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  • Installing joblib — joblib 1. 6. dev0 documentation - Read the Docs
    To install joblib first download the latest tarball (follow the link on the bottom of https: pypi org project joblib ) and expand it Installing in a local environment ¶ If you don’t need to install for all users, we strongly suggest that you create a local environment and install joblib in it
  • 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 computing: >>>
  • Persistence — joblib 1. 6. dev0 documentation - Read the Docs
    joblib dump() and joblib load() provide a replacement for pickle to work efficiently on arbitrary Python objects containing large data, in particular large numpy arrays Warning 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
  • joblib. load — joblib 1. 6. dev0 documentation - Read the Docs
    joblib load (filename, mmap_mode = None, ensure_native_byte_order = 'auto') ¶ Reconstruct a Python object from a file persisted with joblib dump Read more in the User Guide
  • joblib. dump — joblib 1. 6. dev0 documentation - Read the Docs
    joblib dump¶ joblib dump (value, filename, compress = 0, protocol = None) ¶ Persist an arbitrary Python object into one file Read more in the User Guide Parameters: value: any Python object The object to store to disk filename: str, pathlib Path, or file object The file object or path of the file in which it is to be stored
  • Examples — joblib 1. 6. dev0 documentation - Read the Docs
    Using Dask for single-machine parallel computing Using Dask for single-machine parallel computing Download all examples in Python source code: auto_examples_python zip
  • Development — joblib 1. 5. 1 documentation - Read the Docs
    Joblib can efficiently dump and load numpy arrays but does not require numpy to be installed 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 processes


















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