The way to access nested JSON objects in Python is to first clarify the structure and then index layer by layer. First, confirm the hierarchical relationship of JSON, such as a dictionary nested dictionary or list; then use dictionary keys and list index to access layer by layer, such as data "details"["zip"] to obtain zip encoding, data "details"[0] to obtain the first hobby; to avoid KeyError and IndexError, the default value can be set by the .get() method, or the encapsulation function safe_get can be used to achieve secure access; for complex structures, recursively search or use third-party libraries such as jmespath to handle.

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.

Asynchronous programming is made easier in Python with async and await keywords. It allows writing non-blocking code to handle multiple tasks concurrently, especially for I/O-intensive operations. asyncdef defines a coroutine that can be paused and restored, while await is used to wait for the task to complete without blocking the entire program. Running asynchronous code requires an event loop. It is recommended to start with asyncio.run(). Asyncio.gather() is available when executing multiple coroutines concurrently. Common patterns include obtaining multiple URL data at the same time, reading and writing files, and processing of network services. Notes include: Use libraries that support asynchronously, such as aiohttp; CPU-intensive tasks are not suitable for asynchronous; avoid mixed

In C, the POD (PlainOldData) type refers to a type with a simple structure and compatible with C language data processing. It needs to meet two conditions: it has ordinary copy semantics, which can be copied by memcpy; it has a standard layout and the memory structure is predictable. Specific requirements include: all non-static members are public, no user-defined constructors or destructors, no virtual functions or base classes, and all non-static members themselves are PODs. For example structPoint{intx;inty;} is POD. Its uses include binary I/O, C interoperability, performance optimization, etc. You can check whether the type is POD through std::is_pod, but it is recommended to use std::is_trivia after C 11.

In C, there are three main ways to pass functions as parameters: using function pointers, std::function and Lambda expressions, and template generics. 1. Function pointers are the most basic method, suitable for simple scenarios or C interface compatible, but poor readability; 2. Std::function combined with Lambda expressions is a recommended method in modern C, supporting a variety of callable objects and being type-safe; 3. Template generic methods are the most flexible, suitable for library code or general logic, but may increase the compilation time and code volume. Lambdas that capture the context must be passed through std::function or template and cannot be converted directly into function pointers.

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.

In C, the mutable keyword is used to allow the object to be modified, even if the object is declared as const. Its core purpose is to maintain the logical constants of the object while allowing internal state changes, which are commonly found in cache, debug counters and thread synchronization primitives. When using it, mutable must be placed before the data member in the class definition, and it only applies to data members rather than global or local variables. In best practice, abuse should be avoided, concurrent synchronization should be paid attention to, and external behavior should be ensured. For example, std::shared_ptr uses mutable to manage reference counting to achieve thread safety and const correctness.