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python语法十分钟

2016-01-04 15:49 537 查看
# 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(构造函数)
    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)
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