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Merge pull request yasoob#60 from Kwpolska/master
More Py3/PEP8 compliance + documentation for enum.Enum
2 parents 672c6f7 + 5f0e358 commit cbad767

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‎collections.rst‎

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@@ -11,6 +11,7 @@ The ones which we will talk about are:
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- ``counter``
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- ``deque``
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- ``namedtuple``
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- ``enum.Enum`` (outside of the module; Python 3.4+)
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1.\ ``defaultdict``
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^^^^^^^^^^^^^^^^^^^
@@ -277,7 +278,68 @@ Like this:
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from collections import namedtuple
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Animal = namedtuple('Animal', 'name age type')
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perry = Animal(name="perry", age=31, type="cat")
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perry = Animal(name="Perry", age=31, type="cat")
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print(perry._asdict())
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# Output: OrderedDict([('name', 'perry'), ('age', 31), ...
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# Output: OrderedDict([('name', 'Perry'), ('age', 31), ...
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5.\ ``enum.Enum`` (Python 3.4+)
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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Another useful collection is the enum object. It is available in the ``enum``
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module, in Python 3.4 and up (also available as a backport in PyPI named ``enum34``.)
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Enums (`enumerated type <https://en.wikipedia.org/wiki/Enumerated_type>`) are
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basically a way to organize various things.
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Let’s consider the Animal namedtuple from the last example. It had a ``type``
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field. The problem is, the type was a string. This poses some problems for
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us. What if the user types in ``Cat`` because they held the Shift key? Or
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``CAT``? Or ``kitten``?
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Enumerations can help us avoid this problem, by not using strings. Consider
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this example:
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.. code:: python
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from collections import namedtuple
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from enum import Enum
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class Species(Enum):
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cat = 1
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dog = 2
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horse = 3
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aardvark = 4
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butterfly = 5
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owl = 6
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platypus = 7
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dragon = 8
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unicorn = 9
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# The list goes on and on...
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# But we don't really care about age, so we can use an alias.
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kitten = 1
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puppy = 2
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Animal = namedtuple('Animal', 'name age type')
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perry = Animal(name="Perry", age=31, type=Species.cat)
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drogon = Animal(name="Drogon", age=4, type=Species.dragon)
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tom = Animal(name="Tom", age=75, type=Species.cat)
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charlie = Animal(name="Charlie", age=2, type=Species.kitten)
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# And now, some tests.
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>>> charlie.type == tom.type
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True
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>>> charlie.type
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<Species.cat: 1>
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This is much less error-prone. We have to be specific, and we should use only
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the enumeration to name types.
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There are three ways to access enumeration members. For example, all three
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methods will get you the value for ``cat``:
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.. code:: python
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Species(1)
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Species['cat']
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Species.cat

‎context_managers.rst‎

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@@ -123,7 +123,7 @@ Let's try handling the exception in the ``__exit__`` method:
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def __enter__(self):
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return self.file_obj
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def __exit__(self, type, value, traceback):
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print "Exception has been handled"
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print("Exception has been handled")
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self.file_obj.close()
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return True
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‎coroutines.rst‎

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@@ -34,7 +34,7 @@ example would be a ``grep`` alternative in Python:
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.. code:: python
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def grep(pattern):
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print "Searching for %s" % pattern
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print("Searching for", pattern)
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while True:
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line = (yield)
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if pattern in line:

‎decorators.rst‎

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@@ -30,7 +30,7 @@ First of all let's understand functions in python:
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# We are not using parentheses here because we are not calling the function hi
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# instead we are just putting it into the greet variable. Let's try to run this
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print greet()
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print(greet())
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# output: 'hi yasoob'
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# Let's see what happens if we delete the old hi function!
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.. code:: python
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def hi(name="yasoob"):
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print "now you are inside the hi() function"
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print("now you are inside the hi() function")
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def greet():
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return "now you are in the greet() function"
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return "hi yasoob!"
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def doSomethingBeforeHi(func):
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print("I am doing some boring work before executing hi()")
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print("I am doing some boring work before executing hi()")
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print(func())
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doSomethingBeforeHi(hi)
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#outputs:I am doing some boring work before executing hi()
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#outputs:I am doing some boring work before executing hi()
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# hi yasoob!
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Now you have all the required knowledge to learn what decorators really
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def a_new_decorator(a_func):
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def wrapTheFunction():
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print "I am doing some boring work before executing a_func()"
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print("I am doing some boring work before executing a_func()")
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a_func()
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@@ -170,7 +170,7 @@ previous decorator and make a little bit more usable program:
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#now a_function_requiring_decoration is wrapped by wrapTheFunction()
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a_function_requiring_decoration()
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#outputs:I am doing some boring work before executing a_function_requiring_decoration()
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#outputs:I am doing some boring work before executing a_function_requiring_decoration()
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# I am the function which needs some decoration to remove my foul smell
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# I am doing some boring work after executing a_function_requiring_decoration()
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@@ -185,12 +185,12 @@ run the previous code sample using @.
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@a_new_decorator
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def a_function_requiring_decoration():
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"""Hey yo! Decorate me!"""
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"""Hey you! Decorate me!"""
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print("I am the function which needs some decoration to "
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" remove my foul smell")
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"remove my foul smell")
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a_function_requiring_decoration()
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#outputs: I am doing some boring work before executing a_function_requiring_decoration()
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#outputs: I am doing some boring work before executing a_function_requiring_decoration()
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# I am the function which needs some decoration to remove my foul smell
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# I am doing some boring work after executing a_function_requiring_decoration()
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@@ -219,7 +219,7 @@ that is ``functools.wraps``. Let's modify our previous example to use
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def a_new_decorator(a_func):
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@wraps(a_func)
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def wrapTheFunction():
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print("I am doing some boring work before executing a_func()")
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print("I am doing some boring work before executing a_func()")
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a_func()
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print("I am doing some boring work after executing a_func()")
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return wrapTheFunction
@@ -236,7 +236,7 @@ that is ``functools.wraps``. Let's modify our previous example to use
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Now that is much better. Let's move on and learn some use-cases of
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decorators.
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**Blueprint :**
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**Blueprint:**
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.. code:: python
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@@ -313,7 +313,7 @@ Logging is another area where the decorators shine. Here is an example:
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@logit
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def addition_func(x):
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"""does some math"""
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"""Do some math."""
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return x + x
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‎for_-_else.rst‎

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@@ -13,7 +13,7 @@ like this:
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fruits = ['apple', 'banana', 'mango']
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for fruit in fruits:
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print fruit.capitalize()
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print(fruit.capitalize())
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# Output: Apple
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# Banana
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for n in range(2, 10):
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for x in range(2, n):
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if n % x == 0:
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print n, 'equals', x, '*', n/x
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print(n, 'equals', x, '*', n/x)
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break
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It finds factors for numbers between 2 to 10. Now for the fun part. We
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for n in range(2, 10):
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for x in range(2, n):
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if n % x == 0:
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print n, 'equals', x, '*', n/x
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prin( n, 'equals', x, '*', n/x)
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break
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else:
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# loop fell through without finding a factor
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print n, 'is a prime number'
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print(n, 'is a prime number')

‎ternary_operators.rst‎

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@@ -39,8 +39,8 @@ is some sample code:
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.. code:: python
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fat = True
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fitness = ("skinny","fat")[fat]
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print("Ali is " + fitness)
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fitness = ("skinny", "fat")[fat]
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print("Ali is", fitness)
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# Output: Ali is fat
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The above example is not widely used and is generally disliked by

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