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Modify python to be pep8 compliant
This mostly adds spaces.
This commit is contained in:
Guillermo Garza
parent
90ee70b3e3
commit
7db61d1ce1
@ -16,7 +16,9 @@ Note: This article applies to Python 2.7 specifically, but should be applicable
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to Python 2.x. Look for another tour of Python 3 soon!
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```python
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# Single line comments start with a hash.
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""" Multiline strings can be written
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using three "'s, and are often used
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as comments
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@ -27,60 +29,60 @@ to Python 2.x. Look for another tour of Python 3 soon!
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####################################################
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# You have numbers
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3 #=> 3
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3 # => 3
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# Math is what you would expect
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1 + 1 #=> 2
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8 - 1 #=> 7
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10 * 2 #=> 20
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35 / 5 #=> 7
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1 + 1 # => 2
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8 - 1 # => 7
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10 * 2 # => 20
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35 / 5 # => 7
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# Division is a bit tricky. It is integer division and floors the results
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# automatically.
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5 / 2 #=> 2
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5 / 2 # => 2
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# To fix division we need to learn about floats.
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2.0 # This is a float
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11.0 / 4.0 #=> 2.75 ahhh...much better
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11.0 / 4.0 # => 2.75 ahhh...much better
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# Enforce precedence with parentheses
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(1 + 3) * 2 #=> 8
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(1 + 3) * 2 # => 8
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# Boolean values are primitives
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True
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False
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# negate with not
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not True #=> False
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not False #=> True
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not True # => False
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not False # => True
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# Equality is ==
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1 == 1 #=> True
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2 == 1 #=> False
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1 == 1 # => True
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2 == 1 # => False
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# Inequality is !=
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1 != 1 #=> False
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2 != 1 #=> True
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1 != 1 # => False
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2 != 1 # => True
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# More comparisons
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1 < 10 #=> True
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1 > 10 #=> False
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2 <= 2 #=> True
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2 >= 2 #=> True
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1 < 10 # => True
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1 > 10 # => False
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2 <= 2 # => True
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2 >= 2 # => True
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# Comparisons can be chained!
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1 < 2 < 3 #=> True
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2 < 3 < 2 #=> False
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1 < 2 < 3 # => True
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2 < 3 < 2 # => False
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# Strings are created with " or '
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"This is a string."
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'This is also a string.'
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# Strings can be added too!
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"Hello " + "world!" #=> "Hello world!"
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"Hello " + "world!" # => "Hello world!"
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# A string can be treated like a list of characters
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"This is a string"[0] #=> 'T'
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"This is a string"[0] # => 'T'
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# % can be used to format strings, like this:
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"%s can be %s" % ("strings", "interpolated")
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@ -92,12 +94,12 @@ not False #=> True
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"{name} wants to eat {food}".format(name="Bob", food="lasagna")
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# None is an object
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None #=> None
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None # => None
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# Don't use the equality "==" symbol to compare objects to None
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# Use "is" instead
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"etc" is None #=> False
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None is None #=> True
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"etc" is None # => False
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None is None # => True
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# The 'is' operator tests for object identity. This isn't
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# very useful when dealing with primitive values, but is
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@ -105,8 +107,8 @@ None is None #=> True
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# None, 0, and empty strings/lists all evaluate to False.
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# All other values are True
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bool(0) #=> False
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bool("") #=> False
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bool(0) # => False
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bool("") # => False
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####################################################
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@ -121,14 +123,14 @@ print "I'm also Python!"
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# No need to declare variables before assigning to them.
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some_var = 5 # 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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# Accessing a previously unassigned variable is an exception.
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# See Control Flow to learn more about exception handling.
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some_other_var # Raises a name error
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# if can be used as an expression
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"yahoo!" if 3 > 2 else 2 #=> "yahoo!"
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"yahoo!" if 3 > 2 else 2 # => "yahoo!"
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# Lists store sequences
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li = []
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@ -136,63 +138,63 @@ li = []
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other_li = [4, 5, 6]
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# Add stuff to the end of a list with append
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li.append(1) #li is now [1]
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li.append(2) #li is now [1, 2]
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li.append(4) #li is now [1, 2, 4]
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li.append(3) #li is now [1, 2, 4, 3]
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li.append(1) # li is now [1]
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li.append(2) # li is now [1, 2]
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li.append(4) # li is now [1, 2, 4]
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li.append(3) # li is now [1, 2, 4, 3]
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# Remove from the end with pop
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li.pop() #=> 3 and li is now [1, 2, 4]
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li.pop() # => 3 and li is now [1, 2, 4]
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# Let's put it back
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li.append(3) # li is now [1, 2, 4, 3] again.
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# Access a list like you would any array
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li[0] #=> 1
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li[0] # => 1
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# Look at the last element
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li[-1] #=> 3
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li[-1] # => 3
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# Looking out of bounds is an IndexError
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li[4] # Raises an IndexError
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li[4] # Raises an IndexError
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# You can look at ranges with slice syntax.
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# (It's a closed/open range for you mathy types.)
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li[1:3] #=> [2, 4]
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li[1:3] # => [2, 4]
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# Omit the beginning
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li[2:] #=> [4, 3]
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li[2:] # => [4, 3]
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# Omit the end
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li[:3] #=> [1, 2, 4]
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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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li[::2] # =>[1, 4]
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# Revert the list
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li[::-1] #=> [3, 4, 2, 1]
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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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# Remove arbitrary elements from a list with "del"
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del li[2] # li is now [1, 2, 3]
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del li[2] # li is now [1, 2, 3]
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# You can add lists
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li + other_li #=> [1, 2, 3, 4, 5, 6] - Note: li and other_li is left alone
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li + other_li # => [1, 2, 3, 4, 5, 6] - Note: li and other_li is left alone
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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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li.extend(other_li) # Now li is [1, 2, 3, 4, 5, 6]
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# Check for existence in a list with "in"
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1 in li #=> True
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1 in li # => True
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# Examine the length with "len()"
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len(li) #=> 6
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len(li) # => 6
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# Tuples are like lists but are immutable.
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tup = (1, 2, 3)
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tup[0] #=> 1
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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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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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2 in tup #=> True
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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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2 in tup # => True
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# You can unpack tuples (or lists) into variables
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a, b, c = (1, 2, 3) # a is now 1, b is now 2 and c is now 3
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@ -208,60 +210,60 @@ empty_dict = {}
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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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filled_dict["one"] # => 1
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# Get all keys as a list with "keys()"
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filled_dict.keys() #=> ["three", "two", "one"]
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filled_dict.keys() # => ["three", "two", "one"]
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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 values as a list with "values()"
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filled_dict.values() #=> [3, 2, 1]
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filled_dict.values() # => [3, 2, 1]
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# Note - Same as above regarding key ordering.
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# Check for existence of keys in a dictionary with "in"
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"one" in filled_dict #=> True
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1 in filled_dict #=> False
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"one" in filled_dict # => True
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1 in filled_dict # => False
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# Looking up a non-existing key is a KeyError
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filled_dict["four"] # KeyError
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filled_dict["four"] # KeyError
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# Use "get()" method to avoid the KeyError
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filled_dict.get("one") #=> 1
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filled_dict.get("four") #=> None
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filled_dict.get("one") # => 1
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filled_dict.get("four") # => None
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# The get method supports a default argument when the value is missing
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filled_dict.get("one", 4) #=> 1
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filled_dict.get("four", 4) #=> 4
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filled_dict.get("one", 4) # => 1
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filled_dict.get("four", 4) # => 4
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# "setdefault()" inserts into a dictionary only if the given key isn't present
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filled_dict.setdefault("five", 5) #filled_dict["five"] is set to 5
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filled_dict.setdefault("five", 6) #filled_dict["five"] is still 5
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filled_dict.setdefault("five", 5) # filled_dict["five"] is set to 5
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filled_dict.setdefault("five", 6) # filled_dict["five"] is still 5
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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
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some_set = set([1,2,2,3,4]) # some_set is now set([1, 2, 3, 4])
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some_set = set([1, 2, 2, 3, 4]) # some_set is now set([1, 2, 3, 4])
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# Since Python 2.7, {} can be used to declare a set
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filled_set = {1, 2, 2, 3, 4} # => {1, 2, 3, 4}
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filled_set = {1, 2, 2, 3, 4} # => {1, 2, 3, 4}
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# Add more items to a set
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filled_set.add(5) # filled_set is now {1, 2, 3, 4, 5}
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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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other_set = {3, 4, 5, 6}
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filled_set & other_set #=> {3, 4, 5}
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filled_set & other_set # => {3, 4, 5}
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# Do set union with |
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filled_set | other_set #=> {1, 2, 3, 4, 5, 6}
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filled_set | other_set # => {1, 2, 3, 4, 5, 6}
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# Do set difference with -
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{1,2,3,4} - {2,3,5} #=> {1, 4}
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{1, 2, 3, 4} - {2, 3, 5} # => {1, 4}
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# Check for existence in a set with in
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2 in filled_set #=> True
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10 in filled_set #=> False
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2 in filled_set # => True
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10 in filled_set # => False
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####################################################
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@ -337,17 +339,18 @@ def add(x, y):
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return x + y # Return values with a return statement
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# Calling functions with parameters
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add(5, 6) #=> prints out "x is 5 and y is 6" and returns 11
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add(5, 6) # => prints out "x is 5 and y is 6" and returns 11
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# Another way to call functions is with keyword arguments
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add(y=6, x=5) # Keyword arguments can arrive in any order.
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# You can define functions that take a variable number of
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# positional arguments
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def varargs(*args):
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return args
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varargs(1, 2, 3) #=> (1,2,3)
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varargs(1, 2, 3) # => (1, 2, 3)
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# You can define functions that take a variable number of
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@ -356,7 +359,8 @@ def keyword_args(**kwargs):
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return kwargs
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# Let's call it to see what happens
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keyword_args(big="foot", loch="ness") #=> {"big": "foot", "loch": "ness"}
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keyword_args(big="foot", loch="ness") # => {"big": "foot", "loch": "ness"}
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# You can do both at once, if you like
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def all_the_args(*args, **kwargs):
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@ -372,9 +376,10 @@ 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 foo(1, 2, 3, 4)
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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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all_the_args(*args) # equivalent to foo(1, 2, 3, 4)
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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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# Python has first class functions
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def create_adder(x):
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@ -383,23 +388,24 @@ def create_adder(x):
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return adder
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add_10 = create_adder(10)
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add_10(3) #=> 13
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add_10(3) # => 13
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# There are also anonymous functions
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(lambda x: x > 2)(3) #=> True
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(lambda x: x > 2)(3) # => True
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# There are built-in higher order functions
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map(add_10, [1,2,3]) #=> [11, 12, 13]
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filter(lambda x: x > 5, [3, 4, 5, 6, 7]) #=> [6, 7]
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map(add_10, [1, 2, 3]) # => [11, 12, 13]
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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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[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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[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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####################################################
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## 5. Classes
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####################################################
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# We subclass from object to get a class.
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class Human(object):
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@ -413,7 +419,7 @@ class Human(object):
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# An instance method. All methods take "self" as the first argument
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def say(self, msg):
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return "%s: %s" % (self.name, msg)
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return "%s: %s" % (self.name, msg)
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# A class method is shared among all instances
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# They are called with the calling class as the first argument
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@ -432,18 +438,18 @@ i = Human(name="Ian")
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print(i.say("hi")) # prints out "Ian: hi"
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j = Human("Joel")
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print(j.say("hello")) #prints out "Joel: hello"
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print(j.say("hello")) # prints out "Joel: hello"
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# Call our class method
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i.get_species() #=> "H. sapiens"
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i.get_species() # => "H. sapiens"
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# Change the shared attribute
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Human.species = "H. neanderthalensis"
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i.get_species() #=> "H. neanderthalensis"
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j.get_species() #=> "H. neanderthalensis"
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i.get_species() # => "H. neanderthalensis"
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j.get_species() # => "H. neanderthalensis"
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# Call the static method
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Human.grunt() #=> "*grunt*"
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Human.grunt() # => "*grunt*"
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####################################################
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@ -452,12 +458,12 @@ Human.grunt() #=> "*grunt*"
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# You can import modules
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import math
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print(math.sqrt(16) )#=> 4
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print(math.sqrt(16)) # => 4
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# You can get specific functions from a module
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from math import ceil, floor
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print(ceil(3.7)) #=> 4.0
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print(floor(3.7)) #=> 3.0
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print(ceil(3.7)) # => 4.0
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print(floor(3.7)) # => 3.0
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# You can import all functions from a module.
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# Warning: this is not recommended
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@ -465,7 +471,7 @@ from math import *
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# You can shorten module names
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import math as m
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math.sqrt(16) == m.sqrt(16) #=> True
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math.sqrt(16) == m.sqrt(16) # => True
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# Python modules are just ordinary python files. You
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# can write your own, and import them. The name of the
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@ -486,10 +492,12 @@ def double_numbers(iterable):
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for i in iterable:
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yield i + i
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# generator creates the value on the fly
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# instead of generating and returning all values at once it creates one in each iteration
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# this means values bigger than 15 wont be processed in double_numbers
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# note range is a generator too, creating a list 1-900000000 would take lot of time to be made
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# A generator creates values on the fly.
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# Instead of generating and returning all values at once it creates one in each
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# iteration. This means values bigger than 15 wont be processed in
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# 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 :(
|
||||
|
||||
|
||||
```
|
||||
|
||||
## Ready For More?
|
||||
|
||||
Loading…
Reference in New Issue
Block a user