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-rw-r--r--python-pandas-plink.spec428
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+/pandas_plink-2.2.9.tar.gz
diff --git a/python-pandas-plink.spec b/python-pandas-plink.spec
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+%global _empty_manifest_terminate_build 0
+Name: python-pandas-plink
+Version: 2.2.9
+Release: 1
+Summary: Read PLINK files into Pandas data frames
+License: MIT
+URL: https://github.com/limix/pandas-plink
+Source0: https://mirrors.nju.edu.cn/pypi/web/packages/32/98/3a9ce4ab7cc8274fdb7e9d2911cdb946e953280214c06f70943fc02b5b2a/pandas_plink-2.2.9.tar.gz
+
+Requires: python3-Deprecated
+Requires: python3-cffi
+Requires: python3-dask[array,dataframe]
+Requires: python3-numpy
+Requires: python3-pandas
+Requires: python3-pytest
+Requires: python3-tqdm
+Requires: python3-xarray
+Requires: python3-zstandard
+
+%description
+# pandas-plink
+
+Pandas-plink is a Python package for reading [PLINK binary file format](https://www.cog-genomics.org/plink2/formats) andrealized relationship matrices (PLINK or GCTA).
+The file reading is taken place via [lazy loading](https://en.wikipedia.org/wiki/Lazy_loading), meaning that it saves up memory by actually reading only the genotypes that are actually accessed by the user.
+
+Notable changes can be found at the [CHANGELOG.md](https://raw.githubusercontent.com/limix/pandas-plink/master/CHANGELOG.md).
+
+## Install
+
+It can be installed using [pip](https://pypi.python.org/pypi/pip):
+
+```bash
+pip install pandas-plink
+```
+
+Alternatively it can be intalled via [conda](http://conda.pydata.org/docs/index.html):
+
+```bash
+conda install -c conda-forge pandas-plink
+```
+
+## Usage
+
+It is as simple as
+
+```python
+>>> from pandas_plink import read_plink1_bin
+>>> G = read_plink1_bin("chr11.bed", "chr11.bim", "chr11.fam", verbose=False)
+>>> print(G)
+<xarray.DataArray 'genotype' (sample: 14, variant: 779)>
+dask.array<shape=(14, 779), dtype=float64, chunksize=(14, 779)>
+Coordinates:
+ * sample (sample) object 'B001' 'B002' 'B003' ... 'B012' 'B013' 'B014'
+ * variant (variant) object '11_316849996' '11_316874359' ... '11_345698259'
+ father (sample) <U1 '0' '0' '0' '0' '0' '0' ... '0' '0' '0' '0' '0' '0'
+ fid (sample) <U4 'B001' 'B002' 'B003' 'B004' ... 'B012' 'B013' 'B014'
+ gender (sample) <U1 '0' '0' '0' '0' '0' '0' ... '0' '0' '0' '0' '0' '0'
+ i (sample) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13
+ iid (sample) <U4 'B001' 'B002' 'B003' 'B004' ... 'B012' 'B013' 'B014'
+ mother (sample) <U1 '0' '0' '0' '0' '0' '0' ... '0' '0' '0' '0' '0' '0'
+ trait (sample) <U2 '-9' '-9' '-9' '-9' '-9' ... '-9' '-9' '-9' '-9' '-9'
+ a0 (variant) <U1 'C' 'G' 'G' 'C' 'C' 'T' ... 'T' 'A' 'C' 'A' 'A' 'T'
+ a1 (variant) <U1 'T' 'C' 'C' 'T' 'T' 'A' ... 'C' 'G' 'T' 'G' 'C' 'C'
+ chrom (variant) <U2 '11' '11' '11' '11' '11' ... '11' '11' '11' '11' '11'
+ cm (variant) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0
+ pos (variant) int64 157439 181802 248969 ... 28937375 28961091 29005702
+ snp (variant) <U9 '316849996' '316874359' ... '345653648' '345698259'
+>>> print(G.sel(sample="B003", variant="11_316874359").values)
+0.0
+>>> print(G.a0.sel(variant="11_316874359").values)
+G
+>>> print(G.sel(sample="B003", variant="11_316941526").values)
+2.0
+>>> print(G.a1.sel(variant="11_316941526").values)
+C
+```
+Portions of the genotype will be read as the user access them.
+
+Covariance matrices can also be read very easily.
+Example:
+
+```python
+>>> from pandas_plink import read_rel
+>>> K = read_rel("plink2.rel.bin")
+>>> print(K)
+<xarray.DataArray (sample_0: 10, sample_1: 10)>
+array([[ 0.885782, 0.233846, -0.186339, -0.009789, -0.138897, 0.287779,
+ 0.269977, -0.231279, -0.095472, -0.213979],
+ [ 0.233846, 1.077493, -0.452858, 0.192877, -0.186027, 0.171027,
+ 0.406056, -0.013149, -0.131477, -0.134314],
+ [-0.186339, -0.452858, 1.183312, -0.040948, -0.146034, -0.204510,
+ -0.314808, -0.042503, 0.296828, -0.011661],
+ [-0.009789, 0.192877, -0.040948, 0.895360, -0.068605, 0.012023,
+ 0.057827, -0.192152, -0.089094, 0.174269],
+ [-0.138897, -0.186027, -0.146034, -0.068605, 1.183237, 0.085104,
+ -0.032974, 0.103608, 0.215769, 0.166648],
+ [ 0.287779, 0.171027, -0.204510, 0.012023, 0.085104, 0.956921,
+ 0.065427, -0.043752, -0.091492, -0.227673],
+ [ 0.269977, 0.406056, -0.314808, 0.057827, -0.032974, 0.065427,
+ 0.714746, -0.101254, -0.088171, -0.063964],
+ [-0.231279, -0.013149, -0.042503, -0.192152, 0.103608, -0.043752,
+ -0.101254, 1.423033, -0.298255, -0.074334],
+ [-0.095472, -0.131477, 0.296828, -0.089094, 0.215769, -0.091492,
+ -0.088171, -0.298255, 0.910274, -0.024663],
+ [-0.213979, -0.134314, -0.011661, 0.174269, 0.166648, -0.227673,
+ -0.063964, -0.074334, -0.024663, 0.914586]])
+Coordinates:
+ * sample_0 (sample_0) object 'HG00419' 'HG00650' ... 'NA20508' 'NA20753'
+ * sample_1 (sample_1) object 'HG00419' 'HG00650' ... 'NA20508' 'NA20753'
+ fid (sample_1) object 'HG00419' 'HG00650' ... 'NA20508' 'NA20753'
+ iid (sample_1) object 'HG00419' 'HG00650' ... 'NA20508' 'NA20753'
+>>> print(K.values)
+[[ 0.89 0.23 -0.19 -0.01 -0.14 0.29 0.27 -0.23 -0.10 -0.21]
+ [ 0.23 1.08 -0.45 0.19 -0.19 0.17 0.41 -0.01 -0.13 -0.13]
+ [-0.19 -0.45 1.18 -0.04 -0.15 -0.20 -0.31 -0.04 0.30 -0.01]
+ [-0.01 0.19 -0.04 0.90 -0.07 0.01 0.06 -0.19 -0.09 0.17]
+ [-0.14 -0.19 -0.15 -0.07 1.18 0.09 -0.03 0.10 0.22 0.17]
+ [ 0.29 0.17 -0.20 0.01 0.09 0.96 0.07 -0.04 -0.09 -0.23]
+ [ 0.27 0.41 -0.31 0.06 -0.03 0.07 0.71 -0.10 -0.09 -0.06]
+ [-0.23 -0.01 -0.04 -0.19 0.10 -0.04 -0.10 1.42 -0.30 -0.07]
+ [-0.10 -0.13 0.30 -0.09 0.22 -0.09 -0.09 -0.30 0.91 -0.02]
+ [-0.21 -0.13 -0.01 0.17 0.17 -0.23 -0.06 -0.07 -0.02 0.91]]
+```
+
+Please, refer to the [pandas-plink documentation](https://pandas-plink.readthedocs.io/) for more information.
+
+## Authors
+
+* [Danilo Horta](https://github.com/horta)
+
+## License
+
+This project is licensed under the [MIT License](https://raw.githubusercontent.com/limix/pandas-plink/master/LICENSE.md).
+
+
+
+
+%package -n python3-pandas-plink
+Summary: Read PLINK files into Pandas data frames
+Provides: python-pandas-plink
+BuildRequires: python3-devel
+BuildRequires: python3-setuptools
+BuildRequires: python3-pip
+BuildRequires: python3-cffi
+BuildRequires: gcc
+BuildRequires: gdb
+%description -n python3-pandas-plink
+# pandas-plink
+
+Pandas-plink is a Python package for reading [PLINK binary file format](https://www.cog-genomics.org/plink2/formats) andrealized relationship matrices (PLINK or GCTA).
+The file reading is taken place via [lazy loading](https://en.wikipedia.org/wiki/Lazy_loading), meaning that it saves up memory by actually reading only the genotypes that are actually accessed by the user.
+
+Notable changes can be found at the [CHANGELOG.md](https://raw.githubusercontent.com/limix/pandas-plink/master/CHANGELOG.md).
+
+## Install
+
+It can be installed using [pip](https://pypi.python.org/pypi/pip):
+
+```bash
+pip install pandas-plink
+```
+
+Alternatively it can be intalled via [conda](http://conda.pydata.org/docs/index.html):
+
+```bash
+conda install -c conda-forge pandas-plink
+```
+
+## Usage
+
+It is as simple as
+
+```python
+>>> from pandas_plink import read_plink1_bin
+>>> G = read_plink1_bin("chr11.bed", "chr11.bim", "chr11.fam", verbose=False)
+>>> print(G)
+<xarray.DataArray 'genotype' (sample: 14, variant: 779)>
+dask.array<shape=(14, 779), dtype=float64, chunksize=(14, 779)>
+Coordinates:
+ * sample (sample) object 'B001' 'B002' 'B003' ... 'B012' 'B013' 'B014'
+ * variant (variant) object '11_316849996' '11_316874359' ... '11_345698259'
+ father (sample) <U1 '0' '0' '0' '0' '0' '0' ... '0' '0' '0' '0' '0' '0'
+ fid (sample) <U4 'B001' 'B002' 'B003' 'B004' ... 'B012' 'B013' 'B014'
+ gender (sample) <U1 '0' '0' '0' '0' '0' '0' ... '0' '0' '0' '0' '0' '0'
+ i (sample) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13
+ iid (sample) <U4 'B001' 'B002' 'B003' 'B004' ... 'B012' 'B013' 'B014'
+ mother (sample) <U1 '0' '0' '0' '0' '0' '0' ... '0' '0' '0' '0' '0' '0'
+ trait (sample) <U2 '-9' '-9' '-9' '-9' '-9' ... '-9' '-9' '-9' '-9' '-9'
+ a0 (variant) <U1 'C' 'G' 'G' 'C' 'C' 'T' ... 'T' 'A' 'C' 'A' 'A' 'T'
+ a1 (variant) <U1 'T' 'C' 'C' 'T' 'T' 'A' ... 'C' 'G' 'T' 'G' 'C' 'C'
+ chrom (variant) <U2 '11' '11' '11' '11' '11' ... '11' '11' '11' '11' '11'
+ cm (variant) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0
+ pos (variant) int64 157439 181802 248969 ... 28937375 28961091 29005702
+ snp (variant) <U9 '316849996' '316874359' ... '345653648' '345698259'
+>>> print(G.sel(sample="B003", variant="11_316874359").values)
+0.0
+>>> print(G.a0.sel(variant="11_316874359").values)
+G
+>>> print(G.sel(sample="B003", variant="11_316941526").values)
+2.0
+>>> print(G.a1.sel(variant="11_316941526").values)
+C
+```
+Portions of the genotype will be read as the user access them.
+
+Covariance matrices can also be read very easily.
+Example:
+
+```python
+>>> from pandas_plink import read_rel
+>>> K = read_rel("plink2.rel.bin")
+>>> print(K)
+<xarray.DataArray (sample_0: 10, sample_1: 10)>
+array([[ 0.885782, 0.233846, -0.186339, -0.009789, -0.138897, 0.287779,
+ 0.269977, -0.231279, -0.095472, -0.213979],
+ [ 0.233846, 1.077493, -0.452858, 0.192877, -0.186027, 0.171027,
+ 0.406056, -0.013149, -0.131477, -0.134314],
+ [-0.186339, -0.452858, 1.183312, -0.040948, -0.146034, -0.204510,
+ -0.314808, -0.042503, 0.296828, -0.011661],
+ [-0.009789, 0.192877, -0.040948, 0.895360, -0.068605, 0.012023,
+ 0.057827, -0.192152, -0.089094, 0.174269],
+ [-0.138897, -0.186027, -0.146034, -0.068605, 1.183237, 0.085104,
+ -0.032974, 0.103608, 0.215769, 0.166648],
+ [ 0.287779, 0.171027, -0.204510, 0.012023, 0.085104, 0.956921,
+ 0.065427, -0.043752, -0.091492, -0.227673],
+ [ 0.269977, 0.406056, -0.314808, 0.057827, -0.032974, 0.065427,
+ 0.714746, -0.101254, -0.088171, -0.063964],
+ [-0.231279, -0.013149, -0.042503, -0.192152, 0.103608, -0.043752,
+ -0.101254, 1.423033, -0.298255, -0.074334],
+ [-0.095472, -0.131477, 0.296828, -0.089094, 0.215769, -0.091492,
+ -0.088171, -0.298255, 0.910274, -0.024663],
+ [-0.213979, -0.134314, -0.011661, 0.174269, 0.166648, -0.227673,
+ -0.063964, -0.074334, -0.024663, 0.914586]])
+Coordinates:
+ * sample_0 (sample_0) object 'HG00419' 'HG00650' ... 'NA20508' 'NA20753'
+ * sample_1 (sample_1) object 'HG00419' 'HG00650' ... 'NA20508' 'NA20753'
+ fid (sample_1) object 'HG00419' 'HG00650' ... 'NA20508' 'NA20753'
+ iid (sample_1) object 'HG00419' 'HG00650' ... 'NA20508' 'NA20753'
+>>> print(K.values)
+[[ 0.89 0.23 -0.19 -0.01 -0.14 0.29 0.27 -0.23 -0.10 -0.21]
+ [ 0.23 1.08 -0.45 0.19 -0.19 0.17 0.41 -0.01 -0.13 -0.13]
+ [-0.19 -0.45 1.18 -0.04 -0.15 -0.20 -0.31 -0.04 0.30 -0.01]
+ [-0.01 0.19 -0.04 0.90 -0.07 0.01 0.06 -0.19 -0.09 0.17]
+ [-0.14 -0.19 -0.15 -0.07 1.18 0.09 -0.03 0.10 0.22 0.17]
+ [ 0.29 0.17 -0.20 0.01 0.09 0.96 0.07 -0.04 -0.09 -0.23]
+ [ 0.27 0.41 -0.31 0.06 -0.03 0.07 0.71 -0.10 -0.09 -0.06]
+ [-0.23 -0.01 -0.04 -0.19 0.10 -0.04 -0.10 1.42 -0.30 -0.07]
+ [-0.10 -0.13 0.30 -0.09 0.22 -0.09 -0.09 -0.30 0.91 -0.02]
+ [-0.21 -0.13 -0.01 0.17 0.17 -0.23 -0.06 -0.07 -0.02 0.91]]
+```
+
+Please, refer to the [pandas-plink documentation](https://pandas-plink.readthedocs.io/) for more information.
+
+## Authors
+
+* [Danilo Horta](https://github.com/horta)
+
+## License
+
+This project is licensed under the [MIT License](https://raw.githubusercontent.com/limix/pandas-plink/master/LICENSE.md).
+
+
+
+
+%package help
+Summary: Development documents and examples for pandas-plink
+Provides: python3-pandas-plink-doc
+%description help
+# pandas-plink
+
+Pandas-plink is a Python package for reading [PLINK binary file format](https://www.cog-genomics.org/plink2/formats) andrealized relationship matrices (PLINK or GCTA).
+The file reading is taken place via [lazy loading](https://en.wikipedia.org/wiki/Lazy_loading), meaning that it saves up memory by actually reading only the genotypes that are actually accessed by the user.
+
+Notable changes can be found at the [CHANGELOG.md](https://raw.githubusercontent.com/limix/pandas-plink/master/CHANGELOG.md).
+
+## Install
+
+It can be installed using [pip](https://pypi.python.org/pypi/pip):
+
+```bash
+pip install pandas-plink
+```
+
+Alternatively it can be intalled via [conda](http://conda.pydata.org/docs/index.html):
+
+```bash
+conda install -c conda-forge pandas-plink
+```
+
+## Usage
+
+It is as simple as
+
+```python
+>>> from pandas_plink import read_plink1_bin
+>>> G = read_plink1_bin("chr11.bed", "chr11.bim", "chr11.fam", verbose=False)
+>>> print(G)
+<xarray.DataArray 'genotype' (sample: 14, variant: 779)>
+dask.array<shape=(14, 779), dtype=float64, chunksize=(14, 779)>
+Coordinates:
+ * sample (sample) object 'B001' 'B002' 'B003' ... 'B012' 'B013' 'B014'
+ * variant (variant) object '11_316849996' '11_316874359' ... '11_345698259'
+ father (sample) <U1 '0' '0' '0' '0' '0' '0' ... '0' '0' '0' '0' '0' '0'
+ fid (sample) <U4 'B001' 'B002' 'B003' 'B004' ... 'B012' 'B013' 'B014'
+ gender (sample) <U1 '0' '0' '0' '0' '0' '0' ... '0' '0' '0' '0' '0' '0'
+ i (sample) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13
+ iid (sample) <U4 'B001' 'B002' 'B003' 'B004' ... 'B012' 'B013' 'B014'
+ mother (sample) <U1 '0' '0' '0' '0' '0' '0' ... '0' '0' '0' '0' '0' '0'
+ trait (sample) <U2 '-9' '-9' '-9' '-9' '-9' ... '-9' '-9' '-9' '-9' '-9'
+ a0 (variant) <U1 'C' 'G' 'G' 'C' 'C' 'T' ... 'T' 'A' 'C' 'A' 'A' 'T'
+ a1 (variant) <U1 'T' 'C' 'C' 'T' 'T' 'A' ... 'C' 'G' 'T' 'G' 'C' 'C'
+ chrom (variant) <U2 '11' '11' '11' '11' '11' ... '11' '11' '11' '11' '11'
+ cm (variant) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0
+ pos (variant) int64 157439 181802 248969 ... 28937375 28961091 29005702
+ snp (variant) <U9 '316849996' '316874359' ... '345653648' '345698259'
+>>> print(G.sel(sample="B003", variant="11_316874359").values)
+0.0
+>>> print(G.a0.sel(variant="11_316874359").values)
+G
+>>> print(G.sel(sample="B003", variant="11_316941526").values)
+2.0
+>>> print(G.a1.sel(variant="11_316941526").values)
+C
+```
+Portions of the genotype will be read as the user access them.
+
+Covariance matrices can also be read very easily.
+Example:
+
+```python
+>>> from pandas_plink import read_rel
+>>> K = read_rel("plink2.rel.bin")
+>>> print(K)
+<xarray.DataArray (sample_0: 10, sample_1: 10)>
+array([[ 0.885782, 0.233846, -0.186339, -0.009789, -0.138897, 0.287779,
+ 0.269977, -0.231279, -0.095472, -0.213979],
+ [ 0.233846, 1.077493, -0.452858, 0.192877, -0.186027, 0.171027,
+ 0.406056, -0.013149, -0.131477, -0.134314],
+ [-0.186339, -0.452858, 1.183312, -0.040948, -0.146034, -0.204510,
+ -0.314808, -0.042503, 0.296828, -0.011661],
+ [-0.009789, 0.192877, -0.040948, 0.895360, -0.068605, 0.012023,
+ 0.057827, -0.192152, -0.089094, 0.174269],
+ [-0.138897, -0.186027, -0.146034, -0.068605, 1.183237, 0.085104,
+ -0.032974, 0.103608, 0.215769, 0.166648],
+ [ 0.287779, 0.171027, -0.204510, 0.012023, 0.085104, 0.956921,
+ 0.065427, -0.043752, -0.091492, -0.227673],
+ [ 0.269977, 0.406056, -0.314808, 0.057827, -0.032974, 0.065427,
+ 0.714746, -0.101254, -0.088171, -0.063964],
+ [-0.231279, -0.013149, -0.042503, -0.192152, 0.103608, -0.043752,
+ -0.101254, 1.423033, -0.298255, -0.074334],
+ [-0.095472, -0.131477, 0.296828, -0.089094, 0.215769, -0.091492,
+ -0.088171, -0.298255, 0.910274, -0.024663],
+ [-0.213979, -0.134314, -0.011661, 0.174269, 0.166648, -0.227673,
+ -0.063964, -0.074334, -0.024663, 0.914586]])
+Coordinates:
+ * sample_0 (sample_0) object 'HG00419' 'HG00650' ... 'NA20508' 'NA20753'
+ * sample_1 (sample_1) object 'HG00419' 'HG00650' ... 'NA20508' 'NA20753'
+ fid (sample_1) object 'HG00419' 'HG00650' ... 'NA20508' 'NA20753'
+ iid (sample_1) object 'HG00419' 'HG00650' ... 'NA20508' 'NA20753'
+>>> print(K.values)
+[[ 0.89 0.23 -0.19 -0.01 -0.14 0.29 0.27 -0.23 -0.10 -0.21]
+ [ 0.23 1.08 -0.45 0.19 -0.19 0.17 0.41 -0.01 -0.13 -0.13]
+ [-0.19 -0.45 1.18 -0.04 -0.15 -0.20 -0.31 -0.04 0.30 -0.01]
+ [-0.01 0.19 -0.04 0.90 -0.07 0.01 0.06 -0.19 -0.09 0.17]
+ [-0.14 -0.19 -0.15 -0.07 1.18 0.09 -0.03 0.10 0.22 0.17]
+ [ 0.29 0.17 -0.20 0.01 0.09 0.96 0.07 -0.04 -0.09 -0.23]
+ [ 0.27 0.41 -0.31 0.06 -0.03 0.07 0.71 -0.10 -0.09 -0.06]
+ [-0.23 -0.01 -0.04 -0.19 0.10 -0.04 -0.10 1.42 -0.30 -0.07]
+ [-0.10 -0.13 0.30 -0.09 0.22 -0.09 -0.09 -0.30 0.91 -0.02]
+ [-0.21 -0.13 -0.01 0.17 0.17 -0.23 -0.06 -0.07 -0.02 0.91]]
+```
+
+Please, refer to the [pandas-plink documentation](https://pandas-plink.readthedocs.io/) for more information.
+
+## Authors
+
+* [Danilo Horta](https://github.com/horta)
+
+## License
+
+This project is licensed under the [MIT License](https://raw.githubusercontent.com/limix/pandas-plink/master/LICENSE.md).
+
+
+
+
+%prep
+%autosetup -n pandas-plink-2.2.9
+
+%build
+%py3_build
+
+%install
+%py3_install
+install -d -m755 %{buildroot}/%{_pkgdocdir}
+if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
+if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
+if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
+if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
+pushd %{buildroot}
+if [ -d usr/lib ]; then
+ find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/lib64 ]; then
+ find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/bin ]; then
+ find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/sbin ]; then
+ find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+touch doclist.lst
+if [ -d usr/share/man ]; then
+ find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
+fi
+popd
+mv %{buildroot}/filelist.lst .
+mv %{buildroot}/doclist.lst .
+
+%files -n python3-pandas-plink -f filelist.lst
+%dir %{python3_sitearch}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Wed Apr 12 2023 Python_Bot <Python_Bot@openeuler.org> - 2.2.9-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..df56c3f
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+28d3fd16c5b5f4b39464d0216926af20 pandas_plink-2.2.9.tar.gz
generated by cgit v1.2.3 (git 2.25.1) at 2026-09-12 13:29:28 +0000