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 good for …

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 administrator, and …

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 computing:

To fit with Joblib internal implementation and features, such as joblib.load() and joblib.Memory, the registered compressor should implement the Python file object interface.

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, compressed files take …

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 distributions, the …

Examples ¶ General examples ¶ General-purpose and introductory examples for joblib.

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 leaks in parallel worker …

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.

Joblib’s philosophy is to keep the underlying algorithm code unchanged, avoiding framework-style modifications. Joblib’s approach ¶ Functions are the simplest abstraction used by everyone. Pipeline …