filter(function or None, sequence), where sequence can be list, tuple, string. The function of this function is to filter out all elements in the sequence that return True or bool (return value) as True when the function is called with the element itself as a parameter and return it as a list. The filter can only accept two parameters (function, sequence), among which the function Only one value can be returned in the function
Let’s start with a simple code:
print max(filter(lambda x: 555555 % x == 0, range(100, 999)))
The code means to output the divisor of the largest three-digit number of 555555.
First of all, the first knowledge point of this code is python’s built-in function filter
filter() function, which is used to filter lists. The simplest way to put it is to use a function to filter a list, pass each item in the list into the filter function, and delete the item from the list when the filter function returns false.
filter() function includes two parameters, function and list. That is, the function filters the items in the list parameter based on whether the result returned by the function parameter is true, and finally returns a new list.
Simply speaking, the filter() function is equivalent to the following code:
c = [b for b in a1 if b > 2] print c
The second knowledge point is the lambda() function
Python supports this syntax, which allows users to quickly define a single-line minimal function , these functions, called lambdas, are borrowed from Lisp.
def f(x): return x * 2 g = lambda x: x * 2 (lambda x: x * 2)(3)
As you can see from the code, the lambda function completes the same thing as the ordinary function, and the lambda has no brackets around the parameter list and ignores the return keyword (return exists implicitly because the entire function only has one line , and the function has no name, but it can be assigned to a variable and called)
The last piece of code shows that the lambda function is just an inline function.

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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