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python-joblib
python-joblib.changes
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File python-joblib.changes of Package python-joblib
------------------------------------------------------------------- Thu May 9 08:36:55 UTC 2024 - Dirk Müller <dmueller@suse.com> - update to 1.4.2: * Due to maintenance issues, 1.4.1 was not valid and we bumped the version to 1.4.2 * Fix a backward incompatible change in MemorizedFunc.call which needs to return the metadata. Also make sure that NotMemorizedFunc.call return an empty dict for metadata for consistency. https://github.com/joblib/joblib/pull/1576 ------------------------------------------------------------------- Sat Apr 20 21:06:55 UTC 2024 - Dirk Müller <dmueller@suse.com> - update to 1.4.0: * 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. - drop avoid-deprecated-ast.patch (upstream) ------------------------------------------------------------------- Tue Nov 28 03:55:52 UTC 2023 - Steve Kowalik <steven.kowalik@suse.com> - Add patch avoid-deprecated-ast.patch: * Avoid deprecated ast classes. - Add patch also-filter-new-fork-warning.patch: * Filter DeprecationWarning due to calling fork() with multiprocessing. - Switch to pyproject macros. ------------------------------------------------------------------- Sat Nov 25 20:14:35 UTC 2023 - Dirk Müller <dmueller@suse.com> - update to 1.3.2: * FIX treat n_jobs=None as if left to its default value * FIX Init logger parent class in Parallel * MNT remove unnecessary .bck file * MTN adjust test regex for Python 3.12 improved error message * DOC add public documentation for parallel_backend * FIX flake8 new E721: type comparison * Ensure native byte order for memmap. * Drop runtime dependency on `distutils` * Add environment variable to change default parallel backend * Fix memmapping_reducer when 'os' has no attribute 'statvfs' * Move the metadata into `pyproject.toml` * TST Close client in test_pickle_in_socket * Do not swallow PicklingError * FIX Avoid collisions when caching nested functions * FIX heisenfailure in doc/memory.rst * MAINT Explicit support for Python 3.11 * MNT Use faulthandler rather than custom autokill logic * BENCH add benchmark script for n_jobs=1 * TST Fix test_nested_parallel_warnings_parent_backend for Python nogil * TST Fix test_memmapping for Python nogil * MAINT Clean deprecations * ENH make temp resource cleanup safer * MAINT Simplify warning in `_persist_input` * MNT Use full flake8 rather than flake8_diff.sh * Update Dask backend * FIX upload to codecov * MTN vendor loky 3.4.0 * MTN skip thread_bomb mitigation test on PyPy for now * High verbosity mode that prints arguments, hash and store location. * DBG try to debug the thread_bomb_mitigation test * FEA return generator, #588 stripped of unrelated changes for minimal diff review * BENCH scaling of a GridSearch with n_jobs * CLN make generator exit thread safe * FEA parallel_config context manager to allow more fine- grained control * MAINT: Be nitpicky about docs * CLN tidy logger * Give Memory.reduce_size() `items_limit` and `age_limit` options * CLN deprecate bytes_limit from Memory * FIX doc building failing download * Document parallel_config * ENH add cache_validation_callback in Memory * DOC example data DL from GH * merge all configs in pyproject.toml * fix double repeated word typos * DOC reference parallel_config instead of parallel_backend * `return_generator={True,False}` -> `return_as={'list','generator'}` ------------------------------------------------------------------- Sat Jun 10 17:42:25 UTC 2023 - ecsos <ecsos@opensuse.org> - Add %{?sle15_python_module_pythons} ------------------------------------------------------------------- Tue Oct 11 13:20:33 UTC 2022 - Ben Greiner <code@bnavigator.de> - Update to 1.2.0 (CVE-2022-21797, bsc#1204232) * Fix a security issue where eval(pre_dispatch) could potentially run arbitrary code. Now only basic numerics are supported. #1327 * Make sure that joblib works even when multiprocessing is not available, for instance with Pyodide #1256 * Avoid unnecessary warnings when workers and main process delete the temporary memmap folder contents concurrently. #1263 * Vendor loky 3.1.0 with several fixes to more robustly forcibly terminate worker processes in case of a crash. #1269 * 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. #1254 * Vendor cloudpickle 2.2.0 which adds support for PyPy 3.8+. * Vendor loky 3.3.0 which fixes a bug with leaking processes in case of nested loky parallel calls and more reliability spawn the correct number of reusable workers. - Drop support-setuptools-62.patch ------------------------------------------------------------------- Wed Jul 20 11:00:18 UTC 2022 - Steve Kowalik <steven.kowalik@suse.com> - Add patch support-setuptools-62.patch: * Support setuptools >= 62 by handling more than one warning in a test case. ------------------------------------------------------------------- Sat Oct 16 21:31:20 UTC 2021 - Dirk Müller <dmueller@suse.com> - update to 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. * Fix joblib.Memory bug with the ignore parameter when the cached function is a decorated function. * Fix joblib.Memory to properly handle caching for functions defined interactively in a IPython session or in Jupyter notebook cell. * Update vendored loky (from version 2.9 to 3.0) and cloudpickle (from version 1.6 to 2.0) ------------------------------------------------------------------- Mon Feb 15 23:26:21 UTC 2021 - Ben Greiner <code@bnavigator.de> - Update to 1.0.1 * dask: avoid redundant scattering of large arguments to make a more efficient use of the network resources and avoid crashing dask with "OSError: [Errno 55] No buffer space available" or "ConnectionResetError: [Errno 104] connection reset by peer". - Changees in 1.0.0 * Make joblib.hash and joblib.Memory caching system compatible with numpy >= 1.20.0. Also make it explicit in the documentation that users should now expect to have their joblib. Memory cache invalidated when either joblib or a third party library involved in the cached values definition is upgraded. In particular, users updating joblib to a release that includes this fix will see their previous cache invalidated if they contained reference to numpy objects. * Remove deprecated check_pickle argument in delayed. - Changes in 0.17.0 * Fix a spurious invalidation of Memory.cache'd functions called with Parallel under Jupyter or IPython. * Bump vendored loky to 2.9.0 and cloudpickle to 1.6.0. In particular this fixes a problem to add compat for Python 3.9. - Don't require optional NumPy for python36 tests in TW, because NumPy 1.20 dropped support for Python 3.6 (NEP 29) - Drop joblib-disable-unrelialble-tests.patch, they are already used in pytest deselection parameter. * Do the same for disable_test_on_big_endian.patch. ------------------------------------------------------------------- Sun Dec 6 21:37:54 UTC 2020 - Benjamin Greiner <code@bnavigator.de> - BuildRequire threadpoolctl for all python3 flavors gh#openSUSE/python-rpm-macros#66 ------------------------------------------------------------------- Fri Oct 30 08:23:38 UTC 2020 - pgajdos@suse.com - disable test_hash_numpy_noncontiguous, test_hashes_are_different_between_c_and_fortran_contiguous_arrays, test_hashes_stay_the_same_with_numpy_objects, test_non_contiguous_array_pickling [bsc#1177209] ------------------------------------------------------------------- Tue Oct 27 12:01:23 UTC 2020 - pgajdos@suse.com - disable test_nested_loop_error_in_grandchild_resource_tracker_silent [bsc#1177209] ------------------------------------------------------------------- Mon Oct 5 14:18:31 UTC 2020 - pgajdos@suse.com - disable yet another tests [bsc#1177209] ------------------------------------------------------------------- Tue Sep 8 08:26:41 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org> - Disable tests failing often in OBS: * joblib-disable-unrelialble-tests.patch ------------------------------------------------------------------- Fri Aug 21 08:40:04 UTC 2020 - Michel Normand <normand@linux.vnet.ibm.com> - New disable_test_on_big_endian.patch as per upstream issue https://github.com/joblib/joblib/issues/279 ------------------------------------------------------------------- Sat Jul 18 09:12:26 UTC 2020 - Dirk Mueller <dmueller@suse.com> - update to 0.16.0 - Fix a problem in the constructors of of Parallel backends classes that inherit from the `AutoBatchingMixin` that prevented the dask backend to properly batch short tasks. https://github.com/joblib/joblib/pull/1062 - Fix a problem in the way the joblib dask backend batches calls that would badly interact with the dask callable pickling cache and lead to wrong results or errors. https://github.com/joblib/joblib/pull/1055 - Prevent a dask.distributed bug from surfacing in joblib's dask backend during nested Parallel calls (due to joblib's auto-scattering feature) https://github.com/joblib/joblib/pull/1061 - Workaround for a race condition after Parallel calls with the dask backend that would cause low level warnings from asyncio coroutines: https://github.com/joblib/joblib/pull/1078 ------------------------------------------------------------------- Tue Jun 2 16:24:43 UTC 2020 - Dirk Mueller <dmueller@suse.com> - update to 0.15.1: - Make joblib work on Python 3 installation that do not ship with the lzma package in their standard library. - Drop support for Python 2 and Python 3.5. All objects in ``joblib.my_exceptions`` and ``joblib.format_stack`` are now deprecated and will be removed in joblib 0.16. Note that no deprecation warning will be raised for these objects Python < 3.7. https://github.com/joblib/joblib/pull/1018 - Fix many bugs related to the temporary files and folder generated when automatically memory mapping large numpy arrays for efficient inter-process communication. In particular, this would cause `PermissionError` exceptions to be raised under Windows and large leaked files in `/dev/shm` under Linux in case of crash. https://github.com/joblib/joblib/pull/966 - Make the dask backend collect results as soon as they complete leading to a performance improvement: https://github.com/joblib/joblib/pull/1025 - Fix the number of jobs reported by ``effective_n_jobs`` when ``n_jobs=None`` called in a parallel backend context. https://github.com/joblib/joblib/pull/985 - Upgraded vendored cloupickle to 1.4.1 and loky to 2.8.0. This allows for Parallel calls of dynamically defined functions with type annotations in particular. ------------------------------------------------------------------- Thu Mar 5 13:33:14 UTC 2020 - pgajdos@suse.com - version update to 0.14.1 - Configure the loky workers' environment to mitigate oversubsription with nested multi-threaded code in the following case: - allow for a suitable number of threads for numba (``NUMBA_NUM_THREADS``); - enable Interprocess Communication for scheduler coordination when the nested code uses Threading Building Blocks (TBB) (``ENABLE_IPC=1``) https://github.com/joblib/joblib/pull/951 - Fix a regression where the loky backend was not reusing previously spawned workers. https://github.com/joblib/joblib/pull/968 - Revert https://github.com/joblib/joblib/pull/847 to avoid using `pkg_resources` that introduced a performance regression under Windows: https://github.com/joblib/joblib/issues/965 - Improved the load balancing between workers to avoid stranglers caused by an excessively large batch size when the task duration is varying significantly (because of the combined use of ``joblib.Parallel`` and ``joblib.Memory`` with a partially warmed cache for instance). https://github.com/joblib/joblib/pull/899 - Add official support for Python 3.8: fixed protocol number in `Hasher` and updated tests. - Fix a deadlock when using the dask backend (when scattering large numpy arrays). https://github.com/joblib/joblib/pull/914 - Warn users that they should never use `joblib.load` with files from untrusted sources. Fix security related API change introduced in numpy 1.6.3 that would prevent using joblib with recent numpy versions. https://github.com/joblib/joblib/pull/879 - Upgrade to cloudpickle 1.1.1 that add supports for the upcoming Python 3.8 release among other things. https://github.com/joblib/joblib/pull/878 - Fix semaphore availability checker to avoid spawning resource trackers on module import. https://github.com/joblib/joblib/pull/893 - Fix the oversubscription protection to only protect against nested `Parallel` calls. This allows `joblib` to be run in background threads. https://github.com/joblib/joblib/pull/934 - Fix `ValueError` (negative dimensions) when pickling large numpy arrays on Windows. https://github.com/joblib/joblib/pull/920 - Upgrade to loky 2.6.0 that add supports for the setting environment variables in child before loading any module. https://github.com/joblib/joblib/pull/940 - Fix the oversubscription protection for native libraries using threadpools (OpenBLAS, MKL, Blis and OpenMP runtimes). The maximal number of threads is can now be set in children using the ``inner_max_num_threads`` in ``parallel_backend``. It defaults to ``cpu_count() // n_jobs``. https://github.com/joblib/joblib/pull/940 - deleted patches - numpy16.patch (upstreamed) ------------------------------------------------------------------- Tue May 28 10:34:57 UTC 2019 - Tomáš Chvátal <tchvatal@suse.com> - Switch to %pytest - Add patch to work well with new numpy: * numpy16.patch ------------------------------------------------------------------- Tue Mar 26 14:45:24 UTC 2019 - Tomáš Chvátal <tchvatal@suse.com> - Update to 0.13.2: * Upgrade to cloudpickle 0.8.0 * Add a non-regression test related to joblib issues #836 and #833, reporting that cloudpickle versions between 0.5.4 and 0.7 introduced a bug where global variables changes in a parent process between two calls to joblib.Parallel would not be propagated into the workers ------------------------------------------------------------------- Thu Mar 7 15:57:20 UTC 2019 - John Vandenberg <jayvdb@gmail.com> - Remove no longer necessary pytest argument -k 'not test_no_blas_crash_or_freeze_with_subprocesses' ------------------------------------------------------------------- Tue Jan 29 16:41:57 CET 2019 - mcepl@suse.com - Update to Release 0.13.1: * Memory now accepts pathlib.Path objects as ``location`` parameter. Also, a warning is raised if the returned backend is None while ``location`` is not None. * Make ``Parallel`` raise an informative ``RuntimeError`` when the active parallel backend has zero worker. * Make the ``DaskDistributedBackend`` wait for workers before trying to schedule work. This is useful in particular when the workers are provisionned dynamically but provisionning is not immediate (for instance using Kubernetes, Yarn or an HPC job queue). ------------------------------------------------------------------- Mon Jan 7 19:39:00 UTC 2019 - Todd R <toddrme2178@gmail.com> - update to Release 0.13.0 * Include loky 2.4.2 with default serialization with ``cloudpickle``. This can be tweaked with the environment variable ``LOKY_PICKLER``. * Fix nested backend in SequentialBackend to avoid changing the default backend to Sequential. (#792) * Fix nested_backend behavior to avoid setting the default number of workers to -1 when the backend is not dask. (#784) - Update to Release 0.12.5 * Include loky 2.3.1 with better error reporting when a worker is abruptly terminated. Also fixes spurious debug output. * Include cloudpickle 0.5.6. Fix a bug with the handling of global variables by locally defined functions. - Update to Release 0.12.4 * Include loky 2.3.0 with many bugfixes, notably w.r.t. when setting non-default multiprocessing contexts. Also include improvement on memory management of long running worker processes and fixed issues when using the loky backend under PyPy. * Raises a more explicit exception when a corrupted MemorizedResult is loaded. * Loading a corrupted cached file with mmap mode enabled would recompute the results and return them without memmory mapping. - Update to Release 0.12.3 * Fix joblib import setting the global start_method for multiprocessing. * Fix MemorizedResult not picklable (#747). * Fix Memory, MemorizedFunc and MemorizedResult round-trip pickling + unpickling (#746). * Fixed a regression in Memory when positional arguments are called as kwargs several times with different values (#751). * Integration of loky 2.2.2 that fixes issues with the selection of the default start method and improve the reporting when calling functions with arguments that raise an exception when unpickling. * Prevent MemorizedFunc.call_and_shelve from loading cached results to RAM when not necessary. Results in big performance improvements - Update to Release 0.12.2 * Integrate loky 2.2.0 to fix regression with unpicklable arguments and functions reported by users (#723, #643). * Loky 2.2.0 also provides a protection against memory leaks long running applications when psutil is installed (reported as #721). * Joblib now includes the code for the dask backend which has been updated to properly handle nested parallelism and data scattering at the same time (#722). * Restored some private API attribute and arguments (`MemorizedResult.argument_hash` and `BatchedCalls.__init__`'s `pickle_cache`) for backward compat. (#716, #732). * Fix a deprecation warning message (for `Memory`'s `cachedir`) (#720). ------------------------------------------------------------------- Thu Jan 3 07:07:28 UTC 2019 - Tomáš Chvátal <tchvatal@suse.com> - Disable blas test as it is very flaky outside of x86_64 ------------------------------------------------------------------- Fri Jul 27 06:35:25 UTC 2018 - jengelh@inai.de - Use noun phrase in summary. ------------------------------------------------------------------- Fri Jul 20 11:48:47 UTC 2018 - tchvatal@suse.com - Enable tests ------------------------------------------------------------------- Wed Jul 18 03:03:33 UTC 2018 - arun@gmx.de - specfile: * remove devel requirement - update to version 0.12.1: * Make sure that any exception triggered when serializing jobs in the queue will be wrapped as a PicklingError as in past versions of joblib. * Fix kwonlydefaults key error in filter_args (#715) - changes from version 0.12: * Implement the 'loky' backend with @ogrisel. This backend relies on a robust implementation of concurrent.futures.ProcessPoolExecutor with spawned processes that can be reused accross the Parallel calls. This fixes the bad interation with third paty libraries relying on thread pools, described in https://pythonhosted.org/joblib/parallel.html#bad-interaction-of-multiprocessing-and-third-party-libraries * Limit the number of threads used in worker processes by C-libraries that relies on threadpools. This functionality works for MKL, OpenBLAS, OpenMP and Accelerated. * Prevent numpy arrays with the same shape and data from hashing to the same memmap, to prevent jobs with preallocated arrays from writing over each other. * Reduce overhead of automatic memmap by removing the need to hash the array. * Make Memory.cache robust to PermissionError (errno 13) under Windows when run in combination with Parallel. * The automatic array memory mapping feature of Parallel does no longer use /dev/shm if it is too small (less than 2 GB). In particular in docker containers /dev/shm is only 64 MB by default which would cause frequent failures when running joblib in Docker containers. * Make it possible to hint for thread-based parallelism with prefer='threads' or enforce shared-memory semantics with require='sharedmem'. * Rely on the built-in exception nesting system of Python 3 to preserve traceback information when an exception is raised on a remote worker process. This avoid verbose and redundant exception reports under Python 3. * Preserve exception type information when doing nested Parallel calls instead of mapping the exception to the generic JoblibException type. * Introduce the concept of 'store' and refactor the Memory internal storage implementation to make it accept extra store backends for caching results. backend and backend_options are the new options added to Memory to specify and configure a store backend. * Add the register_store_backend function to extend the store backend used by default with Memory. This default store backend is named 'local' and corresponds to the local filesystem. * The store backend API is experimental and thus is subject to change in the future without deprecation. * The cachedir parameter of Memory is now marked as deprecated, use location instead. * Add support for LZ4 compression if lz4 package is installed. * Add register_compressor function for extending available compressors. * Allow passing a string to compress parameter in dump funtion. This string should correspond to the compressor used (e.g. zlib, gzip, lz4, etc). The default compression level is used in this case. * Allow parallel_backend to be used globally instead of only as a context manager. Support lazy registration of external parallel backends ------------------------------------------------------------------- Thu Jan 11 22:12:57 UTC 2018 - jengelh@inai.de - Ensure neutrality of description. ------------------------------------------------------------------- Mon May 22 16:35:59 UTC 2017 - toddrme2178@gmail.com - Implement single-spec version. - Run tests. - Fix source URL. - Update to version 0.11. * For a full changelog please see: https://github.com/joblib/joblib/blob/0.11/CHANGES.rst ------------------------------------------------------------------- Sun May 24 13:14:03 UTC 2015 - toddrme2178@gmail.com - Disable non-functional documentation ------------------------------------------------------------------- Sun Dec 8 19:47:59 UTC 2013 - p.drouand@gmail.com - Update to version 0.7.1 + MISC: capture meaningless argument (n_jobs=0) in Parallel + ENH Handles tuples, sets and Python 3's dict_keys type the same as lists. in pre_dispatch + ENH: fix function caching for IPython ------------------------------------------------------------------- Thu Oct 24 11:07:22 UTC 2013 - speilicke@suse.com - Require python-setuptools instead of distribute (upstreams merged) ------------------------------------------------------------------- Sat Feb 9 15:54:15 UTC 2013 - p.drouand@gmail.com - Update to version 0.7.0d * No changelog available - Clean the specfile and remove .buildinfo file ------------------------------------------------------------------- Wed Oct 10 20:59:57 UTC 2012 - scorot@free.fr - Add Group field in doc package for SLE 11 ------------------------------------------------------------------- Wed Sep 5 17:10:35 UTC 2012 - toddrme2178@gmail.com - Initial version
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