Merge pull request #581 from ggarza/python_pep8

[python/en] Modify python to be pep8 compliant
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Nami-Doc 2014-03-22 00:36:22 +01:00
commit cc360204e3

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@ -16,7 +16,9 @@ Note: This article applies to Python 2.7 specifically, but should be applicable
to Python 2.x. Look for another tour of Python 3 soon!
```python
# Single line comments start with a hash.
""" Multiline strings can be written
using three "'s, and are often used
as comments
@ -27,60 +29,60 @@ to Python 2.x. Look for another tour of Python 3 soon!
####################################################
# You have numbers
3 #=> 3
3 # => 3
# Math is what you would expect
1 + 1 #=> 2
8 - 1 #=> 7
10 * 2 #=> 20
35 / 5 #=> 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
5 / 2 # => 2
# To fix division we need to learn about floats.
2.0 # This is a float
11.0 / 4.0 #=> 2.75 ahhh...much better
11.0 / 4.0 # => 2.75 ahhh...much better
# Enforce precedence with parentheses
(1 + 3) * 2 #=> 8
(1 + 3) * 2 # => 8
# Boolean values are primitives
True
False
# negate with not
not True #=> False
not False #=> True
not True # => False
not False # => True
# Equality is ==
1 == 1 #=> True
2 == 1 #=> False
1 == 1 # => True
2 == 1 # => False
# Inequality is !=
1 != 1 #=> False
2 != 1 #=> True
1 != 1 # => False
2 != 1 # => True
# More comparisons
1 < 10 #=> True
1 > 10 #=> False
2 <= 2 #=> True
2 >= 2 #=> True
1 < 10 # => True
1 > 10 # => False
2 <= 2 # => True
2 >= 2 # => True
# Comparisons can be chained!
1 < 2 < 3 #=> True
2 < 3 < 2 #=> False
1 < 2 < 3 # => True
2 < 3 < 2 # => False
# Strings are created with " or '
"This is a string."
'This is also a string.'
# Strings can be added too!
"Hello " + "world!" #=> "Hello world!"
"Hello " + "world!" # => "Hello world!"
# A string can be treated like a list of characters
"This is a string"[0] #=> 'T'
"This is a string"[0] # => 'T'
# % can be used to format strings, like this:
"%s can be %s" % ("strings", "interpolated")
@ -92,12 +94,12 @@ not False #=> True
"{name} wants to eat {food}".format(name="Bob", food="lasagna")
# None is an object
None #=> None
None # => None
# Don't use the equality "==" symbol to compare objects to None
# Use "is" instead
"etc" is None #=> False
None is None #=> True
"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
@ -105,8 +107,8 @@ None is None #=> True
# None, 0, and empty strings/lists all evaluate to False.
# All other values are True
bool(0) #=> False
bool("") #=> False
bool(0) # => False
bool("") # => False
####################################################
@ -121,14 +123,14 @@ print "I'm also Python!"
# No need to declare variables before assigning to them.
some_var = 5 # 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
# if can be used as an expression
"yahoo!" if 3 > 2 else 2 #=> "yahoo!"
"yahoo!" if 3 > 2 else 2 # => "yahoo!"
# Lists store sequences
li = []
@ -136,63 +138,63 @@ 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.
# Access a list like you would any array
li[0] #=> 1
li[0] # => 1
# Look at the last element
li[-1] #=> 3
li[-1] # => 3
# Looking out of bounds is an IndexError
li[4] # Raises an IndexError
li[4] # Raises an IndexError
# You can look at ranges with slice syntax.
# (It's a closed/open range for you mathy types.)
li[1:3] #=> [2, 4]
li[1:3] # => [2, 4]
# Omit the beginning
li[2:] #=> [4, 3]
li[2:] # => [4, 3]
# Omit the end
li[:3] #=> [1, 2, 4]
li[:3] # => [1, 2, 4]
# Select every second entry
li[::2] #=>[1,4]
li[::2] # =>[1, 4]
# Revert the list
li[::-1] #=> [3, 4, 2, 1]
li[::-1] # => [3, 4, 2, 1]
# Use any combination of these to make advanced slices
# li[start:end:step]
# Remove arbitrary elements from a list with "del"
del li[2] # li is now [1, 2, 3]
del li[2] # li is now [1, 2, 3]
# You can add lists
li + other_li #=> [1, 2, 3, 4, 5, 6] - Note: li and other_li is left alone
li + other_li # => [1, 2, 3, 4, 5, 6] - Note: li and other_li is left alone
# Concatenate lists with "extend()"
li.extend(other_li) # Now li is [1, 2, 3, 4, 5, 6]
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
1 in li # => True
# Examine the length with "len()"
len(li) #=> 6
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
tup + (4, 5, 6) #=> (1, 2, 3, 4, 5, 6)
tup[:2] #=> (1, 2)
2 in tup #=> True
len(tup) # => 3
tup + (4, 5, 6) # => (1, 2, 3, 4, 5, 6)
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
@ -208,60 +210,60 @@ empty_dict = {}
filled_dict = {"one": 1, "two": 2, "three": 3}
# Look up values with []
filled_dict["one"] #=> 1
filled_dict["one"] # => 1
# Get all keys as a list with "keys()"
filled_dict.keys() #=> ["three", "two", "one"]
filled_dict.keys() # => ["three", "two", "one"]
# Note - Dictionary key ordering is not guaranteed.
# Your results might not match this exactly.
# Get all values as a list with "values()"
filled_dict.values() #=> [3, 2, 1]
filled_dict.values() # => [3, 2, 1]
# Note - Same as above regarding key ordering.
# Check for existence of keys in a dictionary with "in"
"one" in filled_dict #=> True
1 in filled_dict #=> False
"one" in filled_dict # => True
1 in filled_dict # => False
# Looking up a non-existing key is a KeyError
filled_dict["four"] # 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("four", 4) #=> 4
filled_dict.get("one", 4) # => 1
filled_dict.get("four", 4) # => 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
filled_dict.setdefault("five", 5) # filled_dict["five"] is set to 5
filled_dict.setdefault("five", 6) # filled_dict["five"] is still 5
# Sets store ... well sets
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])
some_set = set([1, 2, 2, 3, 4]) # some_set is now set([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}
filled_set = {1, 2, 2, 3, 4} # => {1, 2, 3, 4}
# Add more items to a set
filled_set.add(5) # filled_set is now {1, 2, 3, 4, 5}
filled_set.add(5) # filled_set is now {1, 2, 3, 4, 5}
# Do set intersection with &
other_set = {3, 4, 5, 6}
filled_set & other_set #=> {3, 4, 5}
filled_set & other_set # => {3, 4, 5}
# Do set union with |
filled_set | other_set #=> {1, 2, 3, 4, 5, 6}
filled_set | other_set # => {1, 2, 3, 4, 5, 6}
# Do set difference with -
{1,2,3,4} - {2,3,5} #=> {1, 4}
{1, 2, 3, 4} - {2, 3, 5} # => {1, 4}
# Check for existence in a set with in
2 in filled_set #=> True
10 in filled_set #=> False
2 in filled_set # => True
10 in filled_set # => False
####################################################
@ -337,17 +339,18 @@ def add(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
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 arguments
def varargs(*args):
return args
varargs(1, 2, 3) #=> (1,2,3)
varargs(1, 2, 3) # => (1, 2, 3)
# You can define functions that take a variable number of
@ -356,7 +359,8 @@ def keyword_args(**kwargs):
return kwargs
# Let's call it to see what happens
keyword_args(big="foot", loch="ness") #=> {"big": "foot", "loch": "ness"}
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):
@ -372,9 +376,10 @@ all_the_args(1, 2, a=3, b=4) prints:
# 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 foo(1, 2, 3, 4)
all_the_args(**kwargs) # equivalent to foo(a=3, b=4)
all_the_args(*args, **kwargs) # equivalent to foo(1, 2, 3, 4, a=3, b=4)
all_the_args(*args) # equivalent to foo(1, 2, 3, 4)
all_the_args(**kwargs) # equivalent to foo(a=3, b=4)
all_the_args(*args, **kwargs) # equivalent to foo(1, 2, 3, 4, a=3, b=4)
# Python has first class functions
def create_adder(x):
@ -383,23 +388,24 @@ def create_adder(x):
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
# There are built-in higher order functions
map(add_10, [1,2,3]) #=> [11, 12, 13]
filter(lambda x: x > 5, [3, 4, 5, 6, 7]) #=> [6, 7]
map(add_10, [1, 2, 3]) # => [11, 12, 13]
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]
[x for x in [3, 4, 5, 6, 7] if x > 5] #=> [6, 7]
[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]
####################################################
## 5. Classes
####################################################
# We subclass from object to get a class.
class Human(object):
@ -413,7 +419,7 @@ class Human(object):
# An instance method. All methods take "self" as the first argument
def say(self, msg):
return "%s: %s" % (self.name, msg)
return "%s: %s" % (self.name, msg)
# A class method is shared among all instances
# They are called with the calling class as the first argument
@ -432,18 +438,18 @@ i = Human(name="Ian")
print(i.say("hi")) # prints out "Ian: hi"
j = Human("Joel")
print(j.say("hello")) #prints out "Joel: hello"
print(j.say("hello")) # prints out "Joel: hello"
# Call our class method
i.get_species() #=> "H. sapiens"
i.get_species() # => "H. sapiens"
# Change the shared attribute
Human.species = "H. neanderthalensis"
i.get_species() #=> "H. neanderthalensis"
j.get_species() #=> "H. neanderthalensis"
i.get_species() # => "H. neanderthalensis"
j.get_species() # => "H. neanderthalensis"
# Call the static method
Human.grunt() #=> "*grunt*"
Human.grunt() # => "*grunt*"
####################################################
@ -452,12 +458,12 @@ Human.grunt() #=> "*grunt*"
# You can import modules
import math
print(math.sqrt(16) )#=> 4
print(math.sqrt(16)) # => 4
# 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)) # => 4.0
print(floor(3.7)) # => 3.0
# You can import all functions from a module.
# Warning: this is not recommended
@ -465,7 +471,7 @@ from math import *
# You can shorten module names
import math as m
math.sqrt(16) == m.sqrt(16) #=> True
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
@ -486,10 +492,12 @@ def double_numbers(iterable):
for i in iterable:
yield i + i
# generator creates the value on the fly
# instead of generating and returning all values at once it creates one in each iteration
# this means values bigger than 15 wont be processed in double_numbers
# note range is a generator too, creating a list 1-900000000 would take lot of time to be made
# A generator creates values on the fly.
# Instead of generating and returning all values at once it creates one in each
# iteration. This means values bigger than 15 wont be processed in
# double_numbers.
# Note range is a generator too. Creating a list 1-900000000 would take lot of
# time to be made
_range = range(1, 900000000)
# will double all numbers until a result >=30 found
for i in double_numbers(_range):
@ -500,7 +508,8 @@ for i in double_numbers(_range):
# Decorators
# in this example beg wraps say
# Beg will call say. If say_please is True then it will change the returned message
# Beg will call say. If say_please is True then it will change the returned
# message
from functools import wraps
@ -523,8 +532,6 @@ def say(say_please=False):
print(say()) # Can you buy me a beer?
print(say(say_please=True)) # Can you buy me a beer? Please! I am poor :(
```
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