The key to using Python to call WebAPI to obtain data is to master the basic processes and common tools. 1. Using requests to initiate HTTP requests is the most direct way. Use the get method to obtain the response and use json() to parse the data; 2. For APIs that need authentication, you can add tokens or keys through headers; 3. You need to check the response status code, it is recommended to use response.raise_for_status() to automatically handle exceptions; 4. Facing the paging interface, you can request different pages in turn and add delays to avoid frequency limitations; 5. When processing the returned JSON data, you need to extract information according to the structure, and complex data can be converted to Data

Updating a JSON file requires three steps: reading, modifying, and writing. 1. Use json.load() to read the file into a Python data structure; 2. Access the modified value through keys such as data['age']=31 or nested modification; 3. Use json.dump(data,f) to save the changes back to the file and it is recommended to add indent to beautify the output. Before operation, you should confirm that the file exists and backups should be made if necessary. Remote data must be processed in conjunction with the requests module.

Using Python's multiprocessing module can improve performance, but attention should be paid to startup methods, Pool usage, process communication and exception handling. 1. Choose the appropriate startup method: fork (Unix fast but unstable), spawn (cross-platform recommendation), forkserver (property-suitable for frequent creation); 2. Use Pool to manage concurrent tasks, control the number of processes, and reasonably select map or apply_async; 3. Inter-process communication can be used to provide Queue, Pipe, Value, Array or Manager, pay attention to performance and security; 4. Strengthen exception handling, use logging to debug, and can be simulated by a single process during development.

In Python, the following points should be noted when merging strings using the join() method: 1. Use the str.join() method, the previous string is used as a linker when calling, and the iterable object in the brackets contains the string to be connected; 2. Make sure that the elements in the list are all strings, and if they contain non-string types, they need to be converted first; 3. When processing nested lists, you must flatten the structure before connecting.

To master Python web crawlers, you need to grasp three core steps: 1. Use requests to initiate a request, obtain web page content through get method, pay attention to setting headers, handling exceptions, and complying with robots.txt; 2. Use BeautifulSoup or XPath to extract data. The former is suitable for simple parsing, while the latter is more flexible and suitable for complex structures; 3. Use Selenium to simulate browser operations for dynamic loading content. Although the speed is slow, it can cope with complex pages. You can also try to find a website API interface to improve efficiency.

Magic methods (dunder methods) in Python are special methods used to customize object behavior. They start and end with a double underscore, such as __init__ or __str__, and are automatically triggered when a specific syntax or built-in function is used. 1.__init__ is used to initialize the object; 2.__str__ and __repr__ define the readable string representation and reconstructible expression of the object respectively; 3.__add__, __sub__, etc. define the addition and subtraction operation behaviors; 4. Control and comparison operations such as __eq__, __lt__, etc. Implementing these methods, such as adding __add__ to custom class Point to support operations, makes the class behave more naturally and in line with expectations. make

Prettier configuration steps include installing plug-ins, setting default formatting tools, creating configuration files, enabling save automatic formatting, and other precautions. First, install the Prettier plug-in of VSCode and set it as the default formatting tool; second, create the .prettierrc file in the project root directory to define the format rules; then enable "FormatOnSave" in the VSCode settings; finally pay attention to installing local Prettier, ensuring the configuration file is correct, and troubleshooting plug-in interference problems.

There are three common methods for deduplication in Python. 1. Use set deduplication: It is suitable for situations where you don’t care about the order, and is implemented through list(set(my_list)). The advantage is that it is simple and fast, and the disadvantage is to disrupt the order; 2. Manually judge the deduplication: By traversing the original list and determining whether the elements already exist in the new list, the elements that appear for the first time are retained, which is suitable for scenarios where order needs to be maintained; 3. dict.fromkeys() deduplication: supported by Python 3.7, implemented through list(dict.fromkeys(my_list)), which maintains both the order and the writing method is concise. It is recommended to use modern Python. Notes include first converting the structure when dealing with non-hashable elements. It is recommended to use large data sets.