--- language: python author: Louie Dinh author_url: http://ldinh.ca --- Python was created by Guido Van Rossum in the early 90's. It is now one of the most popular languages in existence. I fell in love with Python for it's syntactic clarity. It's basically executable pseudocode. 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 comments can we written using three "'s """ #################################################### ## 1. Primitive Datatypes and Operators #################################################### # You have numbers 3 #=> 3 # Math is what you would expect 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. 11 / 4 #=> 2 # To fix division we need to learn about floats. 2.0 # This is a float 5.0 / 2.0 #=> 2.5 ahhh...much better # Enforce precedence with parentheses (1 + 3) * 2 #=> 8 # Boolean values are primitives True False # negate with not not True #=> False not False #=> True # Equality is == 1 == 1 #=> True 2 == 1 #=> False # Inequality is != 1 != 1 #=> False 2 != 1 #=> True # More comparisons 1 < 10 #=> True 1 > 10 #=> False 2 <= 2 #=> True 2 >= 2 #=> True # Comparisons can be chained ! 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!" # A string can be treated like a list of characters "This is a string"[0] #=> 'T' # None is an object None #=> None #################################################### ## 2. Variables and Collections #################################################### # Printing is pretty easy print "I'm Python. Nice to meet you!" # No need to declare variables before assigning to them. some_var = 5 # Convention is to use lower_case_with_underscores some_var #=> 5 # Accessing a previously unassigned variable is an exception try: some_other_var except NameError: print "Raises a name error" # Conditional Expressions can be used when assigning some_var = a if a > b else b # If a is greater than b, then a is assigned to some_var. # Otherwise b is assigned to some_var. # Lists store sequences li = [] # You can start with a prefilled list 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] # Remove from the end with pop 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 # Look at the last element li[-1] #=> 3 # Looking out of bounds is an IndexError try: li[4] # Raises an IndexError except IndexError: print "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] # Omit the beginning li[:3] #=> [1, 2, 4] # Omit the end li[2:] #=> [4, 3] # Remove arbitrary elements from a list with del 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 # Concatenate lists with extend 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 # Examine the length with len len(li) #=> 6 # Tuples are like lists but are immutable. tup = (1, 2, 3) tup[0] #=> 1 try: tup[0] = 3 # Raises a TypeError except TypeError: print "Tuples cannot be mutated." # 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 # You can unpack tuples into variables a, b, c = (1, 2, 3) # a is now 1, b is now 2 and c is now 3 # Tuples are created by default if you leave out the parentheses d, e, f = 4, 5, 6 # Now look how easy it is to swap two values e, d = d, e # d is now 5 and e is now 4 # Dictionaries store mappings empty_dict = {} # Here is a prefilled dictionary filled_dict = {"one": 1, "two": 2, "three": 3} # Look up values with [] filled_dict["one"] #=> 1 # Get all keys as a list 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 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 # Trying to look up a non-existing key will raise a KeyError filled_dict["four"] #=> KeyError # Use get method to avoid the KeyError 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 # Setdefault method is a safe way to add new key-value pair into dictionary 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 filled_set = set([1,2,2,3,4]) # filled_set is now set([1, 2, 3, 4]) # Add more items to a set filled_set.add(5) # filled_set is now set([1, 2, 3, 4, 5]) # Do set intersection with & other_set = set([3, 4, 5 ,6]) filled_set & other_set #=> set([3, 4, 5]) # Do set union with | filled_set | other_set #=> set([1, 2, 3, 4, 5, 6]) # Do set difference with - set([1,2,3,4]) - set([2,3,5]) #=> set([1, 4]) # Check for existence in a set with in 2 in filled_set #=> True 10 in filled_set #=> False #################################################### ## 3. Control Flow #################################################### # Let's just make a variable some_var = 5 # Here is an if statement. INDENTATION IS SIGNIFICANT IN PYTHON! # prints "some var is smaller than 10" if some_var > 10: print "some_var is totally bigger than 10." elif some_var < 10: # This elif clause is optional. print "some_var is smaller than 10." else: # This is optional too. print "some_var is indeed 10." """ For loops iterate over lists prints: dog is a mammal cat is a mammal mouse is a mammal """ for animal in ["dog", "cat", "mouse"]: # You can use % to interpolate formatted strings print "%s is a mammal" % animal """ While loops go until a condition is no longer met. prints: 0 1 2 3 """ x = 0 while x < 4: print x x += 1 # Shorthand for x = x + 1 # Handle exceptions with a try/except block # Works on Python 2.6 and up: try: # Use raise to raise an error raise IndexError("This is an index error") except IndexError as e: pass # Pass is just a no-op. Usually you would do recovery here. # Works for Python 2.7 and down: try: raise IndexError("This is an index error") except IndexError, e: # No "as", comma instead pass #################################################### ## 4. Functions #################################################### # Use def to create new functions def add(x, y): print "x is %s and y is %s" % (x, y) return x + y # Return values with a return statement # Calling functions with parameters add(5, 6) #=> 11 and prints out "x is 5 and y is 6" # 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) # You can define functions that take a variable number of # keyword arguments, as well def keyword_args(**kwargs): return kwargs # Let's call it to see what happens 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): print args print kwargs """ all_the_args(1, 2, a=3, b=4) prints: [1, 2] {"a": 3, "b": 4} """ # You can also use * and ** when calling a function args = (1, 2, 3, 4) kwargs = {"a": 3, "b": 4} foo(*args) # equivalent to foo(1, 2, 3, 4) foo(**kwargs) # equivalent to foo(a=3, b=4) foo(*args, **kwargs) # equivalent to foo(1, 2, 3, 4, a=3, b=4) # Python has first class functions def create_adder(x): def adder(y): return x + y return adder add_10 = create_adder(10) add_10(3) #=> 13 # There are also anonymous functions (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] # 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] #################################################### ## 5. Classes #################################################### # We subclass from object to get a class. class Human(object): # A class attribute. It is shared by all instances of this class species = "H. sapiens" # Basic initializer def __init__(self, name): # Assign the argument to the instance's name attribute self.name = name # An instance method. All methods take self as the first argument def say(self, 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 @classmethod def get_species(cls): return cls.species # A static method is called without a class or instance reference @staticmethod def grunt(): return "*grunt*" # Instantiate a class i = Human(name="Ian") print i.say("hi") # prints out "Ian: hi" j = Human("Joel") print j.say("hello") #prints out "Joel: hello" # Call our class method i.get_species() #=> "H. sapiens" # Change the shared attribute Human.species = "H. neanderthalensis" i.get_species() #=> "H. neanderthalensis" j.get_species() #=> "H. neanderthalensis" # Call the static method Human.grunt() #=> "*grunt*" ```