[转][译] 分分钟学会一门语言之 Python 篇
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 its syntactic clarity. It's basically
executable pseudocode.
Python 是 90 年代初由 Guido Van Rossum 创立的。它是当前最流行的程序语言之一。它那纯净的语法令我一见倾心,它简直就是可以运行的伪码。
Feedback would be highly appreciated! You can reach me at @louiedinh or louiedinh [at] [google's email service]
非常欢迎您提交反馈!您可以通过 @louiedinh 联系到我,也可以发邮件到 louiedinh
开头的 Google Email 账号。
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!
请注意:本文以 Python 2.7 为基准,但也应该适用于所有 2.X 版本。记得继续学习未来的 Python 3 哦!
# Single line comments start with a hash.
# 单行注释由一个井号开头。
""" Multiline strings can be written
using three "'s, and are often used
as comments
三个双引号(或单引号)之间可以写多行字符串,
通常用来写注释。
"""
####################################################
## 1. Primitive Datatypes and Operators
## 1. 基本数据类型和操作符
####################################################
# You have numbers
# 数字就是数字
3 #=> 3
# Math is what you would expect
# 四则运算也是你所期望的那样
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.
# 除法有一点棘手。
# 对于整数除法来说,计算结果会自动取整。
5 / 2 #=> 2
# To fix division we need to learn about floats.
# 为了修正除法的问题,我们需要先学习浮点数。
2.0 # This is a float
2.0 # 这是一个浮点数
11.0 / 4.0 #=> 2.75 ahhh...much better
11.0 / 4.0 #=> 2.75 啊……这样就好多了
# Enforce precedence with parentheses
# 使用小括号来强制计算的优先顺序
(1 + 3) * 2 #=> 8
# Boolean values are primitives
# 布尔值也是基本数据类型
True
False
# negate with not
# 使用 not 来取反
not True #=> False
not False #=> True
# Equality is ==
# 等式判断用 ==
1 == 1 #=> True
2 == 1 #=> False
# Inequality is !=
# 不等式判断是用 !=
1 != 1 #=> False
2 != 1 #=> True
# More comparisons
# 还有更多的比较运算
1 < 10 #=> True
1 > 10 #=> False
2 <= 2 #=> True
2 >= 2 #=> True
# Comparisons can be chained!
# 居然可以把比较运算串连起来!
1 < 2 < 3 #=> True
2 < 3 < 2 #=> False
# Strings are created with " or '
# 使用 " 或 ' 来创建字符串
"This is a string."
'This is also a string.'
# Strings can be added too!
# 字符串也可以相加!
"Hello " + "world!" #=> "Hello world!"
# A string can be treated like a list of characters
# 一个字符串可以视为一个字符的列表
# (译注:后面会讲到“列表”。)
"This is a string"[0] #=> 'T'
# % can be used to format strings, like this:
# % 可以用来格式化字符串,就像这样:
"%s can be %s" % ("strings", "interpolated")
# A newer way to format strings is the format method.
# This method is the preferred way
# 后来又有一种格式化字符串的新方法:format 方法。
# 我们推荐使用这个方法。
"{0} can be {1}".format("strings", "formatted")
# You can use keywords if you don't want to count.
# 如果你不喜欢数数的话,可以使用关键字(变量)。
"{name} wants to eat {food}".format(name="Bob", food="lasagna")
# None is an object
# None 是一个对象
None #=> None
# Don't use the equality `==` symbol to compare objects to None
# Use `is` instead
# 不要使用相等符号 `==` 来把对象和 None 进行比较,
# 而要用 `is`。
"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.
# 这个 `is` 操作符用于比较两个对象的标识。
# (译注:对象一旦建立,其标识就不会改变,可以认为它就是对象的内存地址。)
# 在处理基本数据类型时基本用不上,
# 但它在处理对象时很有用。
# None, 0, and empty strings/lists all evaluate to False.
# All other values are True
# None、0 以及空字符串和空列表都等于 False,
# 除此以外的所有值都等于 True。
0 == False #=> True
"" == False #=> True
####################################################
## 2. Variables and Collections
## 2. 变量和集合
####################################################
# Printing is pretty easy
# 打印输出很简单
print "I'm Python. Nice to meet you!"
# No need to declare variables before assigning to them.
# 在赋值给变量之前不需要声明
some_var = 5 # Convention is to use lower_case_with_underscores
# 变量名的约定是使用下划线分隔的小写单词
some_var #=> 5
# Accessing a previously unassigned variable is an exception.
# See Control Flow to learn more about exception handling.
# 访问一个未赋值的变量会产生一个异常。
# 进一步了解异常处理,可参见下一节《控制流》。
some_other_var # Raises a name error
# 会抛出一个名称错误
# if can be used as an expression
# if 可以作为表达式来使用
"yahoo!" if 3 > 2 else 2 #=> "yahoo!"
# Lists store sequences
# 列表用于存储序列
li = []
# You can start with a prefilled list
# 我们先尝试一个预先填充好的列表
other_li = [4, 5, 6]
# Add stuff to the end of a list with append
# 使用 append 方法把元素添加到列表的尾部
li.append(1) #li is now [1]
#li 现在是 [1]
li.append(2) #li is now [1, 2]
#li 现在是 [1, 2]
li.append(4) #li is now [1, 2, 4]
#li 现在是 [1, 2, 4]
li.append(3) #li is now [1, 2, 4, 3]
#li 现在是 [1, 2, 4, 3]
# Remove from the end with pop
# 使用 pop 来移除最后一个元素
li.pop() #=> 3 and li is now [1, 2, 4]
#=> 3,然后 li 现在是 [1, 2, 4]
# Let's put it back
# 我们再把它放回去
li.append(3) # li is now [1, 2, 4, 3] again.
# li 现在又是 [1, 2, 4, 3] 了
# Access a list like you would any array
# 像访问其它语言的数组那样访问列表
li[0] #=> 1
# Look at the last element
# 查询最后一个元素
li[-1] #=> 3
# Looking out of bounds is an IndexError
# 越界查询会产生一个索引错误
li[4] # Raises an IndexError
# 抛出一个索引错误
# You can look at ranges with slice syntax.
# (It's a closed/open range for you mathy types.)
# 你可以使用切片语法来查询列表的一个范围。
# (这个范围相当于数学中的左闭右开区间。)
li[1:3] #=> [2, 4]
# Omit the beginning
# 省略开头
li[2:] #=> [4, 3]
# Omit the end
# 省略结尾
li[:3] #=> [1, 2, 4]
# Remove arbitrary elements from a list with del
# 使用 del 来删除列表中的任意元素
del li[2] # li is now [1, 2, 3]
# li 现在是 [1, 2, 3]
# You can add lists
# 可以把列表相加
li + other_li #=> [1, 2, 3, 4, 5, 6] - Note: li and other_li is left alone
#=> [1, 2, 3, 4, 5, 6] - 请留意 li 和 other_li 并不会被修改
# Concatenate lists with extend
# 使用 extend 来合并列表
li.extend(other_li) # Now li is [1, 2, 3, 4, 5, 6]
# 现在 li 是 [1, 2, 3, 4, 5, 6]
# Check for existence in a list with in
# 用 in 来检查是否存在于某个列表中
1 in li #=> True
# Examine the length with len
# 用 len 来检测列表的长度
len(li) #=> 6
# Tuples are like lists but are immutable.
# 元组很像列表,但它是“不可变”的。
tup = (1, 2, 3)
tup[0] #=> 1
tup[0] = 3 # Raises a TypeError
# 抛出一个类型错误
# You can do all those list thingies on tuples too
# 操作列表的方式通常也能用在元组身上
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
# 你可以把元组(或列表)中的元素解包赋值给多个变量
a, b, c = (1, 2, 3) # a is now 1, b is now 2 and c is now 3
# 现在 a 是 1,b 是 2,c 是 3
# Tuples are created by default if you leave out the parentheses
# 如果你省去了小括号,那么元组会被自动创建
d, e, f = 4, 5, 6
# Now look how easy it is to swap two values
# 再来看看交换两个值是多么简单。
e, d = d, e # d is now 5 and e is now 4
# 现在 d 是 5 而 e 是 4
# Dictionaries store mappings
# 字典用于存储映射关系
empty_dict = {}
# Here is a prefilled dictionary
# 这是一个预先填充的字典
filled_dict = {"one": 1, "two": 2, "three": 3}
# Look up values with []
# 使用 [] 来查询键值
filled_dict["one"] #=> 1
# Get all keys as a list
# 将字典的所有键名获取为一个列表
filled_dict.keys() #=> ["three", "two", "one"]
# Note - Dictionary key ordering is not guaranteed.
# Your results might not match this exactly.
# 请注意:无法保证字典键名的顺序如何排列。
# 你得到的结果可能跟上面的示例不一致。
# Get all values as a list
# 将字典的所有键值获取为一个列表
filled_dict.values() #=> [3, 2, 1]
# Note - Same as above regarding key ordering.
# 请注意:顺序的问题和上面一样。
# Check for existence of keys in a dictionary with in
# 使用 in 来检查一个字典是否包含某个键名
"one" in filled_dict #=> True
1 in filled_dict #=> False
# Looking up a non-existing key is a KeyError
# 查询一个不存在的键名会产生一个键名错误
filled_dict["four"] # KeyError
# 键名错误
# Use get method to avoid the KeyError
# 所以要使用 get 方法来避免键名错误
filled_dict.get("one") #=> 1
filled_dict.get("four") #=> None
# The get method supports a default argument when the value is missing
# get 方法支持传入一个默认值参数,将在取不到值时返回。
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
# Setdefault 方法可以安全地把新的名值对添加到字典里
filled_dict.setdefault("five", 5) #filled_dict["five"] is set to 5
#filled_dict["five"] 被设置为 5
filled_dict.setdefault("five", 6) #filled_dict["five"] is still 5
#filled_dict["five"] 仍然为 5
# Sets store ... well sets
# set 用于保存集合
empty_set = set()
# Initialize a set with a bunch of values
# 使用一堆值来初始化一个集合
some_set = set([1,2,2,3,4]) # some_set is now set([1, 2, 3, 4])
# some_set 现在是 set([1, 2, 3, 4])
# Since Python 2.7, {} can be used to declare a set
# 从 Python 2.7 开始,{} 可以用来声明一个集合
filled_set = {1, 2, 2, 3, 4} # => {1, 2, 3, 4}
# (译注:集合是种无序不重复的元素集,因此重复的 2 被滤除了。)
# (译注:{} 不会创建一个空集合,只会创建一个空字典。)
# Add more items to a set
# 把更多的元素添加进一个集合
filled_set.add(5) # filled_set is now {1, 2, 3, 4, 5}
# filled_set 现在是 {1, 2, 3, 4, 5}
# Do set intersection with &
# 使用 & 来获取交集
other_set = {3, 4, 5, 6}
filled_set & other_set #=> {3, 4, 5}
# Do set union with |
# 使用 | 来获取并集
filled_set | other_set #=> {1, 2, 3, 4, 5, 6}
# Do set difference with -
# 使用 - 来获取补集
{1,2,3,4} - {2,3,5} #=> {1, 4}
# Check for existence in a set with in
# 使用 in 来检查是否存在于某个集合中
2 in filled_set #=> True
10 in filled_set #=> False
####################################################
## 3. Control Flow
## 3. 控制流
####################################################
# Let's just make a variable
# 我们先创建一个变量
some_var = 5
# Here is an if statement. Indentation is significant in python!
# prints "some_var is smaller than 10"
# 这里有一个条件语句。缩进在 Python 中可是很重要的哦!
# 程序会打印出 "some_var is smaller than 10"
# (译注:意为“some_var 比 10 小”。)
if some_var > 10:
print "some_var is totally bigger than 10."
# (译注:意为“some_var 完全比 10 大”。)
elif some_var < 10: # This elif clause is optional.
# 这里的 elif 子句是可选的
print "some_var is smaller than 10."
# (译注:意为“some_var 比 10 小”。)
else: # This is optional too.
# 这一句也是可选的
print "some_var is indeed 10."
# (译注:意为“some_var 就是 10”。)
"""
For loops iterate over lists
for 循环可以遍历列表
prints:
如果要打印出:
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
# 别忘了你可以使用 % 来格式化字符串
print "%s is a mammal" % animal
# (译注:意为“%s 是哺乳动物”。)
"""
`range(number)` returns a list of numbers
from zero to the given number
`range(数字)` 会返回一个数字列表,
这个列表将包含从零到给定的数字。
prints:
如果要打印出:
0
1
2
3
"""
for i in range(4):
print i
"""
While loops go until a condition is no longer met.
while 循环会一直继续,直到条件不再满足。
prints:
如果要打印出:
0
1
2
3
"""
x = 0
while x < 4:
print x
x += 1 # Shorthand for x = x + 1
# 这是 x = x + 1 的简写方式
# Handle exceptions with a try/except block
# 使用 try/except 代码块来处理异常
# Works on Python 2.6 and up:
# 适用于 Python 2.6 及以上版本:
try:
# Use raise to raise an error
# 使用 raise 来抛出一个错误
raise IndexError("This is an index error")
# 抛出一个索引错误:“这是一个索引错误”。
except IndexError as e:
pass # Pass is just a no-op. Usually you would do recovery here.
# pass 只是一个空操作。通常你应该在这里做一些恢复工作。
####################################################
## 4. Functions
## 4. 函数
####################################################
# Use def to create new functions
# 使用 def 来创建新函数
def add(x, y):
print "x is %s and y is %s" % (x, y)
# (译注:意为“x 是 %s 而且 y 是 %s”。)
return x + y # Return values with a return statement
# 使用 return 语句来返回值
# Calling functions with parameters
# 调用函数并传入参数
add(5, 6) #=> prints out "x is 5 and y is 6" and returns 11
# (译注:意为“x 是 5 而且 y 是 6”,并返回 11)
# Another way to call functions is with keyword arguments
# 调用函数的另一种方式是传入关键字参数
add(y=6, x=5) # Keyword arguments can arrive in any order.
# 关键字参数可以以任意顺序传入
# You can define functions that take a variable number of
# positional arguments
# 你可以定义一个函数,并让它接受可变数量的定位参数。
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
# 你也可以定义一个函数,并让它接受可变数量的关键字参数。
def keyword_args(**kwargs):
return kwargs
# Let's call it to see what happens
# 我们试着调用它,看看会发生什么:
keyword_args(big="foot", loch="ness") #=> {"big": "foot", "loch": "ness"}
# You can do both at once, if you like
# 你还可以同时使用这两类参数,只要你愿意:
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 varargs/kwargs!
# Use * to expand tuples and use ** to expand kwargs.
# 在调用函数时,定位参数和关键字参数还可以反过来用。
# 使用 * 来展开元组,使用 ** 来展开关键字参数。
args = (1, 2, 3, 4)
kwargs = {"a": 3, "b": 4}
all_the_args(*args) # equivalent to foo(1, 2, 3, 4)
# 相当于 all_the_args(1, 2, 3, 4)
all_the_args(**kwargs) # equivalent to foo(a=3, b=4)
# 相当于 all_the_args(a=3, b=4)
all_the_args(*args, **kwargs) # equivalent to foo(1, 2, 3, 4, a=3, b=4)
# 相当于 all_the_args(1, 2, 3, 4, a=3, b=4)
# Python has first class functions
# 函数在 Python 中是一等公民
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
# 还有匿名函数
(lambda x: x > 2)(3) #=> True
# There are built-in higher order functions
# 还有一些内建的高阶函数
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
# 我们可以使用列表推导式来模拟 map 和 filter
[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
## 5. 类
####################################################
# We subclass from object to get a class.
# 我们可以从对象中继承,来得到一个类。
class Human(object):
# A class attribute. It is shared by all instances of this class
# 下面是一个类属性。它将被这个类的所有实例共享。
species = "H. sapiens"
# Basic initializer
# 基本的初始化函数(构建函数)
def __init__(self, name):
# Assign the argument to the instance's name attribute
# 把参数赋值为实例的 name 属性
self.name = name
# An instance method. All methods take self as the first argument
# 下面是一个实例方法。所有方法都以 self 作为第一个参数。
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
# 类方法会被所有实例共享。
# 类方法在调用时,会将类本身作为第一个函数传入。
@classmethod
def get_species(cls):
return cls.species
# A static method is called without a class or instance reference
# 静态方法在调用时,不会传入类或实例的引用。
@staticmethod
def grunt():
return "*grunt*"
# Instantiate a class
# 实例化一个类
i = Human(name="Ian")
print i.say("hi") # prints out "Ian: hi"
# 打印出 "Ian: hi"
j = Human("Joel")
print j.say("hello") # prints out "Joel: hello"
# 打印出 "Joel: hello"
# Call our class method
# 调用我们的类方法
i.get_species() #=> "H. sapiens"
# Change the shared attribute
# 修改共享属性
Human.species = "H. neanderthalensis"
i.get_species() #=> "H. neanderthalensis"
j.get_species() #=> "H. neanderthalensis"
# Call the static method
# 调用静态方法
Human.grunt() #=> "*grunt*"
####################################################
## 6. Modules
## 6. 模块
####################################################
# You can import modules
# 你可以导入模块
import math
print math.sqrt(16) #=> 4
# You can get specific functions from a module
# 也可以从一个模块中获取指定的函数
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
# 你可以从一个模块中导入所有函数
# 警告:不建议使用这种方式
from math import *
# You can shorten module names
# 你可以缩短模块的名称
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.
# Python 模块就是普通的 Python 文件。
# 你可以编写你自己的模块,然后导入它们。
# 模块的名称与文件名相同。
# You can find out which functions and attributes
# defines a module.
# 你可以查出一个模块里有哪些函数和属性
import math
dir(math)
Ready For More?
还没过瘾吗?
Free Online
免费在线阅读
- Learn Python The Hard Way
- Dive Into Python
- The Official Docs
- Hitchhiker's Guide to Python
- Python Module of the Week
Dead Tree
实体书
转自 https://github.com/cssmagic/blog/issues/24
吐槽。。什么程序都能分分钟学会了那还要程序猿干毛啊。。要说的话他这分分钟能实现的我c也能实现为什么一定要用PYTHON呢?
独立博客:http://nfeng.cc/