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This PR contains the following updates:
==1.1.0
->==1.4.2
Release Notes
joblib/joblib (joblib)
v1.4.2
Compare Source
Due to maintenance issues, 1.4.1 was not valid and we bumped the version to 1.4.2
MemorizedFunc.call
which needs toreturn the metadata. Also make sure that
NotMemorizedFunc.call
returnan empty dict for metadata for consistenhttps://github.com/joblib/joblib/pull/1576ull/1576
v1.4.0
Compare Source
Allow caching co-routines with
Memory.cache
.https://github.com/joblib/joblib/pull/894/894
Try to cast
n_jobs
to int in parallel and raise an error ifit fails. This means that
n_jobs=2.3
will now result ineffective_n_jobs=2
instead of failing.https://github.com/joblib/joblib/pull/15391539
Ensure that errors in the task generator given to Parallel's call
are raised in the results consumming threhttps://github.com/joblib/joblib/pull/1491ull/1491
Adjust codebase to NumPy 2.0 by changing
np.NaN
tonp.nan
and importing
byte_bounds
fromnp.lib.array_utils
.https://github.com/joblib/joblib/pull/15011501
The parameter
return_as
injoblib.Parallel
can now be set togenerator_unordered
. In this case the results will be returned in theorder of task completion rather than the order of submissihttps://github.com/joblib/joblib/pull/1463ull/1463
dask backend now supports
return_as=generator
andreturn_as=generator_unordered
.https://github.com/joblib/joblib/pull/15201520
Vendor cloudpickle 3.0.0 and end support for Python 3.7 which has
reached end of lihttps://github.com/joblib/joblib/pull/1487uhttps://github.com/joblib/joblib/pull/1515ib/pull/1515
v1.3.2
Compare Source
Fix a regression in
joblib.Parallel
introduced in 1.3.0 whereexplicitly setting
n_jobs=None
was not interpreted as "unset".https://github.com/joblib/joblib/pull/14751475
Fix a regression in
joblib.Parallel
introduced in 1.3.0 wherejoblib.Parallel
logging methods exposed from inheritance tojoblib.Logger
didn't work because of missing loggerinitializatihttps://github.com/joblib/joblib/pull/1494ull/1494
Various maintenance updates to the doc, the ci and the test.
https://github.com/joblib/joblib/pull/148014https://github.com/joblib/joblib/pull/1481ulhttps://github.com/joblib/joblib/pull/1476ibhttps://github.com/joblib/joblib/pull/1492joblib/pull/1492
v1.3.1
Compare Source
which is compatible with this versihttps://github.com/joblib/joblib/pull/1472ull/1472
v1.3.0
Compare Source
Ensure native byte order for memmap arrays in
joblib.load
.https://github.com/joblib/joblib/issues/13531353
Add ability to change default Parallel backend in tests by setting the
JOBLIB_TESTS_DEFAULT_PARALLEL_BACKEND
environment variable.https://github.com/joblib/joblib/pull/13561356
Fix temporary folder creation in
joblib.Parallel
on Linux subsystems on Windowswhich do have
/dev/shm
but don't have theos.statvfs
functionhttps://github.com/joblib/joblib/issues/13531353
Drop runtime dependency on
distutils
.distutils
is going awayin 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 (version 1.1 was released
in May 2022) that it should be safe https://github.com/joblib/joblib/pull/1361lib/joblib/pull/1361
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
.https://github.com/joblib/joblib/pull/13591359
Avoid (module, name) collisions when caching nested functions. This fix
changes the module name of nested functions, invalidating caches from
previous versions of https://github.com/joblib/joblib/pull/1374ib/pull/1374
Add
cache_validation_callback
in :meth:joblib.Memory.cache
, to allowcustom cache invalidation based on the metadata of the function cahttps://github.com/joblib/joblib/pull/1149ull/1149
Add a
return_as
parameter forParallel
, that enables consumingresults asynchronoushttps://github.com/joblib/joblib/pull/1393ulhttps://github.com/joblib/joblib/pull/1458ib/pull/1458
Improve the behavior of
joblib
forn_jobs=1
, with simplifiedtracebacks and more efficient running tihttps://github.com/joblib/joblib/pull/1393ull/1393
Add the
parallel_config
context manager to allow for more fine-grainedcontrol over the backend configuration. It should be used in place of the
parallel_backend
context manager. In particular, it has the advantageof not requiring to set a specific backend in the context managhttps://github.com/joblib/joblib/pull/1392ulhttps://github.com/joblib/joblib/pull/1457ib/pull/1457
Add
items_limit
andage_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 thehttps://github.com/joblib/joblib/pull/1200ib/pull/1200
Deprecate
bytes_limit
inMemory
as this is not automatically enforced,the limit can be directly passed to :meth:
joblib.Memory.reduce_size
whichneeds to be called to actually enforce the limhttps://github.com/joblib/joblib/pull/1447ull/1447
Vendor
loky
3.4.0 which includes various fixes.https://github.com/joblib/joblib/pull/14221422
Various updates to the documentation and to benchmarking tools.
https://github.com/joblib/joblib/pull/134313https://github.com/joblib/joblib/pull/1348ulhttps://github.com/joblib/joblib/pull/1411ibhttps://github.com/joblib/joblib/pull/1451johttps://github.com/joblib/joblib/pull/1427lihttps://github.com/joblib/joblib/pull/1400/BENCH add benchmark script for n_jobs=1 joblib/joblib#1400
Move project metadata to
pyproject.toml
.https://github.com/joblib/joblib/pull/138213https://github.com/joblib/joblib/pull/1433ull/1433
Add more tests to improve python
nogil
support.https://github.com/joblib/joblib/pull/139413https://github.com/joblib/joblib/pull/1395ull/1395
v1.2.0
Compare Source
Fix a security issue where
eval(pre_dispatch)
could potentially runarbitrary code. Now only basic numerics are supporthttps://github.com/joblib/joblib/pull/1327ull/1327
Make sure that joblib works even when multiprocessing is not available,
for instance with Pyodhttps://github.com/joblib/joblib/pull/1256ull/1256
Avoid unnecessary warnings when workers and main process delete
the temporary memmap folder contents concurrenthttps://github.com/joblib/joblib/pull/1263ull/1263
Fix memory alignment bug for pickles containing numpy arrays.
This is especially important when loading the pickle with
mmap_mode != None
as the resultingnumpy.memmap
objectwould 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 plathttps://github.com/joblib/joblib/pull/1254thub.com/Make sure arrays are bytes aligned in joblib pickles joblib/joblib#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/1269ull/1269);
avoiding leaking worker processes in case of nested loky parallel
calls;
reliability spawn the correct number of reusable workers.
v1.1.1
Compare Source
eval(pre_dispatch)
could potentially runarbitrary code. Now only basic numerics are supporthttps://github.com/joblib/joblib/pull/1327ull/1327
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