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devel/py-joblib,
Set of tools to provide lightweight pipelining
Branch: CURRENT,
Version: 1.4.2,
Package name: py311-joblib-1.4.2,
Maintainer: jihbed.researchJoblib is a set of tools to provide lightweight pipelining in Python.
In particular, joblib offers transparent disk-caching of the output
values and lazy re-evaluation (memoize pattern), easy simple parallel
computing, and 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.
Required to run:[
devel/py-setuptools] [
lang/python37]
Required to build:[
pkgtools/cwrappers]
Master sites:
Filesize: 2067.013 KB
Version history: (Expand)
- (2024-05-11) Updated to version: py311-joblib-1.4.2
- (2024-04-13) Updated to version: py311-joblib-1.4.0
- (2024-01-10) Updated to version: py311-joblib-1.3.2nb1
- (2023-11-03) Updated to version: py311-joblib-1.3.2
- (2022-11-21) Updated to version: py310-joblib-1.2.0
- (2022-01-05) Updated to version: py39-joblib-1.1.0nb1
CVS history: (Expand)
2024-04-13 07:27:48 by Adam Ciarcinski | Files touched by this commit (3) | |
Log message:
py-joblib: updated to 1.4.0
Release 1.4.0 -- 2024/04/08
- Allow caching co-routines with `Memory.cache`.
- Try to cast ``n_jobs`` to int in parallel and raise an error if
it fails. This means that ``n_jobs=2.3`` will now result in
``effective_n_jobs=2`` instead of failing.
- Ensure that errors in the task generator given to Parallel's call
are raised in the results consumming thread.
- Adjust codebase to NumPy 2.0 by changing ``np.NaN`` to ``np.nan``
and importing ``byte_bounds`` from ``np.lib.array_utils``.
- The parameter ``return_as`` in ``joblib.Parallel`` can now be set to
``generator_unordered``. In this case the results will be returned in the
order of task completion rather than the order of submission.
- dask backend now supports ``return_as=generator`` and
``return_as=generator_unordered``.
- Vendor cloudpickle 3.0.0 and end support for Python 3.7 which has
reached end of life.
|
2024-01-10 15:38:25 by Jason Bacon | Files touched by this commit (3) |
Log message:
devel/py-joblib: Unbreak hardware core count
Patch in platform-specific cases for NetBSD and FreeBSD
Without this, the core count routine errors out
No other changes
Maintainer feedback timeout (12 days)
Issue was discussed on tech-pkg and upstream
https://github.com/joblib/joblib/issues/1535
|
2023-11-03 11:35:53 by Adam Ciarcinski | Files touched by this commit (3) | |
Log message:
py-joblib: updated to 1.3.2
Release 1.3.2 -- 2023/08/08
Fix a regression in joblib.Parallel introduced in 1.3.0 where explicitly setting \
n_jobs=None was not interpreted as "unset".
Fix a regression in joblib.Parallel introduced in 1.3.0 where joblib.Parallel \
logging methods exposed from inheritance to joblib.Logger didn't work because of \
missing logger initialization.
Various maintenance updates to the doc, the ci and the test.
Release 1.3.1 -- 2023/06/29
Fix compatibility with python 3.7 by vendor loky 3.4.1 which is compatible with \
this version.
Release 1.3.0 -- 2023/06/28
Ensure native byte order for memmap arrays in joblib.load.
Add ability to change default Parallel backend in tests by setting the \
JOBLIB_TESTS_DEFAULT_PARALLEL_BACKEND environment variable.
Fix temporary folder creation in joblib.Parallel on Linux subsystems on Windows \
which do have /dev/shm but don't have the os.statvfs function
Drop runtime dependency on distutils. distutils is going away in Python 3.12 and \
is deprecated from Python 3.10 onwards. This import was kept around to avoid \
breaking scikit-learn, however it's now been long enough since scikit-learn \
deployed a fixed (verion 1.1 was released in May 2022) that it should be safe to \
remove this.
A warning is raised when a pickling error occurs during caching operations. In \
version 1.5, this warning will be turned into an error. For all other errors, a \
new warning has been introduced: joblib.memory.CacheWarning.
Avoid (module, name) collisions when caching nested functions. This fix changes \
the module name of nested functions, invalidating caches from previous versions \
of Joblib.
Add cache_validation_callback in :meth:`joblib.Memory.cache`, to allow custom \
cache invalidation based on the metadata of the function call.
Add a return_as parameter for Parallel, that enables consuming results \
asynchronously.
Improve the behavior of joblib for n_jobs=1, with simplified tracebacks and more \
efficient running time.
Add the parallel_config context manager to allow for more fine-grained control \
over the backend configuration. It should be used in place of the \
parallel_backend context manager. In particular, it has the advantage of not \
requiring to set a specific backend in the context manager.
Add items_limit and age_limit in :meth:`joblib.Memory.reduce_size` to make it \
easy to limit the number of items and remove items that have not been accessed \
for a long time in the cache.
Deprecate bytes_limit in Memory as this is not automatically enforced, the limit \
can be directly passed to :meth:`joblib.Memory.reduce_size` which needs to be \
called to actually enforce the limit.
Vendor loky 3.4.0 which includes various fixes.
Various updates to the documentation and to benchmarking tools.
Move project metadata to pyproject.toml.
Add more tests to improve python nogil support.
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2022-11-21 10:35:31 by Adam Ciarcinski | Files touched by this commit (3) | |
Log message:
py-joblib: updated to 1.2.0
Release 1.2.0
Fix a security issue where eval(pre_dispatch) could potentially run arbitrary \
code. Now only basic numerics are supported. \
https://github.com/joblib/joblib/pull/1327
Make sure that joblib works even when multiprocessing is not available, for \
instance with Pyodide https://github.com/joblib/joblib/pull/1256
Avoid unnecessary warnings when workers and main process delete the temporary \
memmap folder contents concurrently. https://github.com/joblib/joblib/pull/1263
Fix memory alignment bug for pickles containing numpy arrays. This is especially \
important when loading the pickle with mmap_mode != None as the resulting \
numpy.memmap object would not be able to correct the misalignment without \
performing a memory copy. This bug would cause invalid computation and \
segmentation faults with native code that would directly access the underlying \
data buffer of a numpy array, for instance C/C++/Cython code compiled with older \
GCC versions or some old OpenBLAS written in platform specific assembly. \
https://github.com/joblib/joblib/pull/1254
Vendor cloudpickle 2.2.0 which adds support for PyPy 3.8+.
Vendor loky 3.3.0 which fixes several bugs including:
robustly forcibly terminating worker processes in case of a crash \
(https://github.com/joblib/joblib/pull/1269);
avoiding leaking worker processes in case of nested loky parallel calls;
reliability spawn the correct number of reusable workers.
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2022-01-04 21:55:40 by Thomas Klausner | Files touched by this commit (1595) |
Log message:
*: bump PKGREVISION for egg.mk users
They now have a tool dependency on py-setuptools instead of a DEPENDS
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2021-10-26 12:20:11 by Nia Alarie | Files touched by this commit (3016) |
Log message:
archivers: Replace RMD160 checksums with BLAKE2s checksums
All checksums have been double-checked against existing RMD160 and
SHA512 hashes
Could not be committed due to merge conflict:
devel/py-traitlets/distinfo
The following distfiles were unfetchable (note: some may be only fetched
conditionally):
./devel/pvs/distinfo pvs-3.2-solaris.tgz
./devel/eclipse/distinfo eclipse-sourceBuild-srcIncluded-3.0.1.zip
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2021-10-07 21:38:32 by Adam Ciarcinski | Files touched by this commit (3) | |
Log message:
py-joblib: updated to 1.1.0
Release 1.1.0
Fix byte order inconsistency issue during deserialization using joblib.load in \
cross-endian environment: the numpy arrays are now always loaded to use the \
system byte order, independently of the byte order of the system that serialized \
the pickle. https://github.com/joblib/joblib/pull/1181
Fix joblib.Memory bug with the ignore parameter when the cached function is a \
decorated function. https://github.com/joblib/joblib/pull/1165
Fix joblib.Memory to properly handle caching for functions defined interactively \
in a IPython session or in Jupyter notebook cell. \
https://github.com/joblib/joblib/pull/1214
Update vendored loky (from version 2.9 to 3.0) and cloudpickle (from version 1.6 \
to 2.0) https://github.com/joblib/joblib/pull/1218
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2021-10-07 15:44:44 by Nia Alarie | Files touched by this commit (3017) |
Log message:
devel: Remove SHA1 hashes for distfiles
|