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This article mainly shows you the meaning of "multi-process, multi-thread and cooperative process in Python development", which is easy to understand and well-organized. I hope it can help you solve your doubts. Let me lead you to study and learn "what is the meaning of multi-process, multi-threading and collaborative process in Python development".

In fact, multi-thread, multi-process, rarely used in actual development, process: a running program (code) is a process, no running code is called a program; thread: the smallest unit of scheduling execution, also known as the execution path; co-program: is a user-mode lightweight thread, the scheduling of the co-program is completely controlled by the user

The probability of this question being asked is quite high. In fact, multithreading and multiprocess are rarely used in actual development, unless they are those who have high requirements for project performance, and some developers have been working for several years and have not used them. You can answer this question by telling him what is a process and the concept of threads (pseudo-multithreading in cpython). It is really impossible to say that when you wrote the download file before. Use too many threads technology, or use too many threads to write crawlers in your spare time to improve efficiency.

Process: a running program (code) is a process, no running code is called a program, the process is the smallest unit of system resource allocation, and the process has its own independent memory space, so the data between processes are not shared and the overhead is high.

Thread: the smallest unit of scheduling execution, also known as the execution path, cannot exist independently, depending on the process there is at least one thread, called the main thread, and multiple threads share memory (data sharing, sharing global variables). As a result, the running efficiency of the program is greatly improved.

Cooperative program: it is a kind of lightweight thread in user mode, and the scheduling of cooperative program is completely controlled by the user.

The co-program has its own register context and stack. During the cooperative program scheduling switch, the register context and stack are saved somewhere else, and the previously saved register context and stack are restored when the switch back, while the direct operation stack basically has no kernel switching overhead, and the global variables can be accessed without locking, so the context switch is very fast.

These are all the contents of the article "what is the meaning of multiprocess, multithreading and collaboration in Python development". Thank you for reading! I believe we all have a certain understanding, hope to share the content to help you, if you want to learn more knowledge, welcome to follow the industry information channel!

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