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Merge pull request #4537 from nbehrnd/python_en_linelimit
[python/en] stricter restraint of 80 characters/line maximum
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@ -13,11 +13,13 @@ contributors:
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filename: learnpython.py
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---
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Python was created by Guido van Rossum in the early 90s. It is now one of the most popular
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languages in existence. I fell in love with Python for its syntactic clarity. It's basically
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executable pseudocode.
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Python was created by Guido van Rossum in the early 90s. It is now one of the
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most popular languages in existence. I fell in love with Python for its
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syntactic clarity. It's basically executable pseudocode.
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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
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Note: This article applies to Python 3 specifically. Check out
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[here](http://learnxinyminutes.com/docs/pythonlegacy/) if you want to learn the
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old Python 2.7
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```python
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@ -97,8 +99,9 @@ bool(set()) # => False
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bool(4) # => True
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bool(-6) # => True
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# Using boolean logical operators on ints casts them to booleans for evaluation, but their non-cast value is returned
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# Don't mix up with bool(ints) and bitwise and/or (&,|)
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# Using boolean logical operators on ints casts them to booleans for evaluation,
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# but their non-cast value is returned. Don't mix up with bool(ints) and bitwise
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# and/or (&,|)
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bool(0) # => False
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bool(2) # => True
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0 and 2 # => 0
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@ -152,10 +155,10 @@ b == a # => True, a's and b's objects are equal
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# You can find the length of a string
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len("This is a string") # => 16
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# You can also format using f-strings or formatted string literals (in Python 3.6+)
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# Since Python 3.6, you can use f-strings or formatted string literals.
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name = "Reiko"
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f"She said her name is {name}." # => "She said her name is Reiko"
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# You can basically put any Python expression inside the braces and it will be output in the string.
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# Any valid Python expression inside these braces is returned to the string.
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f"{name} is {len(name)} characters long." # => "Reiko is 5 characters long."
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# None is an object
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@ -294,7 +297,7 @@ filled_dict = {"one": 1, "two": 2, "three": 3}
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# Note keys for dictionaries have to be immutable types. This is to ensure that
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# the key can be converted to a constant hash value for quick look-ups.
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# Immutable types include ints, floats, strings, tuples.
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invalid_dict = {[1,2,3]: "123"} # => Raises a TypeError: unhashable type: 'list'
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invalid_dict = {[1,2,3]: "123"} # => Yield a TypeError: unhashable type: 'list'
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valid_dict = {(1,2,3):[1,2,3]} # Values can be of any type, however.
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# Look up values with []
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@ -348,7 +351,7 @@ del filled_dict["one"] # Removes the key "one" from filled dict
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# Sets store ... well sets
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empty_set = set()
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# Initialize a set with a bunch of values. Yeah, it looks a bit like a dict. Sorry.
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# Initialize a set with a bunch of values.
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some_set = {1, 1, 2, 2, 3, 4} # some_set is now {1, 2, 3, 4}
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# Similar to keys of a dictionary, elements of a set have to be immutable.
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@ -454,8 +457,7 @@ for i in range(4, 8, 2):
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print(i)
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"""
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To loop over a list, and retrieve both the index and the value of each item in the list
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prints:
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Loop over a list to retrieve both the index and the value of each list item:
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0 dog
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1 cat
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2 mouse
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@ -482,10 +484,11 @@ try:
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# Use "raise" to raise an error
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raise IndexError("This is an index error")
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except IndexError as e:
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pass # Pass is just a no-op. Usually you would do recovery here.
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pass # Refrain from this, provide a recovery (next example).
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except (TypeError, NameError):
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pass # Multiple exceptions can be handled together, if required.
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else: # Optional clause to the try/except block. Must follow all except blocks
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pass # Multiple exceptions can be processed jointly.
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else: # Optional clause to the try/except block. Must follow
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# all except blocks.
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print("All good!") # Runs only if the code in try raises no exceptions
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finally: # Execute under all circumstances
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print("We can clean up resources here")
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@ -521,7 +524,8 @@ print(contents)
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filled_dict = {"one": 1, "two": 2, "three": 3}
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our_iterable = filled_dict.keys()
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print(our_iterable) # => dict_keys(['one', 'two', 'three']). This is an object that implements our Iterable interface.
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print(our_iterable) # => dict_keys(['one', 'two', 'three']). This is an object
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# that implements our Iterable interface.
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# We can loop over it.
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for i in our_iterable:
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@ -533,15 +537,16 @@ our_iterable[1] # Raises a TypeError
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# An iterable is an object that knows how to create an iterator.
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our_iterator = iter(our_iterable)
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# Our iterator is an object that can remember the state as we traverse through it.
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# We get the next object with "next()".
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# Our iterator is an object that can remember the state as we traverse through
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# it. We get the next object with "next()".
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next(our_iterator) # => "one"
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# It maintains state as we iterate.
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next(our_iterator) # => "two"
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next(our_iterator) # => "three"
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# After the iterator has returned all of its data, it raises a StopIteration exception
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# After the iterator has returned all of its data, it raises a
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# StopIteration exception
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next(our_iterator) # Raises StopIteration
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# We can also loop over it, in fact, "for" does this implicitly!
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@ -549,7 +554,7 @@ our_iterator = iter(our_iterable)
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for i in our_iterator:
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print(i) # Prints one, two, three
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# You can grab all the elements of an iterable or iterator by calling list() on it.
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# You can grab all the elements of an iterable or iterator by call of list().
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list(our_iterable) # => Returns ["one", "two", "three"]
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list(our_iterator) # => Returns [] because state is saved
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@ -599,9 +604,9 @@ all_the_args(1, 2, a=3, b=4) prints:
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# Use * to expand tuples and use ** to expand kwargs.
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args = (1, 2, 3, 4)
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kwargs = {"a": 3, "b": 4}
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all_the_args(*args) # equivalent to all_the_args(1, 2, 3, 4)
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all_the_args(**kwargs) # equivalent to all_the_args(a=3, b=4)
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all_the_args(*args, **kwargs) # equivalent to all_the_args(1, 2, 3, 4, a=3, b=4)
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all_the_args(*args) # equivalent: all_the_args(1, 2, 3, 4)
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all_the_args(**kwargs) # equivalent: all_the_args(a=3, b=4)
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all_the_args(*args, **kwargs) # equivalent: all_the_args(1, 2, 3, 4, a=3, b=4)
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# Returning multiple values (with tuple assignments)
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def swap(x, y):
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@ -611,7 +616,7 @@ def swap(x, y):
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x = 1
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y = 2
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x, y = swap(x, y) # => x = 2, y = 1
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# (x, y) = swap(x,y) # Again parenthesis have been excluded but can be included.
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# (x, y) = swap(x,y) # Again the use of parenthesis is optional.
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# global scope
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x = 5
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@ -659,7 +664,7 @@ list(map(max, [1, 2, 3], [4, 2, 1])) # => [4, 2, 3]
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list(filter(lambda x: x > 5, [3, 4, 5, 6, 7])) # => [6, 7]
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# We can use list comprehensions for nice maps and filters
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# List comprehension stores the output as a list which can itself be a nested list
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# List comprehension stores the output as a list (which itself may be nested).
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[add_10(i) for i in [1, 2, 3]] # => [11, 12, 13]
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[x for x in [3, 4, 5, 6, 7] if x > 5] # => [6, 7]
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@ -719,8 +724,8 @@ class Human:
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# Note that the double leading and trailing underscores denote objects
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# or attributes that are used by Python but that live in user-controlled
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# namespaces. Methods(or objects or attributes) like: __init__, __str__,
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# __repr__ etc. are called special methods (or sometimes called dunder methods)
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# You should not invent such names on your own.
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# __repr__ etc. are called special methods (or sometimes called dunder
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# methods). You should not invent such names on your own.
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def __init__(self, name):
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# Assign the argument to the instance's name attribute
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self.name = name
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@ -774,7 +779,7 @@ if __name__ == '__main__':
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i.say("hi") # "Ian: hi"
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j = Human("Joel")
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j.say("hello") # "Joel: hello"
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# i and j are instances of type Human, or in other words: they are Human objects
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# i and j are instances of type Human; i.e., they are Human objects.
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# Call our class method
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i.say(i.get_species()) # "Ian: H. sapiens"
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@ -811,8 +816,8 @@ if __name__ == '__main__':
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# "species", "name", and "age", as well as methods, like "sing" and "grunt"
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# from the Human class, but can also have its own unique properties.
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# To take advantage of modularization by file you could place the classes above in their own files,
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# say, human.py
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# To take advantage of modularization by file you could place the classes above
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# in their own files, say, human.py
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# To import functions from other files use the following format
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# from "filename-without-extension" import "function-or-class"
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@ -936,8 +941,8 @@ class Batman(Superhero, Bat):
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# However we are dealing with multiple inheritance here, and super()
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# only works with the next base class in the MRO list.
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# So instead we explicitly call __init__ for all ancestors.
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# The use of *args and **kwargs allows for a clean way to pass arguments,
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# with each parent "peeling a layer of the onion".
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# The use of *args and **kwargs allows for a clean way to pass
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# arguments, with each parent "peeling a layer of the onion".
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Superhero.__init__(self, 'anonymous', movie=True,
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superpowers=['Wealthy'], *args, **kwargs)
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Bat.__init__(self, *args, can_fly=False, **kwargs)
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@ -1036,8 +1041,6 @@ print(say()) # Can you buy me a beer?
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print(say(say_please=True)) # Can you buy me a beer? Please! I am poor :(
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```
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## Ready For More?
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### Free Online
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* [Automate the Boring Stuff with Python](https://automatetheboringstuff.com)
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