which they are inserted into the dictionary. +list(filled_dict.keys()) # => ["three", "two", "one"] in Python <3.7 +list(filled_dict.keys()) # => ["one", "two", "three"] in Python 3.7+ -# Get all values as a list with "values()" -filled_dict.values() # => [3, 2, 1] -# Note - Same as above regarding key ordering. -# Get all key-value pairs as a list of tuples with "items()" -filled_dict.items() # => [("one", 1), ("two", 2), ("three", 3)] +# 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] in Python <3.7 +list(filled_dict.values()) # => [1, 2, 3] in Python 3.7+ # Check for existence of keys in a dictionary with "in" "one" in filled_dict # => True -1 in filled_dict # => False +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 +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("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 -# You can declare sets (which are like unordered lists that cannot contain -# duplicate values) using the set object. -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]) +# 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} + + -# 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]) +# 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} -# Since Python 2.7, {} can be used to declare a set -filled_set = {1, 2, 2, 3, 4} # => {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} -# Add more items to a set +# Add one more item to the set +filled_set = some_set filled_set.add(5) # filled_set is now {1, 2, 3, 4, 5} +# Sets do not have duplicate elements +filled_set.add(5) # it remains as before {1, 2, 3, 4, 5} # Do set intersection with & other_set = {3, 4, 5, 6} @@ -357,37 +370,37 @@ filled_set | other_set # => {1, 2, 3, 4, 5, 6} {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 +{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 +{1, 2} <= {1, 2, 3} # => True # Check for existence in a set with in -2 in filled_set # => True +2 in filled_set # => True 10 in filled_set # => False -10 not in filled_set # => True -# Check data type of variable -type(li) # => list -type(filled_dict) # => dict -type(5) # => int +# Make a one layer deep copy +filled_set = some_set.copy() # filled_set is {1, 2, 3, 4, 5} +filled_set is some_set # => False #################################################### -# 3. Control Flow +## 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" +# Here is an if statement. Indentation is significant in Python! +# Convention is to use four spaces, not tabs. +# This 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." + 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 @@ -397,11 +410,11 @@ prints: mouse is a mammal """ for animal in ["dog", "cat", "mouse"]: - # You can use {0} to interpolate formatted strings. (See above.) - print "{0} is a mammal".format(animal) + # You can use format() to interpolate formatted strings + print("{} is a mammal".format(animal)) """ -"range(number)" returns a list of numbers +"range(number)" returns an iterable of numbers from zero to the given number prints: 0 @@ -410,10 +423,10 @@ prints: 3 """ for i in range(4): - print i + print(i) """ -"range(lower, upper)" returns a list of numbers +"range(lower, upper)" returns an iterable of numbers from the lower number to the upper number prints: 4 @@ -422,7 +435,29 @@ prints: 7 """ for i in range(4, 8): - print i + 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) + +""" +To loop over a list, and retrieve both the index and the value of each item in the list +prints: + 0 dog + 1 cat + 2 mouse +""" +animals = ["dog", "cat", "mouse"] +for i, value in enumerate(animals): + print(i, value) """ While loops go until a condition is no longer met. @@ -434,72 +469,121 @@ prints: """ x = 0 while x < 4: - print x + 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. + 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" + 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 + print(line) + +# Writing to a file +contents = {"aa": 12, "bb": 21} +with open("myfile1.txt", "w+") as file: + file.write(str(contents)) # writes a string to a file + +with open("myfile2.txt", "w+") as file: + file.write(json.dumps(contents)) # writes an object to a file + +# Reading from a file +with open('myfile1.txt', "r+") as file: + contents = file.read() # reads a string from a file +print(contents) +# print: {"aa": 12, "bb": 21} + +with open('myfile2.txt', "r+") as file: + contents = json.load(file) # reads a json object from a file +print(contents) +# print: {"aa": 12, "bb": 21} + + +# Python offers a fundamental abstraction called the Iterable. +# An iterable is an object that can be treated as a sequence. +# The object returned by 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 raises a StopIteration exception +next(our_iterator) # Raises StopIteration + +# We can also loop over it, in fact, "for" does this implicitly! +our_iterator = iter(our_iterable) +for i in our_iterator: + print(i) # Prints one, two, three + +# You can grab all the elements of an iterable or iterator by calling list() on it. +list(our_iterable) # => Returns ["one", "two", "three"] +list(our_iterator) # => Returns [] because state is saved #################################################### -# 4. Functions +## 4. Functions #################################################### # Use "def" to create new functions def add(x, y): - print "x is {0} and y is {1}".format(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 args, which will be interpreted as a tuple by using * +# 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 args, as well, which will be interpreted as a dict by using ** +# 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 - - + print(args) + print(kwargs) """ all_the_args(1, 2, a=3, b=4) prints: (1, 2) @@ -507,38 +591,36 @@ all_the_args(1, 2, a=3, b=4) prints: """ # When calling functions, you can do the opposite of args/kwargs! -# Use * to expand positional args and use ** to expand keyword args. +# 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 all_the_args(1, 2, 3, 4) -all_the_args(**kwargs) # equivalent to all_the_args(a=3, b=4) +all_the_args(*args) # equivalent to all_the_args(1, 2, 3, 4) +all_the_args(**kwargs) # equivalent to all_the_args(a=3, b=4) all_the_args(*args, **kwargs) # equivalent to all_the_args(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) -# 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) - +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 - + 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 - + print(x) # => 5 + x = num # global var x is now set to 6 + print(x) # => 6 set_x(43) set_global_x(6) @@ -548,55 +630,98 @@ set_global_x(6) def create_adder(x): def adder(y): return x + y - return adder - add_10 = create_adder(10) -add_10(3) # => 13 +add_10(3) # => 13 # There are also anonymous functions -(lambda x: x > 2)(3) # => True +(lambda x: x > 2)(3) # => True (lambda x, y: x ** 2 + y ** 2)(2, 1) # => 5 # There are built-in higher order functions -map(add_10, [1, 2, 3]) # => [11, 12, 13] -map(max, [1, 2, 3], [4, 2, 1]) # => [4, 2, 3] +list(map(add_10, [1, 2, 3])) # => [11, 12, 13] +list(map(max, [1, 2, 3], [4, 2, 1])) # => [4, 2, 3] -filter(lambda x: x > 5, [3, 4, 5, 6, 7]) # => [6, 7] +list(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] +# 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 in 'abc'} # => {'a', 'b', 'c'} -{x: x ** 2 for x in range(5)} # => {0: 0, 1: 1, 2: 4, 3: 9, 4: 16} +{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. Classes +## 5. Modules #################################################### -# We subclass from object to get a class. -class Human(object): +# 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 +# are defined in 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" statement to create 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. You should not invent such names on your own. + # 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 special 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 + self._age = 0 # An instance method. All methods take "self" as the first argument def say(self, msg): - return "{0}: {1}".format(self.name, 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 @@ -610,8 +735,8 @@ class Human(object): return "*grunt*" # A property is just like a getter. - # It turns the method age() into an read-only attribute - # of the same name. + # It turns the method age() into an read-only attribute of the same name. + # There's no need to write trivial getters and setters in Python, though. @property def age(self): return self._age @@ -627,160 +752,253 @@ class Human(object): del self._age -# Instantiate a class -i = Human(name="Ian") -print i.say("hi") # prints out "Ian: hi" +# 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*" + + # Static methods can be called by instances too + print(i.grunt()) # => "*grunt*" + + # Update the property for this instance + i.age = 42 + # Get the property + i.say(i.age) # => "Ian: 42" + j.say(j.age) # => "Joel: 0" + # Delete the property + del i.age + # i.age # => this would raise an AttributeError -j = Human("Joel") -print j.say("hello") # prints out "Joel: hello" -# Call our class method -i.get_species() # => "H. sapiens" +#################################################### +## 6.1 Inheritance +#################################################### -# Change the shared attribute -Human.species = "H. neanderthalensis" -i.get_species() # => "H. neanderthalensis" -j.get_species() # => "H. neanderthalensis" +# Inheritance allows new child classes to be defined that inherit methods and +# variables from their parent class. -# Call the static method -Human.grunt() # => "*grunt*" +# Using the Human class defined above as the base or parent class, we can +# define a child class, Superhero, which inherits the class variables like +# "species", "name", and "age", as well as methods, like "sing" and "grunt" +# from the Human class, but can also have its own unique properties. -# Update the property -i.age = 42 +# To take advantage of modularization by file you could place the classes above in their own files, +# say, human.py -# Get the property -i.age # => 42 +# To import functions from other files use the following format +# from "filename-without-extension" import "function-or-class" -# Delete the property -del i.age -i.age # => raises an AttributeError +from human import Human -#################################################### -# 6. Modules -#################################################### -# You can import modules -import math +# Specify the parent class(es) as parameters to the class definition +class Superhero(Human): -print math.sqrt(16) # => 4.0 + # If the child class should inherit all of the parent's definitions without + # any modifications, you can just use the "pass" keyword (and nothing else) + # but in this case it is commented out to allow for a unique child class: + # pass -# You can get specific functions from a module -from math import ceil, floor + # Child classes can override their parents' attributes + species = 'Superhuman' -print ceil(3.7) # => 4.0 -print floor(3.7) # => 3.0 + # Children automatically inherit their parent class's constructor including + # its arguments, but can also define additional arguments or definitions + # and override its methods such as the class constructor. + # This constructor inherits the "name" argument from the "Human" class and + # adds the "superpower" and "movie" arguments: + def __init__(self, name, movie=False, + superpowers=["super strength", "bulletproofing"]): -# You can import all functions from a module. -# Warning: this is not recommended -from math import * + # add additional class attributes: + self.fictional = True + self.movie = movie + # be aware of mutable default values, since defaults are shared + self.superpowers = superpowers -# You can shorten module names -import math as m + # The "super" function lets you access the parent class's methods + # that are overridden by the child, in this case, the __init__ method. + # This calls the parent class constructor: + super().__init__(name) -math.sqrt(16) == m.sqrt(16) # => True -# you can also test that the functions are equivalent -from math import sqrt + # override the sing method + def sing(self): + return 'Dun, dun, DUN!' -math.sqrt == m.sqrt == sqrt # => True + # add an additional instance method + def boast(self): + for power in self.superpowers: + print("I wield the power of {pow}!".format(pow=power)) -# 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 +if __name__ == '__main__': + sup = Superhero(name="Tick") -dir(math) + # Instance type checks + if isinstance(sup, Human): + print('I am human') + if type(sup) is Superhero: + print('I am a superhero') + # Get the Method Resolution search Order used by both getattr() and super() + # This attribute is dynamic and can be updated + print(Superhero.__mro__) # => (<class '__main__.Superhero'>, + # => <class 'human.Human'>, <class 'object'>) -# 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. + # Calls parent method but uses its own class attribute + print(sup.get_species()) # => Superhuman + + # Calls overridden method + print(sup.sing()) # => Dun, dun, DUN! + + # Calls method from Human + sup.say('Spoon') # => Tick: Spoon + # Call method that exists only in Superhero + sup.boast() # => I wield the power of super strength! + # => I wield the power of bulletproofing! + + # Inherited class attribute + sup.age = 31 + print(sup.age) # => 31 + + # Attribute that only exists within Superhero + print('Am I Oscar eligible? ' + str(sup.movie)) #################################################### -# 7. Advanced +## 6.2 Multiple Inheritance #################################################### -# Generators -# A generator "generates" values as they are requested instead of storing -# everything up front +# Another class definition +# bat.py +class Bat: -# The following method (*NOT* a generator) will double all values and store it -# in `double_arr`. For large size of iterables, that might get huge! -def double_numbers(iterable): - double_arr = [] - for i in iterable: - double_arr.append(i + i) - return double_arr + species = 'Baty' + def __init__(self, can_fly=True): + self.fly = can_fly -# Running the following would mean we'll double all values first and return all -# of them back to be checked by our condition -for value in double_numbers(range(1000000)): # `test_non_generator` - print value - if value > 5: - break + # 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) + + +# And yet another class definition that inherits from Superhero and Bat +# superhero.py +from superhero import Superhero +from bat import Bat +# Define Batman as a child that inherits from both Superhero and Bat +class Batman(Superhero, Bat): -# We could instead use a generator to "generate" the doubled value as the item -# is being requested -def double_numbers_generator(iterable): + 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". + Superhero.__init__(self, 'anonymous', movie=True, + superpowers=['Wealthy'], *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() + + # 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 'superhero.Superhero'>, + # => <class 'human.Human'>, + # => <class 'bat.Bat'>, <class 'object'>) + + # Calls parent method but uses its own class attribute + print(sup.get_species()) # => Superhuman + + # Calls overridden 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) # => 100 + + # Inherited attribute from 2nd ancestor whose default value was overridden. + print('Can I fly? ' + str(sup.fly)) # => Can I fly? False + + + +#################################################### +## 7. Advanced +#################################################### + +# Generators help you make lazy code. +def double_numbers(iterable): for i in iterable: yield i + i - -# Running the same code as before, but with a generator, now allows us to iterate -# over the values and doubling them one by one as they are being consumed by -# our logic. Hence as soon as we see a value > 5, we break out of the -# loop and don't need to double most of the values sent in (MUCH FASTER!) -for value in double_numbers_generator(xrange(1000000)): # `test_generator` - print value - if value > 5: +# 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 -# BTW: did you notice the use of `range` in `test_non_generator` and `xrange` in `test_generator`? -# Just as `double_numbers_generator` is the generator version of `double_numbers` -# We have `xrange` as the generator version of `range` -# `range` would return back and array with 1000000 values for us to use -# `xrange` would generate 1000000 values for us as we request / iterate over those items - # 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]) +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]) +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 -# A decorator is a higher order function, which accepts and returns a function. -# Simple usage example – add_apples decorator will add 'Apple' element into -# fruits list returned by get_fruits target function. -def add_apples(func): - def get_fruits(): - fruits = func() - fruits.append('Apple') - return fruits - return get_fruits - -@add_apples -def get_fruits(): - return ['Banana', 'Mango', 'Orange'] - -# Prints out the list of fruits with 'Apple' element in it: -# Banana, Mango, Orange, Apple -print ', '.join(get_fruits()) - -# in this example beg wraps say -# Beg will call say. If say_please is True then it will change the returned -# message +# In this example `beg` wraps `say`. If say_please is True then it +# will change the returned message. from functools import wraps @@ -801,8 +1019,8 @@ def say(say_please=False): 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 :( +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? @@ -810,18 +1028,16 @@ print say(say_please=True) # Can you buy me a beer? Please! 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