joblib.Memory

class joblib.Memory(cachedir, mmap_mode=None, compress=False, verbose=1, bytes_limit=None)

A context object for caching a function’s return value each time it is called with the same input arguments.

All values are cached on the filesystem, in a deep directory structure.

see Reference documentation of the Memory class

__init__(cachedir, mmap_mode=None, compress=False, verbose=1, bytes_limit=None)
Parameters:

cachedir: string or None

The path of the base directory to use as a data store or None. If None is given, no caching is done and the Memory object is completely transparent.

mmap_mode: {None, ‘r+’, ‘r’, ‘w+’, ‘c’}, optional

The memmapping mode used when loading from cache numpy arrays. See numpy.load for the meaning of the arguments.

compress: boolean, or integer

Whether to zip the stored data on disk. If an integer is given, it should be between 1 and 9, and sets the amount of compression. Note that compressed arrays cannot be read by memmapping.

verbose: int, optional

Verbosity flag, controls the debug messages that are issued as functions are evaluated.

bytes_limit: int, optional

Limit in bytes of the size of the cache

Methods

__init__(cachedir[, mmap_mode, compress, ...])
Parameters:
cache([func, ignore, verbose, mmap_mode]) Decorates the given function func to only compute its return value for input arguments not cached on disk.
clear([warn]) Erase the complete cache directory.
debug(msg)
eval(func, \*args, \*\*kwargs) Eval function func with arguments *args and **kwargs, in the context of the memory.
format(obj[, indent]) Return the formated representation of the object.
reduce_size() Remove cache folders to make cache size fit in bytes_limit.
warn(msg)