Because of the global interpreter lock in CPython, it is sometimes beneficial to use separate processes to handle different tasks. This can pose a challenge for sharing data: it's generally best to avoid sharing memory between processes for reasons of safety1. One common approach is to use pipes, queues, or sockets to communicate data from one process to another. This approach works quite well, but it can be a bit cumbersome to get right when there are more than two processes involved and you just need to share a small amount of infrequently changing data (say some configuration settings that are loaded after worker processes have already been spawned). In such cases, using a file that each process can read is a simple solution, but may have problems if reading and writing happen simultaneously. Thankfully, SQLite can handle this situation easily!

I have created a small module (Permadict) which utilizes SQLite to persist arbitrary (picklable) Python objects to a SQLite database using a dict-like interface. This is not a new idea, but it was fun and simple to utilize only the Python standard library to accomplish this. A basic usage example:

>>> from permadict import Permadict
>>> d = Permadict("db.sqlite")
>>> d["key"] = "value"
>>> print(d["key"])
value

Because context managers are great, you can also use permadicts that way:

>>> with Permadict("db.sqlite") as d:
...     d["something"] = 1.2345
...
>>> with Permadict("db.sqlite") as d:
...     print(d["something"])
...
1.2345

  1. Of course, Python allows you to share memory among processes by using a manager, but this is not always possible depending on the specific use case.