Joblib: running Python functions as pipeline jobs — joblib 1.5.2 ...
Using joblib’s caching mechanism avoids hand-written persistence and implicitly links the file on disk to the execution context of the original Python object. As a result, joblib’s persistence is …
Embarrassingly parallel for loops — joblib 1.6.dev0 documentation
Joblib provides a simple helper class to write parallel for loops using multiprocessing. The core idea is to write the code to be executed as a generator expression, and convert it to parallel …
Installing joblib — joblib 1.6.dev0 documentation
If you don’t need to install for all users, we strongly suggest that you create a local environment and install joblib in it. One of the pros of this method is that you never have to become …
joblib.dump — joblib 1.6.dev0 documentation
See also joblib.load corresponding loader Notes Memmapping on load cannot be used for compressed files. Thus using compression can significantly slow down loading. In addition, …
joblib.Parallel — joblib 1.6.dev0 documentation - Read the Docs
a folder pointed by the JOBLIB_TEMP_FOLDER environment variable, /dev/shm if the folder exists and is writable: this is a RAM disk filesystem available by default on modern Linux …
Examples — joblib 1.6.dev0 documentation
Examples ¶ General examples ¶ General-purpose and introductory examples for joblib.
Persistence — joblib 1.6.dev0 documentation
joblib.dump() and joblib.load() are based on the Python pickle serialization model, which means that arbitrary Python code can be executed when loading a serialized object with joblib.load().
Development — joblib 1.5.2 documentation
Joblib has an optional dependency on python-lz4 as a faster alternative to zlib and gzip for compressed serialization. Joblib has an optional dependency on psutil to mitigate memory …
joblib.load — joblib 1.6.dev0 documentation
WARNING: joblib.load relies on the pickle module and can therefore execute arbitrary Python code. It should therefore never be used to load files from untrusted sources.
How to use joblib.Memory — joblib 1.6.dev0 documentation
joblib.Memory is designed to work with functions with no side effects. When dealing with class, the computationally expensive part of a method has to be moved to a function and decorated in …