On Thu, Dec 29, 2011 at 10:34:16AM -0800, Josh Bleecher Snyder wrote:
> If you want to experiment with more options, you might also play with
> blosc (http://blosc.pytables.org/trac). The compression level is not
> as good as heavier weight algorithms, but it is really zippy. I ended
> up using it
> Obviously the fine-tuning that I did is not needed for the
> scikit's storage of the datasets, but it general fast dump/load of Python
> objects is useful for scientific computing and big data (think caching or
> message passing parallel computing).
If you want to experiment with more options, y
On Wed, Dec 28, 2011 at 05:21:39PM +0100, Alexandre Gramfort wrote:
> thanks Gael for the christmas present :)
I just couldn't help playing more. I have pushed a new update that
enables to control the compression level, and in general can achieve
better compromises between speed and compression. H
thanks Gael for the christmas present :)
Alex
On Wed, Dec 28, 2011 at 11:45 AM, Olivier Grisel
wrote:
> Great job Gael!
>
> --
> Olivier
>
> --
> Write once. Port to many.
> Get the SDK and tools to simplify cross-platfo
Great job Gael!
--
Olivier
--
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Hi list,
This message is not terribly informative. I just to share my current
successes with joblib compression.
I am a bit frustrated at the fact that the LFW cache takes 400M on my
disk, for something that I never used. The disk space in the LFW cache is
made of two major contributors:
* The
