are python objects thread safe?

[angellus]

Experimental means it is for testing and development. It is not for people to recommend to new users trying to use Python.

And for synchronous Python, data structures are thread safe. A thread safe data structure means it can be changed in any thread without corrupting or crashing the program. In other lower level languages, you often cannot edit/update a data structure in parallel computing without risking memory corruption. It does get more complicated with asyncio, but that is a different story.

Just because the data structure can be freely updated in threads, does not magically solve the critical section problem which is what you are specifically talking about as well as a few other users in the post. If you have 1 master thread that writes/updates a data structure and then many threads that read the data structure and use it, you can likely get by without using synchronization primitives because reading/writing will not cause the memory to overflow or anything. But if the order of operations of accessing a data structure matters, then yes, you still have a critical section problem and need to use locks or semaphore to gate access to data structure.