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  • License: Freeware
  • Last update: 5 years ago
  • Total downloads: 93
  • Price: Free |
  • Operating system: Linux
  • Publisher: Gael Varoquaux
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linux default iconJoblib Publisher's description

Joblib is a set of tools to provide lightweight pipelining in Python.

Joblib is a set of tools to provide lightweight pipelining in Python. In particular, joblib offers:

1. transparent disk-caching of the output values and lazy re-evaluation (memoize pattern)
2. easy simple parallel computing
3. logging and tracing of the execution

Joblib is optimized to be fast and robust in particular on large data and has specific optimizations for numpy arrays.

Main features :

1. Transparent and fast disk-caching of output value: a memoize or make-like functionality for Python functions that works well for arbitrary Python objects, including very large numpy arrays. Separate persistence and flow-execution logic from domain logic or algorithmic code by writing the operations as a set of steps with well-defined inputs and outputs: Python functions. Joblib can save their computation to disk and rerun it only if necessary:

>>> from joblib import Memory
>>> mem = Memory(cachedir='/tmp/joblib')
>>> import numpy as np
>>> a = np.vander(np.arange(3))
>>> square = mem.cache(np.square)
>>> b = square(a)
[Memory] Calling square...
square(array([[0, 0, 1],
[1, 1, 1],
[4, 2, 1]]))
___________________________________________________________square - 0.0s, 0.0min

>>> c = square(a)
>>> # The above call did not trigger an evaluation

2. Embarrassingly parallel helper: to make is easy to write readable parallel code and debug it quickly:

>>> from joblib import Parallel, delayed
>>> from math import sqrt
>>> Parallel(n_jobs=1)(delayed(sqrt)(i**2) for i in range(10))
[0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]

3. Logging/tracing: The different functionalities will progressively acquire better logging mechanism to help track what has been ran, and capture I/O easily. In addition, Joblib will provide a few I/O primitives, to easily define define logging and display streams, and provide a way of compiling a report. We want to be able to quickly inspect what has been run.

System Requirements:

В· Python
Program Release Status: Minor Update
Program Install Support: Install and Uninstall

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