The key to dealing with API authentication is to understand and use the authentication method correctly. 1. APIKey is the simplest authentication method, usually placed in the request header or URL parameters; 2. BasicAuth uses username and password for Base64 encoding transmission, which is suitable for internal systems; 3. OAuth2 needs to obtain the token first through client_id and client_secret, and then bring the BearerToken in the request header; 4. In order to deal with the token expiration, the token management class can be encapsulated and automatically refreshed the token; in short, selecting the appropriate method according to the document and safely storing the key information is the key.

To test the API, you need to use Python's Requests library. The steps are to install the library, send requests, verify responses, set timeouts and retry. First, install the library through pipinstallrequests; then use requests.get() or requests.post() and other methods to send GET or POST requests; then check response.status_code and response.json() to ensure that the return result is in compliance with expectations; finally, add timeout parameters to set the timeout time, and combine the retrying library to achieve automatic retry to enhance stability.

In Python, variables defined inside a function are local variables and are only valid within the function; externally defined are global variables that can be read anywhere. 1. Local variables are destroyed as the function is executed; 2. The function can access global variables but cannot be modified directly, so the global keyword is required; 3. If you want to modify outer function variables in nested functions, you need to use the nonlocal keyword; 4. Variables with the same name do not affect each other in different scopes; 5. Global must be declared when modifying global variables, otherwise UnboundLocalError error will be raised. Understanding these rules helps avoid bugs and write more reliable functions.

The aggregation function is used to perform calculations on a set of values ??and return a single value. Common ones include COUNT, SUM, AVG, MAX, and MIN; GROUPBY groups data by one or more columns and applies an aggregation function to each group. For example, GROUPBYuser_id is required to count the total order amount of each user; SELECTuser_id, SUM(amount)FROMordersGROUPBYuser_id; non-aggregated fields must appear in GROUPBY; multiple fields can be used for multi-condition grouping; HAVING is used instead of WHERE after grouping; application scenarios such as counting the number of classified products, maximum ordering users, monthly sales trends, etc. Mastering these can effectively solve the number

MySQL's EXPLAIN is a tool used to analyze query execution plans. You can view the execution process by adding EXPLAIN before the SELECT query. 1. The main fields include id, select_type, table, type, key, Extra, etc.; 2. Efficient query needs to pay attention to type (such as const, eq_ref is the best), key (whether to use the appropriate index) and Extra (avoid Usingfilesort and Usingtemporary); 3. Common optimization suggestions: avoid using functions or blurring the leading wildcards for fields, ensure the consistent field types, reasonably set the connection field index, optimize sorting and grouping operations to improve performance and reduce capital

To create modern and efficient APIs using Python, FastAPI is recommended; it is based on standard Python type prompts and can automatically generate documents, with excellent performance. After installing FastAPI and ASGI server uvicorn, you can write interface code. By defining routes, writing processing functions, and returning data, APIs can be quickly built. FastAPI supports a variety of HTTP methods and provides automatically generated SwaggerUI and ReDoc documentation systems. URL parameters can be captured through path definition, while query parameters can be implemented by setting default values ??for function parameters. The rational use of Pydantic models can help improve development efficiency and accuracy.

Add timeout control to Python's for loop. 1. You can record the start time with the time module, and judge whether it is timed out in each iteration and use break to jump out of the loop; 2. For polling class tasks, you can use the while loop to match time judgment, and add sleep to avoid CPU fullness; 3. Advanced methods can consider threading or signal to achieve more precise control, but the complexity is high, and it is not recommended for beginners to choose; summary key points: manual time judgment is the basic solution, while is more suitable for time-limited waiting class tasks, sleep is indispensable, and advanced methods are suitable for specific scenarios.

CTEs are a feature introduced by MySQL8.0 to improve the readability and maintenance of complex queries. 1. CTE is a temporary result set, which is only valid in the current query, has a clear structure, and supports duplicate references; 2. Compared with subqueries, CTE is more readable, reusable and supports recursion; 3. Recursive CTE can process hierarchical data, such as organizational structure, which needs to include initial query and recursion parts; 4. Use suggestions include avoiding abuse, naming specifications, paying attention to performance and debugging methods.