Getting started with the Python GIL: How to understand and use the global interpreter lock

What is GIL?

GIL is the abbreviation of global interpreter lock, which is an important concept of python interpreter. The GIL ensures that the Python interpreter can only execute one thread at a time. This means that at any time, only one thread can run Python bytecode. Other threads must wait for the GIL to be available before continuing execution.

How does GIL work?

GIL is a lock written in C language and is located in the Python interpreter. When a thread wants to execute Python bytecode, it must first obtain the GIL. If the GIL is already held by another thread, that thread must wait for the GIL to be available before continuing execution.

What impact does GIL have on Python programs?

The impact of GIL on Python programs is manifold. First, it prevents Python programs from taking full advantage of multi-core CPUs in a multi-threaded environment. This is because the GIL ensures that only one thread can execute Python bytecode at the same time, which means that other threads must wait for the GIL to be available before continuing execution.

Secondly, GIL makes Python programs prone to deadlocks under certain circumstances. For example, if one thread is holding the GIL and waiting for another thread to release a lock, and another thread is holding the lock and waiting for the GIL to be available, then the two threads will be stuck in a deadlock.

How to understand and use GIL?

In order to understand and use GIL, you first need to understand how GIL works. As mentioned above, the GIL is a lock written in C and located in the Python interpreter. When a thread wants to execute Python bytecode, it must first obtain the GIL. If the GIL is already held by another thread, that thread must wait for the GIL to be available before continuing execution.

Secondly, you need to understand the impact of GIL on Python programs. The impact of GIL on Python programs is manifold. First, it prevents Python programs from taking full advantage of multi-core CPUs in a multi-threaded environment. This is because the GIL ensures that only one thread can execute Python bytecode at the same time, which means that other threads must wait for the GIL to be available before continuing execution.

Secondly, GIL makes Python programs prone to deadlocks under certain circumstances. For example, if one thread is holding the GIL and waiting for another thread to release a lock, and another thread is holding the lock and waiting for the GIL to be available, then the two threads will be stuck in a deadlock.

In order to avoid the negative impact of GIL on Python programs, you can take the following measures:

• Try to avoid using multi-threading in Python programs.
• If you must use multi-threading, you should pay attention to avoid deadlock.
• You can use the GILStateSave() and GILStateRestore() functions to temporarily release GIL.

Demo code:

import threading

def task():
print("This is a task.")

def main():
threads = []
for i in range(10):
thread = threading.Thread(target=task)
threads.append(thread)

for thread in threads:
thread.start()

for thread in threads:
thread.join()

if __name__ == "__main__":
main()

This code creates 10 threads, each thread will execute the task function. The task function prints a message. The main function first creates 10 threads and then starts them. Finally, the main function waits for all threads to finish executing.

When running this code, GIL will ensure that only one thread executes the task function at the same time. This means that other threads must wait for the GIL to be available before they can continue execution.

GILStateSave() and GILStateRestore() functions

The GILStateSave() and GILStateRestore() functions can be used to temporarily release GIL. This is useful for certain operations that take a long time to perform, such as I/O operations. The GILStateSave() function can save the current GIL state, and the GILStateRestore() function can restore the saved GIL state.

The following example demonstrates how to use the GILStateSave() and GILStateRestore() functions:

import threading

def task():
print("This is a task.")

def main():
threads = []
for i in range(10):
thread = threading.Thread(target=task)
threads.append(thread)

for thread in threads:
thread.start()

with GILStateSave():
# PerfORM an operation that does not require the GIL.

for thread in threads:
thread.join()

if __name__ == "__main__":
main()

This code is similar to the previous code, but it uses the GILStateSave() and GILStateRestore() functions to temporarily release the GIL. This allows operations that do not require the GIL to be performed while other threads are executing.

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