forked from pool/python-joblib
Accepting request 623917 from home:apersaud:branches:devel:languages:python
update to latest version OBS-URL: https://build.opensuse.org/request/show/623917 OBS-URL: https://build.opensuse.org/package/show/devel:languages:python/python-joblib?expand=0&rev=13
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version https://git-lfs.github.com/spec/v1
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oid sha256:7b8fd56df36d9731a83729395ccb85a3b401f62a96255deb1a77220c00ed4085
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size 213136
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3
joblib-0.12.1.tar.gz
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joblib-0.12.1.tar.gz
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version https://git-lfs.github.com/spec/v1
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oid sha256:68e6128e4734196616a39e2d48830ec7d61551c7f5748849e4c91478d2444524
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size 268415
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-------------------------------------------------------------------
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Wed Jul 18 03:03:33 UTC 2018 - arun@gmx.de
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- specfile:
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* remove devel requirement
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- update to version 0.12.1:
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* Make sure that any exception triggered when serializing jobs in
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the queue will be wrapped as a PicklingError as in past versions
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of joblib.
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* Fix kwonlydefaults key error in filter_args (#715)
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- changes from version 0.12:
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* Implement the 'loky' backend with @ogrisel. This backend relies on
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a robust implementation of concurrent.futures.ProcessPoolExecutor
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with spawned processes that can be reused accross the Parallel
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calls. This fixes the bad interation with third paty libraries
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relying on thread pools, described in
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https://pythonhosted.org/joblib/parallel.html#bad-interaction-of-multiprocessing-and-third-party-libraries
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* Limit the number of threads used in worker processes by
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C-libraries that relies on threadpools. This functionality works
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for MKL, OpenBLAS, OpenMP and Accelerated.
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* Prevent numpy arrays with the same shape and data from hashing to
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the same memmap, to prevent jobs with preallocated arrays from
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writing over each other.
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* Reduce overhead of automatic memmap by removing the need to hash
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the array.
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* Make Memory.cache robust to PermissionError (errno 13) under
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Windows when run in combination with Parallel.
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* The automatic array memory mapping feature of Parallel does no
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longer use /dev/shm if it is too small (less than 2 GB). In
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particular in docker containers /dev/shm is only 64 MB by default
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which would cause frequent failures when running joblib in Docker
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containers.
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* Make it possible to hint for thread-based parallelism with
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prefer='threads' or enforce shared-memory semantics with
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require='sharedmem'.
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* Rely on the built-in exception nesting system of Python 3 to
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preserve traceback information when an exception is raised on a
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remote worker process. This avoid verbose and redundant exception
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reports under Python 3.
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* Preserve exception type information when doing nested Parallel
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calls instead of mapping the exception to the generic
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JoblibException type.
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* Introduce the concept of 'store' and refactor the Memory internal
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storage implementation to make it accept extra store backends for
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caching results. backend and backend_options are the new options
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added to Memory to specify and configure a store backend.
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* Add the register_store_backend function to extend the store
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backend used by default with Memory. This default store backend is
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named 'local' and corresponds to the local filesystem.
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* The store backend API is experimental and thus is subject to
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change in the future without deprecation.
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* The cachedir parameter of Memory is now marked as deprecated, use
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location instead.
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* Add support for LZ4 compression if lz4 package is installed.
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* Add register_compressor function for extending available
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compressors.
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* Allow passing a string to compress parameter in dump funtion. This
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string should correspond to the compressor used (e.g. zlib, gzip,
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lz4, etc). The default compression level is used in this case.
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* Allow parallel_backend to be used globally instead of only as a
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context manager. Support lazy registration of external parallel
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backends
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-------------------------------------------------------------------
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-------------------------------------------------------------------
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Thu Jan 11 22:12:57 UTC 2018 - jengelh@inai.de
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Thu Jan 11 22:12:57 UTC 2018 - jengelh@inai.de
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@@ -16,28 +16,25 @@
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#
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#
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%bcond_with test
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%{?!python_module:%define python_module() python-%{**} python3-%{**}}
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%{?!python_module:%define python_module() python-%{**} python3-%{**}}
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%bcond_with test
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Name: python-joblib
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Name: python-joblib
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Version: 0.11
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Version: 0.12.1
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Release: 0
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Release: 0
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Summary: Lightweight pipelining: using Python functions as pipeline jobs
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Summary: Lightweight pipelining: using Python functions as pipeline jobs
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License: BSD-3-Clause
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License: BSD-3-Clause
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Group: Development/Languages/Python
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Group: Development/Languages/Python
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Url: https://github.com/joblib/joblib
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URL: https://github.com/joblib/joblib
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Source: https://files.pythonhosted.org/packages/source/j/joblib/joblib-%{version}.tar.gz
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Source: https://files.pythonhosted.org/packages/source/j/joblib/joblib-%{version}.tar.gz
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BuildRequires: %{python_module devel}
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BuildRequires: %{python_module setuptools}
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BuildRequires: %{python_module setuptools}
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BuildRequires: fdupes
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BuildRequires: fdupes
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BuildRequires: python-rpm-macros
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BuildRequires: python-rpm-macros
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Recommends: python-numpy
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BuildArch: noarch
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%if %{with test}
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%if %{with test}
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BuildRequires: %{python_module numpy}
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BuildRequires: %{python_module numpy}
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BuildRequires: %{python_module pytest}
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BuildRequires: %{python_module pytest}
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%endif
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%endif
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Recommends: python-numpy
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BuildRoot: %{_tmppath}/%{name}-%{version}-build
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BuildArch: noarch
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%python_subpackages
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%python_subpackages
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%description
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%description
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@@ -53,7 +50,6 @@ Python. In particular, joblib offers:
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Joblib can handle large data and has specific optimizations for `numpy` arrays.
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Joblib can handle large data and has specific optimizations for `numpy` arrays.
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%prep
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%prep
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%setup -q -n joblib-%{version}
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%setup -q -n joblib-%{version}
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@@ -70,8 +66,8 @@ Joblib can handle large data and has specific optimizations for `numpy` arrays.
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%endif
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%endif
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%files %{python_files}
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%files %{python_files}
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%defattr(-,root,root,-)
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%license LICENSE.txt
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%doc LICENSE.txt README.rst
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%doc README.rst
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%{python_sitelib}/joblib-%{version}-py*.egg-info
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%{python_sitelib}/joblib-%{version}-py*.egg-info
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%{python_sitelib}/joblib/
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%{python_sitelib}/joblib/
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