Hi folks, as illustrated in faster-cpython#150 [1], we have implemented a mechanism that supports data persistence of a subset of python date types with mmap, therefore can reduce package import time by caching code object. This could be seen as a more eager pyc format, as they are for the same purpose, but our approach try to avoid [de]serialization. Therefore, we get a speedup in overall python startup by ~15%.

Currently, we’ve made it a third-party library and have been working on open-sourcing.

Our implementation (whose non-official name is “pycds”) mainly contains two parts:

• importlib hooks, this implements the mechanism to dump code objects to an archive and a `Finder` that supports loading code object from mapped memory.
• Dumping and loading (subset of) python types with mmap. In this part, we deal with 1) ASLR by patching `ob_type` fields; 2) hash seed randomization by supporting only basic types who don’t have hash-based layout (i.e. dict is not supported); 3) interned string by re-interning strings while loading mmap archive and so on.