filter(function, sequence):对sequence中的item依次执行function(item),将执行结果为True的item组成一个List/String/Tuple(取决于sequence的类型)返回:
>>> def f(x): return x % 2 != 0 and x % 3 != 0
>>> filter(f, range(2, 25))
[5, 7, 11, 13, 17, 19, 23]
>>> def f(x): return x != 'a'
>>> filter(f, "abcdef")
'bcdef'
map(function, sequence) :对sequence中的item依次执行function(item),见执行结果组成一个List返回:
>>> def cube(x): return x*x*x
>>> map(cube, range(1, 11))
[1, 8, 27, 64, 125, 216, 343, 512, 729, 1000]
>>> def cube(x) : return x + x
...
>>> map(cube , "abcde")
['aa', 'bb', 'cc', 'dd', 'ee']
另外map也支持多个sequence,这就要求function也支持相应数量的参数输入:
>>> def add(x, y): return x+y
>>> map(add, range(8), range(8))
[0, 2, 4, 6, 8, 10, 12, 14]
reduce(function, sequence, starting_value):对sequence中的item顺序迭代调用function,如果有starting_value,还可以作为初始值调用,例如可以用来对List求和:
>>> def add(x,y): return x + y
>>> reduce(add, range(1, 11))
55 (注:1+2+3+4+5+6+7+8+9+10)
>>> reduce(add, range(1, 11), 20)
75 (注:1+2+3+4+5+6+7+8+9+10+20)
lambda:这是Python支持一种有趣的语法,它允许你快速定义单行的最小函数,类似与C语言中的宏,这些叫做lambda的函数,是从LISP借用来的,可以用在任何需要函数的地方:
>>> g = lambda x: x * 2
>>> g(3)
6
>>> (lambda x: x * 2)(3)
6
我们也可以把filter map reduce 和lambda结合起来用,函数就可以简单的写成一行。
例如:
kmpathes = filter(lambda kmpath: kmpath,
map(lambda kmpath: string.strip(kmpath),
string.split(l, ':')))
看起来麻烦,其实就像用语言来描述问题一样,非常优雅。
对 l 中的所有元素以':'做分割,得出一个列表。对这个列表的每一个元素做字符串strip,形成一个列表。对这个列表的每一个元素做直接返回操作(这个地方可以加上过滤条件限制),最终获得一个字符串被':'分割的列表,列表中的每一个字符串都做了strip,并可以对特殊字符串过滤。
---------------------------------------------------------------
lambda表达式返回一个函数对象
例子:
func = lambda x,y:x+y
func相当于下面这个函数
def func(x,y):
return x+y
注意def是语句而lambda是表达式
下面这种情况下就只能用lambda而不能用def
[(lambda x:x*x)(x) for x in range(1,11)]
map,reduce,filter中的function都可以用lambda表达式来生成!
map(function,sequence)
把sequence中的值当参数逐个传给function,返回一个包含函数执行结果的list。
如果function有两个参数,即map(function,sequence1,sequence2)。
例子:
求1*1,2*2,3*3,4*4
map(lambda x:x*x,range(1,5))
返回值是[1,4,9,16]
reduce(function,sequence)
function接收的参数个数只能为2
先把sequence中第一个值和第二个值当参数传给function,再把function的返回值和第三个值当参数传给
function,然后只返回一个结果。
例子:
求1到10的累加
reduce(lambda x,y:x+y,range(1,11))
返回值是55。
filter(function,sequence)
function的返回值只能是True或False
把sequence中的值逐个当参数传给function,如果function(x)的返回值是True,就把x加到filter的返回值里面。一般来说filter的返回值是list,特殊情况如sequence是string或tuple,则返回值按照sequence的类型。
例子:
找出1到10之间的奇数
filter(lambda x:x%2!=0,range(1,11))
返回值
[1,3,5,7,9]
如果sequence是一个string
filter(lambda x:len(x)!=0,'hello')返回'hello'
filter(lambda x:len(x)==0,'hello')返回''

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

Python's real-world applications include data analytics, web development, artificial intelligence and automation. 1) In data analysis, Python uses Pandas and Matplotlib to process and visualize data. 2) In web development, Django and Flask frameworks simplify the creation of web applications. 3) In the field of artificial intelligence, TensorFlow and PyTorch are used to build and train models. 4) In terms of automation, Python scripts can be used for tasks such as copying files.

Python is widely used in data science, web development and automation scripting fields. 1) In data science, Python simplifies data processing and analysis through libraries such as NumPy and Pandas. 2) In web development, the Django and Flask frameworks enable developers to quickly build applications. 3) In automated scripts, Python's simplicity and standard library make it ideal.

Python's flexibility is reflected in multi-paradigm support and dynamic type systems, while ease of use comes from a simple syntax and rich standard library. 1. Flexibility: Supports object-oriented, functional and procedural programming, and dynamic type systems improve development efficiency. 2. Ease of use: The grammar is close to natural language, the standard library covers a wide range of functions, and simplifies the development process.

Python is highly favored for its simplicity and power, suitable for all needs from beginners to advanced developers. Its versatility is reflected in: 1) Easy to learn and use, simple syntax; 2) Rich libraries and frameworks, such as NumPy, Pandas, etc.; 3) Cross-platform support, which can be run on a variety of operating systems; 4) Suitable for scripting and automation tasks to improve work efficiency.

Yes, learn Python in two hours a day. 1. Develop a reasonable study plan, 2. Select the right learning resources, 3. Consolidate the knowledge learned through practice. These steps can help you master Python in a short time.


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