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Name: python310-fastparquet | Distribution: openSUSE Tumbleweed |
Version: 2024.5.0 | Vendor: openSUSE |
Release: 1.1 | Build date: Thu Jun 6 19:44:58 2024 |
Group: Unspecified | Build host: reproducible |
Size: 1580419 | Source RPM: python-fastparquet-2024.5.0-1.1.src.rpm |
Packager: http://bugs.opensuse.org | |
Url: https://github.com/dask/fastparquet/ | |
Summary: Python support for Parquet file format |
This is a Python implementation of the parquet format for integrating it into python-based Big Data workflows.
Apache-2.0
* Thu Jun 06 2024 Ben Greiner <code@bnavigator.de> - Update to 2024.5.0 * Allow zoneinfo objects (#916) * Use np.int64 type for day to nanosecond conversion (NEP50) (#922) * Mon Mar 04 2024 Ben Greiner <code@bnavigator.de> - Update to 2024.2.0 * allow loading categoricals even if not so in the pandas metadata, when a column is dict-encoded and we only have one row-group (#863) * apply dtype to the columns names series, even when selecting no columns (#861, 859) * don’t make strings while estimating bye column size (#858) * handle upstream depr (#857, 856) * Mon Jan 22 2024 Daniel Garcia <daniel.garcia@suse.com> - Do not run tests in s390x, bsc#1218603 * Tue Dec 05 2023 Dirk Müller <dmueller@suse.com> - update to 2023.10.0: * Datetime units in empty() with tz (#893) * Fewer inplace decompressions for V2 pages (#890 * Allow writing categorical column with no categories (#888) * Fixes for new numpy (#886) * RLE bools and DELTA for v1 pages (#885, 883) * Mon Sep 11 2023 Dirk Müller <dmueller@suse.com> - update to 2023.8.0: * More general timestamp units (#874) * ReadTheDocs V2 (#871) * Better roundtrip dtypes (#861, 859) * No convert when computing bytes-per-item for str (#858) * Sat Jul 01 2023 Arun Persaud <arun@gmx.de> - update to version 2023.7.0: * Add test case for reading non-pandas parquet file (#870) * Extra field when cloning ParquetFile (#866) * Fri Apr 28 2023 Dirk Müller <dmueller@suse.com> - update to 2023.4.0: * allow loading categoricals even if not so in the pandas metadata, when a column is dict-encodedand we only have one row-group (#863)  * apply dtype to the columns names series, even when selecting no columns (#861, 859)  * don't make strings while estimating bye column size (#858)  * handle upstream depr (#857, 856) * Thu Feb 09 2023 Arun Persaud <arun@gmx.de> - update to version 2023.2.0: * revert one-level set of filters (#852) * full size dict for decoding V2 pages (#850) * infer_object_encoding fix (#847) * row filtering with V2 pages (#845) * Wed Feb 08 2023 Arun Persaud <arun@gmx.de> - specfile: * remove fastparquet-pr835.patch, implemented upstream - update to version 2023.1.0: * big improvement to write speed * paging support for bigger row-groups * pandas 2.0 support * delta for big-endian architecture * Mon Jan 02 2023 Ben Greiner <code@bnavigator.de> - Update to 2022.12.0 * check all int32 values before passing to thrift writer * fix type of num_rows to i64 for big single file - Release 2022.11.0 * Switch to calver * Speed up loading of nullable types * Allow schema evolution by addition of columns * Allow specifying dtypes of output * update to scm versioning * fixes to row filter, statistics and tests * support pathlib.Paths * JSON encoder options - Drop fastparquet-pr813-updatefixes.patch * Fri Dec 23 2022 Guillaume GARDET <guillaume.gardet@opensuse.org> - Add patch to fox the test test_delta_from_def_2 on aarch64, armv7 and ppc64le: * fastparquet-pr835.patch * Fri Oct 28 2022 Ben Greiner <code@bnavigator.de> - Update to 0.8.3 * improved key/value handling and rejection of bad types * fix regression in consolidate_cats (caught in dask tests) - Release 0.8.2 * datetime indexes initialised to 0 to prevent overflow from randommemory * case from csv_to_parquet where stats exists but has not nulls entry * define len and bool for ParquetFile * maintain int types of optional data tha came from pandas * fix for delta encoding - Add fastparquet-pr813-updatefixes.patch gh#dask/fastparquet#813 * Tue Apr 26 2022 Ben Greiner <code@bnavigator.de> - Update to 0.8.1 * fix critical buffer overflow crash for large number of columns and long column names * metadata handling * thrift int32 for list * avoid error storing NaNs in column stats * Sat Jan 29 2022 Ben Greiner <code@bnavigator.de> - Update to 0.8.0 * our own cythonic thrift implementation (drop thrift dependency) * more in-place dataset editing ad reordering * python 3.10 support * fixes for multi-index and pandas types - Clean test skips * Sun Jan 16 2022 Ben Greiner <code@bnavigator.de> - Clean specfile from unused python36 conditionals - Require thrift 0.15.0 (+patch) for Python 3.10 compatibility * gh#dask/fastparquet#514 * Sat Nov 27 2021 Arun Persaud <arun@gmx.de> - update to version 0.7.2: * Ability to remove row-groups in-place for multifile datasets * Accept pandas nullable Float type * allow empty strings and fix min/max when there is no data * make writing statistics optional * row selection in to_pandas() * Sun Aug 08 2021 Ben Greiner <code@bnavigator.de> - Update to version 0.7.1 * Back compile for older versions of numpy * Make pandas nullable types opt-out. The old behaviour (casting to float) is still available with ParquetFile(..., pandas_nulls=False). * Fix time field regression: IsAdjustedToUTC will be False when there is no timezone * Micro improvements to the speed of ParquetFile creation by using simple simple string ops instead of regex and regularising filenames once at the start. Effects datasets with many files. - Release 0.7.0 * This version institutes major, breaking changes, listed here, and incremental fixes and additions. * Reading a directory without a _metadata summary file now works by providing only the directory, instead of a list of constituent files. This change also makes direct of use of fsspec filesystems, if given, to be able to load the footer metadata areas of the files concurrently, if the storage backend supports it, and not directly instantiating intermediate ParquetFile instances * row-level filtering of the data. Whereas previously, only full row-groups could be excluded on the basis of their parquet metadata statistics (if present), filtering can now be done within row-groups too. The syntax is the same as before, allowing for multiple column expressions to be combined with AND|OR, depending on the list structure. This mechanism requires two passes: one to load the columns needed to create the boolean mask, and another to load the columns actually needed in the output. This will not be faster, and may be slower, but in some cases can save significant memory footprint, if a small fraction of rows are considered good and the columns for the filter expression are not in the output. Not currently supported for reading with DataPageV2. * DELTA integer encoding (read-only): experimentally working, but we only have one test file to verify against, since it is not trivial to persuade Spark to produce files encoded this way. DELTA can be extremely compact a representation for slowly varying and/or monotonically increasing integers. * nanosecond resolution times: the new extended "logical" types system supports nanoseconds alongside the previous millis and micros. We now emit these for the default pandas time type, and produce full parquet schema including both "converted" and "logical" type information. Note that all output has isAdjustedToUTC=True, i.e., these are timestamps rather than local time. The time-zone is stored in the metadata, as before, and will be successfully recreated only in fastparquet and (py)arrow. Otherwise, the times will appear to be UTC. For compatibility with Spark, you may still want to use times="int96" when writing. * DataPageV2 writing: now we support both reading and writing. For writing, can be enabled with the environment variable FASTPARQUET_DATAPAGE_V2, or module global fastparquet.writer. DATAPAGE_VERSION and is off by default. It will become on by default in the future. In many cases, V2 will result in better read performance, because the data and page headers are encoded separately, so data can be directly read into the output without addition allocation/copies. This feature is considered experimental, but we believe it working well for most use cases (i.e., our test suite) and should be readable by all modern parquet frameworks including arrow and spark. * pandas nullable types: pandas supports "masked" extension arrays for types that previously could not support NULL at all: ints and bools. Fastparquet used to cast such columns to float, so that we could represent NULLs as NaN; now we use the new(er) masked types by default. This means faster reading of such columns, as there is no conversion. If the metadata guarantees that there are no nulls, we still use the non-nullable variant unless the data was written with fastparquet/pyarrow, and the metadata indicates that the original datatype was nullable. We already handled writing of nullable columns. * Tue May 18 2021 Ben Greiner <code@bnavigator.de> - Update to version 0.6.3 * no release notes * new requirement: cramjam instead of separate compression libs and their bindings * switch from numba to Cython * Fri Feb 12 2021 Dirk Müller <dmueller@suse.com> - skip python 36 build * Thu Feb 04 2021 Jan Engelhardt <jengelh@inai.de> - Use of "+=" in %check warrants bash as buildshell. * Wed Feb 03 2021 Ben Greiner <code@bnavigator.de> - Skip the import without warning test gh#dask/fastparquet#558 - Apply the Cepl-Strangelove-Parameter to pytest (--import-mode append) * Sat Jan 02 2021 Benjamin Greiner <code@bnavigator.de> - update to version 0.5 * no changelog - update test suite setup -- install the .test module
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