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Merge pull request #1077 from geoffliu/master
[Python3/en] Python3 doc cleanup
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@ -39,7 +39,7 @@ Note: This article applies to Python 3 specifically. Check out [here](http://lea
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# Except division which returns floats by default
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35 / 5 # => 7.0
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# Result of integer division truncated down both for positive and negative.
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# Result of integer division truncated down both for positive and negative.
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5 // 3 # => 1
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5.0 // 3.0 # => 1.0 # works on floats too
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-5 // 3 # => -2
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@ -73,8 +73,8 @@ False or True #=> True
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# Note using Bool operators with ints
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0 and 2 #=> 0
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-5 or 0 #=> -5
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0 == False #=> True
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2 == True #=> False
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0 == False #=> True
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2 == True #=> False
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1 == True #=> True
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# Equality is ==
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@ -145,7 +145,7 @@ bool({}) #=> False
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# Python has a print function
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print("I'm Python. Nice to meet you!")
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# No need to declare variables before assigning to them.
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# No need to declare variables before assigning to them.
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# Convention is to use lower_case_with_underscores
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some_var = 5
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some_var # => 5
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@ -186,7 +186,7 @@ li[2:] # => [4, 3]
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li[:3] # => [1, 2, 4]
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# Select every second entry
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li[::2] # =>[1, 4]
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# Revert the list
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# Return a reversed copy of the list
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li[::-1] # => [3, 4, 2, 1]
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# Use any combination of these to make advanced slices
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# li[start:end:step]
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@ -196,7 +196,7 @@ del li[2] # li is now [1, 2, 3]
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# You can add lists
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# Note: values for li and for other_li are not modified.
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li + other_li # => [1, 2, 3, 4, 5, 6]
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li + other_li # => [1, 2, 3, 4, 5, 6]
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# Concatenate lists with "extend()"
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li.extend(other_li) # Now li is [1, 2, 3, 4, 5, 6]
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@ -213,7 +213,7 @@ tup = (1, 2, 3)
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tup[0] # => 1
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tup[0] = 3 # Raises a TypeError
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# You can do all those list thingies on tuples too
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# You can do most of the list operations on tuples too
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len(tup) # => 3
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tup + (4, 5, 6) # => (1, 2, 3, 4, 5, 6)
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tup[:2] # => (1, 2)
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@ -235,15 +235,15 @@ filled_dict = {"one": 1, "two": 2, "three": 3}
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# Look up values with []
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filled_dict["one"] # => 1
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# Get all keys as a list with "keys()".
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# We need to wrap the call in list() because we are getting back an iterable. We'll talk about those later.
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# Note - Dictionary key ordering is not guaranteed.
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# Your results might not match this exactly.
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# Get all keys as an iterable with "keys()". We need to wrap the call in list()
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# to turn it into a list. We'll talk about those later. Note - Dictionary key
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# ordering is not guaranteed. Your results might not match this exactly.
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list(filled_dict.keys()) # => ["three", "two", "one"]
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# Get all values as a list with "values()". Once again we need to wrap it in list() to get it out of the iterable.
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# Note - Same as above regarding key ordering.
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# Get all values as an iterable with "values()". Once again we need to wrap it
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# in list() to get it out of the iterable. Note - Same as above regarding key
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# ordering.
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list(filled_dict.values()) # => [3, 2, 1]
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@ -281,7 +281,7 @@ some_set = {1, 1, 2, 2, 3, 4} # some_set is now {1, 2, 3, 4}
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# Can set new variables to a set
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filled_set = some_set
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# Add one more item to the set
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# Add one more item to the set
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filled_set.add(5) # filled_set is now {1, 2, 3, 4, 5}
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# Do set intersection with &
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@ -328,7 +328,7 @@ for animal in ["dog", "cat", "mouse"]:
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print("{} is a mammal".format(animal))
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"""
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"range(number)" returns a list of numbers
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"range(number)" returns an iterable of numbers
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from zero to the given number
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prints:
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0
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@ -340,7 +340,7 @@ for i in range(4):
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print(i)
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"""
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"range(lower, upper)" returns a list of numbers
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"range(lower, upper)" returns an iterable of numbers
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from the lower number to the upper number
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prints:
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4
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@ -458,14 +458,14 @@ all_the_args(**kwargs) # equivalent to foo(a=3, b=4)
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all_the_args(*args, **kwargs) # equivalent to foo(1, 2, 3, 4, a=3, b=4)
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# Function Scope
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# Function Scope
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x = 5
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def setX(num):
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# Local var x not the same as global variable x
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x = num # => 43
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print (x) # => 43
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def setGlobalX(num):
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global x
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print (x) # => 5
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@ -512,8 +512,8 @@ class Human(object):
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# Basic initializer, this is called when this class is instantiated.
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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 magic methods (or sometimes called dunder methods)
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# namespaces. Methods(or objects or attributes) like: __init__, __str__,
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# __repr__ etc. are called magic methods (or sometimes called dunder methods)
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# 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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@ -600,7 +600,7 @@ def double_numbers(iterable):
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# double_numbers.
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# Note range is a generator too. Creating a list 1-900000000 would take lot of
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# time to be made
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# We use a trailing underscore in variable names when we want to use a name that
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# We use a trailing underscore in variable names when we want to use a name that
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# would normally collide with a python keyword
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range_ = range(1, 900000000)
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# will double all numbers until a result >=30 found
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