一篇非常好的文章，解释了python基本语法的方方面面：
# Single line comments start with a hash. """ Multiline strings can be written using three "'s, and are often used as comments """ #################################################### ## 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. 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 # 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' # % can be used to format strings, like this: "%s can be %s" % ("strings", "interpolated") # A newer way to format strings is the format method. # This method is the preferred way "{0} can be {1}".format("strings", "formatted") # You can use keywords if you don't want to count. "{name} wants to eat {food}".format(name="Bob", food="lasagna") # None is an object None #=> None # Don't use the equality "==" symbol to compare objects to None # Use "is" instead "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 # very useful when dealing with objects. # None, 0, and empty strings/lists all evaluate to False. # All other values are True 0 == False #=> True "" == False #=> True #################################################### ## 2. Variables and Collections #################################################### # Python has a print function, available in versions 2.7 and 3... print("I'm Python. Nice to meet you!") # and an older print statement, in all 2.x versions but removed from 3. 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 # 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!" # 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 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] # Omit the beginning li[2:] #=> [4, 3] # Omit the end li[:3] #=> [1, 2, 4] # 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 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 # 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 # 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 with "keys()" 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] # 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 # Looking up a non-existing key is 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()" 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 # 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]) # Since Python 2.7, {} can be used to declare a set 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} # Do set intersection with & other_set = {3, 4, 5, 6} filled_set & other_set #=> {3, 4, 5} # Do set union with | filled_set | other_set #=> {1, 2, 3, 4, 5, 6} # Do set difference with - {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 #################################################### ## 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) """ "range(number)" returns a list of numbers from zero to the given number prints: 0 1 2 3 """ for i in range(4): print(i) """ 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. #################################################### ## 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) #=> 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) # 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} """ # When calling functions, you can do the opposite of args/kwargs! # 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) # 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*" #################################################### ## 6. Modules #################################################### # You can import modules import math 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 # You can import all functions from a module. # Warning: this is not recommended from math import * # You can shorten module names import math as m 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 # module is the same as the name of the file. # You can find out which functions and attributes # defines a module. import math dir(math)