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Diffstat (limited to 'python.html.markdown')
| -rw-r--r-- | python.html.markdown | 190 |
1 files changed, 124 insertions, 66 deletions
diff --git a/python.html.markdown b/python.html.markdown index 687529b5..9d97e64d 100644 --- a/python.html.markdown +++ b/python.html.markdown @@ -10,14 +10,17 @@ contributors: - ["Roberto Fernandez Diaz", "https://github.com/robertofd1995"] - ["caminsha", "https://github.com/caminsha"] - ["Stanislav Modrak", "https://stanislav.gq"] + - ["John Paul Wohlscheid", "https://gitpi.us"] 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. -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 +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 @@ -82,7 +85,7 @@ False - 5 # => -5 # Comparison operators look at the numerical value of True and False 0 == False # => True -1 == True # => True +2 > True # => True 2 == True # => False -5 != False # => True @@ -97,8 +100,9 @@ bool(set()) # => False bool(4) # => True bool(-6) # => 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 (&,|) +# 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(2) # => True 0 and 2 # => 0 @@ -152,10 +156,10 @@ b == a # => True, a's and b's objects are equal # You can find the length of a string len("This is a string") # => 16 -# You can also format using f-strings or formatted string literals (in Python 3.6+) +# Since Python 3.6, you can use f-strings or formatted string literals. name = "Reiko" f"She said her name is {name}." # => "She said her name is Reiko" -# You can basically put any Python expression inside the braces and it will be output in the string. +# Any valid Python expression inside these braces is returned to the string. f"{name} is {len(name)} characters long." # => "Reiko is 5 characters long." # None is an object @@ -181,7 +185,7 @@ print("Hello, World", end="!") # => Hello, World! input_string_var = input("Enter some data: ") # Returns the data as a string # There are no declarations, only assignments. -# Convention is to use lower_case_with_underscores +# Convention in naming variables is snake_case style some_var = 5 some_var # => 5 @@ -222,7 +226,7 @@ li[4] # Raises an IndexError 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[::2] # Return list selecting elements with a step size of 2 => [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] @@ -294,7 +298,7 @@ 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' +invalid_dict = {[1,2,3]: "123"} # => Yield a TypeError: unhashable type: 'list' valid_dict = {(1,2,3):[1,2,3]} # Values can be of any type, however. # Look up values with [] @@ -348,7 +352,7 @@ del filled_dict["one"] # Removes the key "one" from filled dict # Sets store ... well sets empty_set = set() -# Initialize a set with a bunch of values. Yeah, it looks a bit like a dict. Sorry. +# Initialize a set with a bunch of values. 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. @@ -454,8 +458,7 @@ 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: +Loop over a list to retrieve both the index and the value of each list item: 0 dog 1 cat 2 mouse @@ -482,10 +485,11 @@ 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 # Refrain from this, provide a recovery (next example). 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 + pass # Multiple exceptions can be processed jointly. +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") @@ -497,19 +501,20 @@ with open("myfile.txt") as f: # Writing to a file contents = {"aa": 12, "bb": 21} -with open("myfile1.txt", "w+") as file: +with open("myfile1.txt", "w") as file: file.write(str(contents)) # writes a string to a file -with open("myfile2.txt", "w+") as file: +import json +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: +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: +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} @@ -521,7 +526,8 @@ print(contents) 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. +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: @@ -533,15 +539,16 @@ 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()". +# 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 +# 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! @@ -549,7 +556,7 @@ 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. +# You can grab all the elements of an iterable or iterator by call of list(). list(our_iterable) # => Returns ["one", "two", "three"] list(our_iterator) # => Returns [] because state is saved @@ -596,12 +603,12 @@ all_the_args(1, 2, a=3, b=4) prints: """ # When calling functions, you can do the opposite of args/kwargs! -# Use * to expand tuples and use ** to expand kwargs. +# Use * to expand args (tuples) and use ** to expand kwargs (dictionaries). 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, **kwargs) # equivalent to all_the_args(1, 2, 3, 4, a=3, b=4) +all_the_args(*args) # equivalent: all_the_args(1, 2, 3, 4) +all_the_args(**kwargs) # equivalent: all_the_args(a=3, b=4) +all_the_args(*args, **kwargs) # equivalent: all_the_args(1, 2, 3, 4, a=3, b=4) # Returning multiple values (with tuple assignments) def swap(x, y): @@ -611,7 +618,7 @@ def swap(x, y): 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. +# (x, y) = swap(x,y) # Again the use of parenthesis is optional. # global scope x = 5 @@ -648,6 +655,22 @@ def create_adder(x): add_10 = create_adder(10) add_10(3) # => 13 +# Closures in nested functions: +# We can use the nonlocal keyword to work with variables in nested scope which shouldn't be declared in the inner functions. +def create_avg(): + total = 0 + count = 0 + def avg(n): + nonlocal total, count + total += n + count += 1 + return total/count + return avg +avg = create_avg() +avg(3) # => 3.0 +avg(5) # (3+5)/2 => 4.0 +avg(7) # (8+7)/3 => 5.0 + # There are also anonymous functions (lambda x: x > 2)(3) # => True (lambda x, y: x ** 2 + y ** 2)(2, 1) # => 5 @@ -659,7 +682,7 @@ 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 +# List comprehension stores the output as a list (which itself may be nested). [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] @@ -678,8 +701,8 @@ 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 +print(ceil(3.7)) # => 4 +print(floor(3.7)) # => 3 # You can import all functions from a module. # Warning: this is not recommended @@ -719,14 +742,16 @@ class Human: # 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 special methods (or sometimes called dunder methods) - # You should not invent such names on your own. + # __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 # the leading underscore indicates the "age" property is + # intended to be used internally + # do not rely on this to be enforced: it's a hint to other devs # An instance method. All methods take "self" as the first argument def say(self, msg): @@ -774,7 +799,7 @@ if __name__ == '__main__': 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 + # i and j are instances of type Human; i.e., they are Human objects. # Call our class method i.say(i.get_species()) # "Ian: H. sapiens" @@ -811,8 +836,8 @@ if __name__ == '__main__': # "species", "name", and "age", as well as methods, like "sing" and "grunt" # from the Human class, but can also have its own unique properties. -# To take advantage of modularization by file you could place the classes above in their own files, -# say, human.py +# To take advantage of modularization by file you could place the classes above +# in their own files, say, human.py # To import functions from other files use the following format # from "filename-without-extension" import "function-or-class" @@ -869,7 +894,8 @@ if __name__ == '__main__': if type(sup) is Superhero: print('I am a superhero') - # Get the Method Resolution search Order used by both getattr() and super() + # Get the "Method Resolution Order" used by both getattr() and super() + # (the order in which classes are searched for an attribute or method) # This attribute is dynamic and can be updated print(Superhero.__mro__) # => (<class '__main__.Superhero'>, # => <class 'human.Human'>, <class 'object'>) @@ -936,8 +962,8 @@ class Batman(Superhero, Bat): # 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". + # 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) @@ -951,8 +977,7 @@ class Batman(Superhero, Bat): 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 + # The Method Resolution Order print(Batman.__mro__) # => (<class '__main__.Batman'>, # => <class 'superhero.Superhero'>, # => <class 'human.Human'>, @@ -1009,39 +1034,72 @@ 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 +# Decorators are a form of syntactic sugar. +# They make code easier to read while accomplishing clunky syntax. +# Wrappers are one type of decorator. +# They're really useful for adding logging to existing functions without needing to modify them. -def beg(target_function): - @wraps(target_function) +def log_function(func): def wrapper(*args, **kwargs): - msg, say_please = target_function(*args, **kwargs) - if say_please: - return "{} {}".format(msg, "Please! I am poor :(") - return msg - + print("Entering function", func.__name__) + result = func(*args, **kwargs) + print("Exiting function", func.__name__) + return result return wrapper +@log_function # equivalent: +def my_function(x,y): # def my_function(x,y): + return x+y # return x+y + # my_function = log_function(my_function) +# The decorator @log_function tells us as we begin reading the function definition +# for my_function that this function will be wrapped with log_function. +# When function definitions are long, it can be hard to parse the non-decorated +# assignment at the end of the definition. -@beg -def say(say_please=False): - msg = "Can you buy me a beer?" - return msg, say_please +my_function(1,2) # => "Entering function my_function" + # => "3" + # => "Exiting function my_function" +# But there's a problem. +# What happens if we try to get some information about my_function? -print(say()) # Can you buy me a beer? -print(say(say_please=True)) # Can you buy me a beer? Please! I am poor :( -``` +print(my_function.__name__) # => 'wrapper' +print(my_function.__code__.co_argcount) # => 0. The argcount is 0 because both arguments in wrapper()'s signature are optional. + +# Because our decorator is equivalent to my_function = log_function(my_function) +# we've replaced information about my_function with information from wrapper + +# Fix this using functools -## Ready For More? +from functools import wraps + +def log_function(func): + @wraps(func) # this ensures docstring, function name, arguments list, etc. are all copied + # to the wrapped function - instead of being replaced with wrapper's info + def wrapper(*args, **kwargs): + print("Entering function", func.__name__) + result = func(*args, **kwargs) + print("Exiting function", func.__name__) + return result + return wrapper + +@log_function +def my_function(x,y): + return x+y + +my_function(1,2) # => "Entering function my_function" + # => "3" + # => "Exiting function my_function" + +print(my_function.__name__) # => 'my_function' +print(my_function.__code__.co_argcount) # => 2 + +``` ### Free Online * [Automate the Boring Stuff with Python](https://automatetheboringstuff.com) -* [Ideas for Python Projects](http://pythonpracticeprojects.com) * [The Official Docs](https://docs.python.org/3/) * [Hitchhiker's Guide to Python](https://docs.python-guide.org/en/latest/) * [Python Course](https://www.python-course.eu) |