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495 lines
13 KiB
Markdown
495 lines
13 KiB
Markdown
---
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language: python
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contributors:
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- ["Louie Dinh", "http://ldinh.ca"]
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- ["Amin Bandali", "http://aminbandali.com"]
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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 90's. 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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Feedback would be highly appreciated! You can reach me at [@louiedinh](http://twitter.com/louiedinh) or louiedinh [at] [google's email service]
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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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"""
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####################################################
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## 1. Primitive Datatypes and Operators
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####################################################
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# You have numbers
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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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# 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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# 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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# Enforce precedence with parentheses
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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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# Equality is ==
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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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# 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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# Comparisons can be chained!
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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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# A string can be treated like a list of characters
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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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# A newer way to format strings is the format method.
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# This method is the preferred way
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"{0} can be {1}".format("strings", "formatted")
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# You can use keywords if you don't want to count.
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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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# 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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# 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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# very useful when dealing with objects.
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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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####################################################
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## 2. Variables and Collections
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####################################################
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# Python has a print function, available in versions 2.7 and 3...
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print("I'm Python. Nice to meet you!")
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# and an older print statement, in all 2.x versions but removed from 3.
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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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# 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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# Lists store sequences
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li = []
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# You can start with a prefilled list
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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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# Remove from the end with pop
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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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# Look at the last element
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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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# 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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# Omit the beginning
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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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# Revert the list
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li[::-1] #=> [3, 4, 2, 1]
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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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# 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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# 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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# Check for existence in a list with "in"
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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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# 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] = 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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# 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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# Tuples are created by default if you leave out the parentheses
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d, e, f = 4, 5, 6
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# Now look how easy it is to swap two values
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e, d = d, e # d is now 5 and e is now 4
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# Dictionaries store mappings
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empty_dict = {}
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# Here is a prefilled dictionary
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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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# Get all keys as a list with "keys()"
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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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# 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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# Looking up a non-existing key is a 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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# 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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# "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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# 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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# 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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# 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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# 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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# Do set union with |
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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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# 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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####################################################
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## 3. Control Flow
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####################################################
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# Let's just make a variable
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some_var = 5
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# Here is an if statement. Indentation is significant in python!
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# prints "some_var is smaller than 10"
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if some_var > 10:
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print("some_var is totally bigger than 10.")
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elif some_var < 10: # This elif clause is optional.
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print("some_var is smaller than 10.")
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else: # This is optional too.
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print("some_var is indeed 10.")
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"""
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For loops iterate over lists
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prints:
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dog is a mammal
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cat is a mammal
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mouse is a mammal
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"""
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for animal in ["dog", "cat", "mouse"]:
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# You can use % to interpolate formatted strings
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print("%s is a mammal" % animal)
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"""
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"range(number)" returns a list 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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1
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2
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3
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"""
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for i in range(4):
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print(i)
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"""
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While loops go until a condition is no longer met.
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prints:
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0
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1
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2
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3
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"""
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x = 0
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while x < 4:
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print(x)
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x += 1 # Shorthand for x = x + 1
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# Handle exceptions with a try/except block
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# Works on Python 2.6 and up:
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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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####################################################
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## 4. Functions
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####################################################
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# Use "def" to create new functions
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def add(x, y):
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print("x is %s and y is %s" % (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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# 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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# You can define functions that take a variable number of
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# keyword arguments, as well
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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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# You can do both at once, if you like
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def all_the_args(*args, **kwargs):
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print(args)
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print(kwargs)
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"""
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all_the_args(1, 2, a=3, b=4) prints:
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(1, 2)
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{"a": 3, "b": 4}
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"""
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# When calling functions, you can do the opposite of args/kwargs!
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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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# Python has first class functions
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def create_adder(x):
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def adder(y):
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return x + y
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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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# There are also anonymous functions
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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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# 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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####################################################
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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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# A class attribute. It is shared by all instances of this class
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species = "H. sapiens"
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# Basic initializer
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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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# 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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# 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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@classmethod
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def get_species(cls):
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return cls.species
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# A static method is called without a class or instance reference
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@staticmethod
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def grunt():
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return "*grunt*"
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# Instantiate a class
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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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# Call our class method
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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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# Call the static method
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Human.grunt() #=> "*grunt*"
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####################################################
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## 6. Modules
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####################################################
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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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# 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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# You can import all functions from a module.
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# Warning: this is not recommended
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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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# 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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# module is the same as the name of the file.
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# You can find out which functions and attributes
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# defines a module.
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import math
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dir(math)
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```
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## Ready For More?
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### Free Online
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* [Learn Python The Hard Way](http://learnpythonthehardway.org/book/)
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* [Dive Into Python](http://www.diveintopython.net/)
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* [The Official Docs](http://docs.python.org/2.6/)
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* [Hitchhiker's Guide to Python](http://docs.python-guide.org/en/latest/)
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* [Python Module of the Week](http://pymotw.com/2/)
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* [A Crash Course in Python for Scientists](http://nbviewer.ipython.org/5920182)
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### Dead Tree
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* [Programming Python](http://www.amazon.com/gp/product/0596158106/ref=as_li_qf_sp_asin_tl?ie=UTF8&camp=1789&creative=9325&creativeASIN=0596158106&linkCode=as2&tag=homebits04-20)
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* [Dive Into Python](http://www.amazon.com/gp/product/1441413022/ref=as_li_tf_tl?ie=UTF8&camp=1789&creative=9325&creativeASIN=1441413022&linkCode=as2&tag=homebits04-20)
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* [Python Essential Reference](http://www.amazon.com/gp/product/0672329786/ref=as_li_tf_tl?ie=UTF8&camp=1789&creative=9325&creativeASIN=0672329786&linkCode=as2&tag=homebits04-20)
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