automatic import of python-pyvcf

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+/PyVCF-0.6.8.tar.gz
diff --git a/python-pyvcf.spec b/python-pyvcf.spec
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+%global _empty_manifest_terminate_build 0
+Name:		python-PyVCF
+Version:	0.6.8
+Release:	1
+Summary:	Variant Call Format (VCF) parser for Python
+License:	UNKNOWN
+URL:		https://github.com/jamescasbon/PyVCF
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/20/b6/36bfb1760f6983788d916096193fc14c83cce512c7787c93380e09458c09/PyVCF-0.6.8.tar.gz
+BuildArch:	noarch
+
+
+%description
+A VCFv4.0 and 4.1 parser for Python.
+
+Online version of PyVCF documentation is available at http://pyvcf.rtfd.org/
+
+The intent of this module is to mimic the ``csv`` module in the Python stdlib,
+as opposed to more flexible serialization formats like JSON or YAML.  ``vcf``
+will attempt to parse the content of each record based on the data types
+specified in the meta-information lines --  specifically the ##INFO and
+##FORMAT lines.  If these lines are missing or incomplete, it will check
+against the reserved types mentioned in the spec.  Failing that, it will just
+return strings.
+
+There main interface is the class: ``Reader``.  It takes a file-like
+object and acts as a reader::
+
+    >>> import vcf
+    >>> vcf_reader = vcf.Reader(open('vcf/test/example-4.0.vcf', 'r'))
+    >>> for record in vcf_reader:
+    ...     print record
+    Record(CHROM=20, POS=14370, REF=G, ALT=[A])
+    Record(CHROM=20, POS=17330, REF=T, ALT=[A])
+    Record(CHROM=20, POS=1110696, REF=A, ALT=[G, T])
+    Record(CHROM=20, POS=1230237, REF=T, ALT=[None])
+    Record(CHROM=20, POS=1234567, REF=GTCT, ALT=[G, GTACT])
+
+
+This produces a great deal of information, but it is conveniently accessed.
+The attributes of a Record are the 8 fixed fields from the VCF spec::
+
+    * ``Record.CHROM``
+    * ``Record.POS``
+    * ``Record.ID``
+    * ``Record.REF``
+    * ``Record.ALT``
+    * ``Record.QUAL``
+    * ``Record.FILTER``
+    * ``Record.INFO``
+
+plus attributes to handle genotype information:
+
+    * ``Record.FORMAT``
+    * ``Record.samples``
+    * ``Record.genotype``
+
+``samples`` and ``genotype``, not being the title of any column, are left lowercase.  The format
+of the fixed fields is from the spec.  Comma-separated lists in the VCF are
+converted to lists.  In particular, one-entry VCF lists are converted to
+one-entry Python lists (see, e.g., ``Record.ALT``).  Semicolon-delimited lists
+of key=value pairs are converted to Python dictionaries, with flags being given
+a ``True`` value. Integers and floats are handled exactly as you'd expect::
+
+    >>> vcf_reader = vcf.Reader(open('vcf/test/example-4.0.vcf', 'r'))
+    >>> record = next(vcf_reader)
+    >>> print record.POS
+    14370
+    >>> print record.ALT
+    [A]
+    >>> print record.INFO['AF']
+    [0.5]
+
+There are a number of convenience methods and properties for each ``Record`` allowing you to
+examine properties of interest::
+
+    >>> print record.num_called, record.call_rate, record.num_unknown
+    3 1.0 0
+    >>> print record.num_hom_ref, record.num_het, record.num_hom_alt
+    1 1 1
+    >>> print record.nucl_diversity, record.aaf, record.heterozygosity
+    0.6 [0.5] 0.5
+    >>> print record.get_hets()
+    [Call(sample=NA00002, CallData(GT=1|0, GQ=48, DP=8, HQ=[51, 51]))]
+    >>> print record.is_snp, record.is_indel, record.is_transition, record.is_deletion
+    True False True False
+    >>> print record.var_type, record.var_subtype
+    snp ts
+    >>> print record.is_monomorphic
+    False
+
+``record.FORMAT`` will be a string specifying the format of the genotype
+fields.  In case the FORMAT column does not exist, ``record.FORMAT`` is
+``None``.  Finally, ``record.samples`` is a list of dictionaries containing the
+parsed sample column and ``record.genotype`` is a way of looking up genotypes
+by sample name::
+
+    >>> record = next(vcf_reader)
+    >>> for sample in record.samples:
+    ...     print sample['GT']
+    0|0
+    0|1
+    0/0
+    >>> print record.genotype('NA00001')['GT']
+    0|0
+
+The genotypes are represented by ``Call`` objects, which have three attributes: the
+corresponding Record ``site``, the sample name in ``sample`` and a dictionary of
+call data in ``data``::
+
+     >>> call = record.genotype('NA00001')
+     >>> print call.site
+     Record(CHROM=20, POS=17330, REF=T, ALT=[A])
+     >>> print call.sample
+     NA00001
+     >>> print call.data
+     CallData(GT=0|0, GQ=49, DP=3, HQ=[58, 50])
+
+Please note that as of release 0.4.0, attributes known to have single values (such as
+``DP`` and ``GQ`` above) are returned as values.  Other attributes are returned
+as lists (such as ``HQ`` above).
+
+There are also a number of methods::
+
+    >>> print call.called, call.gt_type, call.gt_bases, call.phased
+    True 0 T|T True
+
+Metadata regarding the VCF file itself can be investigated through the
+following attributes:
+
+    * ``Reader.metadata``
+    * ``Reader.infos``
+    * ``Reader.filters``
+    * ``Reader.formats``
+    * ``Reader.samples``
+
+For example::
+
+    >>> vcf_reader.metadata['fileDate']
+    '20090805'
+    >>> vcf_reader.samples
+    ['NA00001', 'NA00002', 'NA00003']
+    >>> vcf_reader.filters
+    OrderedDict([('q10', Filter(id='q10', desc='Quality below 10')), ('s50', Filter(id='s50', desc='Less than 50% of samples have data'))])
+    >>> vcf_reader.infos['AA'].desc
+    'Ancestral Allele'
+
+ALT records are actually classes, so that you can interrogate them::
+
+    >>> reader = vcf.Reader(open('vcf/test/example-4.1-bnd.vcf'))
+    >>> _ = next(reader); row = next(reader)
+    >>> print row
+    Record(CHROM=1, POS=2, REF=T, ALT=[T[2:3[])
+    >>> bnd = row.ALT[0]
+    >>> print bnd.withinMainAssembly, bnd.orientation, bnd.remoteOrientation, bnd.connectingSequence
+    True False True T
+
+The Reader supports retrieval of records within designated regions for files
+with tabix indexes via the fetch method. This requires the pysam module as a
+dependency. Pass in a chromosome, and, optionally, start and end coordinates,
+for the regions of interest::
+
+    >>> vcf_reader = vcf.Reader(filename='vcf/test/tb.vcf.gz')
+    >>> # fetch all records on chromosome 20 from base 1110696 through 1230237
+    >>> for record in vcf_reader.fetch('20', 1110695, 1230237):  # doctest: +SKIP
+    ...     print record
+    Record(CHROM=20, POS=1110696, REF=A, ALT=[G, T])
+    Record(CHROM=20, POS=1230237, REF=T, ALT=[None])
+
+Note that the start and end coordinates are in the zero-based, half-open
+coordinate system, similar to ``_Record.start`` and ``_Record.end``. The very
+first base of a chromosome is index 0, and the the region includes bases up
+to, but not including the base at the end coordinate. For example::
+
+    >>> # fetch all records on chromosome 4 from base 11 through 20
+    >>> vcf_reader.fetch('4', 10, 20)   # doctest: +SKIP
+
+would include all records overlapping a 10 base pair region from the 11th base
+of through the 20th base (which is at index 19) of chromosome 4. It would not
+include the 21st base (at index 20). (See
+http://genomewiki.ucsc.edu/index.php/Coordinate_Transforms for more
+information on the zero-based, half-open coordinate system.)
+
+The ``Writer`` class provides a way of writing a VCF file.  Currently, you must specify a
+template ``Reader`` which provides the metadata::
+
+    >>> vcf_reader = vcf.Reader(filename='vcf/test/tb.vcf.gz')
+    >>> vcf_writer = vcf.Writer(open('/dev/null', 'w'), vcf_reader)
+    >>> for record in vcf_reader:
+    ...     vcf_writer.write_record(record)
+
+An extensible script is available to filter vcf files in vcf_filter.py.  VCF filters
+declared by other packages will be available for use in this script.  Please
+see :doc:`FILTERS` for full description.
+
+
+%package -n python3-PyVCF
+Summary:	Variant Call Format (VCF) parser for Python
+Provides:	python-PyVCF
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-PyVCF
+A VCFv4.0 and 4.1 parser for Python.
+
+Online version of PyVCF documentation is available at http://pyvcf.rtfd.org/
+
+The intent of this module is to mimic the ``csv`` module in the Python stdlib,
+as opposed to more flexible serialization formats like JSON or YAML.  ``vcf``
+will attempt to parse the content of each record based on the data types
+specified in the meta-information lines --  specifically the ##INFO and
+##FORMAT lines.  If these lines are missing or incomplete, it will check
+against the reserved types mentioned in the spec.  Failing that, it will just
+return strings.
+
+There main interface is the class: ``Reader``.  It takes a file-like
+object and acts as a reader::
+
+    >>> import vcf
+    >>> vcf_reader = vcf.Reader(open('vcf/test/example-4.0.vcf', 'r'))
+    >>> for record in vcf_reader:
+    ...     print record
+    Record(CHROM=20, POS=14370, REF=G, ALT=[A])
+    Record(CHROM=20, POS=17330, REF=T, ALT=[A])
+    Record(CHROM=20, POS=1110696, REF=A, ALT=[G, T])
+    Record(CHROM=20, POS=1230237, REF=T, ALT=[None])
+    Record(CHROM=20, POS=1234567, REF=GTCT, ALT=[G, GTACT])
+
+
+This produces a great deal of information, but it is conveniently accessed.
+The attributes of a Record are the 8 fixed fields from the VCF spec::
+
+    * ``Record.CHROM``
+    * ``Record.POS``
+    * ``Record.ID``
+    * ``Record.REF``
+    * ``Record.ALT``
+    * ``Record.QUAL``
+    * ``Record.FILTER``
+    * ``Record.INFO``
+
+plus attributes to handle genotype information:
+
+    * ``Record.FORMAT``
+    * ``Record.samples``
+    * ``Record.genotype``
+
+``samples`` and ``genotype``, not being the title of any column, are left lowercase.  The format
+of the fixed fields is from the spec.  Comma-separated lists in the VCF are
+converted to lists.  In particular, one-entry VCF lists are converted to
+one-entry Python lists (see, e.g., ``Record.ALT``).  Semicolon-delimited lists
+of key=value pairs are converted to Python dictionaries, with flags being given
+a ``True`` value. Integers and floats are handled exactly as you'd expect::
+
+    >>> vcf_reader = vcf.Reader(open('vcf/test/example-4.0.vcf', 'r'))
+    >>> record = next(vcf_reader)
+    >>> print record.POS
+    14370
+    >>> print record.ALT
+    [A]
+    >>> print record.INFO['AF']
+    [0.5]
+
+There are a number of convenience methods and properties for each ``Record`` allowing you to
+examine properties of interest::
+
+    >>> print record.num_called, record.call_rate, record.num_unknown
+    3 1.0 0
+    >>> print record.num_hom_ref, record.num_het, record.num_hom_alt
+    1 1 1
+    >>> print record.nucl_diversity, record.aaf, record.heterozygosity
+    0.6 [0.5] 0.5
+    >>> print record.get_hets()
+    [Call(sample=NA00002, CallData(GT=1|0, GQ=48, DP=8, HQ=[51, 51]))]
+    >>> print record.is_snp, record.is_indel, record.is_transition, record.is_deletion
+    True False True False
+    >>> print record.var_type, record.var_subtype
+    snp ts
+    >>> print record.is_monomorphic
+    False
+
+``record.FORMAT`` will be a string specifying the format of the genotype
+fields.  In case the FORMAT column does not exist, ``record.FORMAT`` is
+``None``.  Finally, ``record.samples`` is a list of dictionaries containing the
+parsed sample column and ``record.genotype`` is a way of looking up genotypes
+by sample name::
+
+    >>> record = next(vcf_reader)
+    >>> for sample in record.samples:
+    ...     print sample['GT']
+    0|0
+    0|1
+    0/0
+    >>> print record.genotype('NA00001')['GT']
+    0|0
+
+The genotypes are represented by ``Call`` objects, which have three attributes: the
+corresponding Record ``site``, the sample name in ``sample`` and a dictionary of
+call data in ``data``::
+
+     >>> call = record.genotype('NA00001')
+     >>> print call.site
+     Record(CHROM=20, POS=17330, REF=T, ALT=[A])
+     >>> print call.sample
+     NA00001
+     >>> print call.data
+     CallData(GT=0|0, GQ=49, DP=3, HQ=[58, 50])
+
+Please note that as of release 0.4.0, attributes known to have single values (such as
+``DP`` and ``GQ`` above) are returned as values.  Other attributes are returned
+as lists (such as ``HQ`` above).
+
+There are also a number of methods::
+
+    >>> print call.called, call.gt_type, call.gt_bases, call.phased
+    True 0 T|T True
+
+Metadata regarding the VCF file itself can be investigated through the
+following attributes:
+
+    * ``Reader.metadata``
+    * ``Reader.infos``
+    * ``Reader.filters``
+    * ``Reader.formats``
+    * ``Reader.samples``
+
+For example::
+
+    >>> vcf_reader.metadata['fileDate']
+    '20090805'
+    >>> vcf_reader.samples
+    ['NA00001', 'NA00002', 'NA00003']
+    >>> vcf_reader.filters
+    OrderedDict([('q10', Filter(id='q10', desc='Quality below 10')), ('s50', Filter(id='s50', desc='Less than 50% of samples have data'))])
+    >>> vcf_reader.infos['AA'].desc
+    'Ancestral Allele'
+
+ALT records are actually classes, so that you can interrogate them::
+
+    >>> reader = vcf.Reader(open('vcf/test/example-4.1-bnd.vcf'))
+    >>> _ = next(reader); row = next(reader)
+    >>> print row
+    Record(CHROM=1, POS=2, REF=T, ALT=[T[2:3[])
+    >>> bnd = row.ALT[0]
+    >>> print bnd.withinMainAssembly, bnd.orientation, bnd.remoteOrientation, bnd.connectingSequence
+    True False True T
+
+The Reader supports retrieval of records within designated regions for files
+with tabix indexes via the fetch method. This requires the pysam module as a
+dependency. Pass in a chromosome, and, optionally, start and end coordinates,
+for the regions of interest::
+
+    >>> vcf_reader = vcf.Reader(filename='vcf/test/tb.vcf.gz')
+    >>> # fetch all records on chromosome 20 from base 1110696 through 1230237
+    >>> for record in vcf_reader.fetch('20', 1110695, 1230237):  # doctest: +SKIP
+    ...     print record
+    Record(CHROM=20, POS=1110696, REF=A, ALT=[G, T])
+    Record(CHROM=20, POS=1230237, REF=T, ALT=[None])
+
+Note that the start and end coordinates are in the zero-based, half-open
+coordinate system, similar to ``_Record.start`` and ``_Record.end``. The very
+first base of a chromosome is index 0, and the the region includes bases up
+to, but not including the base at the end coordinate. For example::
+
+    >>> # fetch all records on chromosome 4 from base 11 through 20
+    >>> vcf_reader.fetch('4', 10, 20)   # doctest: +SKIP
+
+would include all records overlapping a 10 base pair region from the 11th base
+of through the 20th base (which is at index 19) of chromosome 4. It would not
+include the 21st base (at index 20). (See
+http://genomewiki.ucsc.edu/index.php/Coordinate_Transforms for more
+information on the zero-based, half-open coordinate system.)
+
+The ``Writer`` class provides a way of writing a VCF file.  Currently, you must specify a
+template ``Reader`` which provides the metadata::
+
+    >>> vcf_reader = vcf.Reader(filename='vcf/test/tb.vcf.gz')
+    >>> vcf_writer = vcf.Writer(open('/dev/null', 'w'), vcf_reader)
+    >>> for record in vcf_reader:
+    ...     vcf_writer.write_record(record)
+
+An extensible script is available to filter vcf files in vcf_filter.py.  VCF filters
+declared by other packages will be available for use in this script.  Please
+see :doc:`FILTERS` for full description.
+
+
+%package help
+Summary:	Development documents and examples for PyVCF
+Provides:	python3-PyVCF-doc
+%description help
+A VCFv4.0 and 4.1 parser for Python.
+
+Online version of PyVCF documentation is available at http://pyvcf.rtfd.org/
+
+The intent of this module is to mimic the ``csv`` module in the Python stdlib,
+as opposed to more flexible serialization formats like JSON or YAML.  ``vcf``
+will attempt to parse the content of each record based on the data types
+specified in the meta-information lines --  specifically the ##INFO and
+##FORMAT lines.  If these lines are missing or incomplete, it will check
+against the reserved types mentioned in the spec.  Failing that, it will just
+return strings.
+
+There main interface is the class: ``Reader``.  It takes a file-like
+object and acts as a reader::
+
+    >>> import vcf
+    >>> vcf_reader = vcf.Reader(open('vcf/test/example-4.0.vcf', 'r'))
+    >>> for record in vcf_reader:
+    ...     print record
+    Record(CHROM=20, POS=14370, REF=G, ALT=[A])
+    Record(CHROM=20, POS=17330, REF=T, ALT=[A])
+    Record(CHROM=20, POS=1110696, REF=A, ALT=[G, T])
+    Record(CHROM=20, POS=1230237, REF=T, ALT=[None])
+    Record(CHROM=20, POS=1234567, REF=GTCT, ALT=[G, GTACT])
+
+
+This produces a great deal of information, but it is conveniently accessed.
+The attributes of a Record are the 8 fixed fields from the VCF spec::
+
+    * ``Record.CHROM``
+    * ``Record.POS``
+    * ``Record.ID``
+    * ``Record.REF``
+    * ``Record.ALT``
+    * ``Record.QUAL``
+    * ``Record.FILTER``
+    * ``Record.INFO``
+
+plus attributes to handle genotype information:
+
+    * ``Record.FORMAT``
+    * ``Record.samples``
+    * ``Record.genotype``
+
+``samples`` and ``genotype``, not being the title of any column, are left lowercase.  The format
+of the fixed fields is from the spec.  Comma-separated lists in the VCF are
+converted to lists.  In particular, one-entry VCF lists are converted to
+one-entry Python lists (see, e.g., ``Record.ALT``).  Semicolon-delimited lists
+of key=value pairs are converted to Python dictionaries, with flags being given
+a ``True`` value. Integers and floats are handled exactly as you'd expect::
+
+    >>> vcf_reader = vcf.Reader(open('vcf/test/example-4.0.vcf', 'r'))
+    >>> record = next(vcf_reader)
+    >>> print record.POS
+    14370
+    >>> print record.ALT
+    [A]
+    >>> print record.INFO['AF']
+    [0.5]
+
+There are a number of convenience methods and properties for each ``Record`` allowing you to
+examine properties of interest::
+
+    >>> print record.num_called, record.call_rate, record.num_unknown
+    3 1.0 0
+    >>> print record.num_hom_ref, record.num_het, record.num_hom_alt
+    1 1 1
+    >>> print record.nucl_diversity, record.aaf, record.heterozygosity
+    0.6 [0.5] 0.5
+    >>> print record.get_hets()
+    [Call(sample=NA00002, CallData(GT=1|0, GQ=48, DP=8, HQ=[51, 51]))]
+    >>> print record.is_snp, record.is_indel, record.is_transition, record.is_deletion
+    True False True False
+    >>> print record.var_type, record.var_subtype
+    snp ts
+    >>> print record.is_monomorphic
+    False
+
+``record.FORMAT`` will be a string specifying the format of the genotype
+fields.  In case the FORMAT column does not exist, ``record.FORMAT`` is
+``None``.  Finally, ``record.samples`` is a list of dictionaries containing the
+parsed sample column and ``record.genotype`` is a way of looking up genotypes
+by sample name::
+
+    >>> record = next(vcf_reader)
+    >>> for sample in record.samples:
+    ...     print sample['GT']
+    0|0
+    0|1
+    0/0
+    >>> print record.genotype('NA00001')['GT']
+    0|0
+
+The genotypes are represented by ``Call`` objects, which have three attributes: the
+corresponding Record ``site``, the sample name in ``sample`` and a dictionary of
+call data in ``data``::
+
+     >>> call = record.genotype('NA00001')
+     >>> print call.site
+     Record(CHROM=20, POS=17330, REF=T, ALT=[A])
+     >>> print call.sample
+     NA00001
+     >>> print call.data
+     CallData(GT=0|0, GQ=49, DP=3, HQ=[58, 50])
+
+Please note that as of release 0.4.0, attributes known to have single values (such as
+``DP`` and ``GQ`` above) are returned as values.  Other attributes are returned
+as lists (such as ``HQ`` above).
+
+There are also a number of methods::
+
+    >>> print call.called, call.gt_type, call.gt_bases, call.phased
+    True 0 T|T True
+
+Metadata regarding the VCF file itself can be investigated through the
+following attributes:
+
+    * ``Reader.metadata``
+    * ``Reader.infos``
+    * ``Reader.filters``
+    * ``Reader.formats``
+    * ``Reader.samples``
+
+For example::
+
+    >>> vcf_reader.metadata['fileDate']
+    '20090805'
+    >>> vcf_reader.samples
+    ['NA00001', 'NA00002', 'NA00003']
+    >>> vcf_reader.filters
+    OrderedDict([('q10', Filter(id='q10', desc='Quality below 10')), ('s50', Filter(id='s50', desc='Less than 50% of samples have data'))])
+    >>> vcf_reader.infos['AA'].desc
+    'Ancestral Allele'
+
+ALT records are actually classes, so that you can interrogate them::
+
+    >>> reader = vcf.Reader(open('vcf/test/example-4.1-bnd.vcf'))
+    >>> _ = next(reader); row = next(reader)
+    >>> print row
+    Record(CHROM=1, POS=2, REF=T, ALT=[T[2:3[])
+    >>> bnd = row.ALT[0]
+    >>> print bnd.withinMainAssembly, bnd.orientation, bnd.remoteOrientation, bnd.connectingSequence
+    True False True T
+
+The Reader supports retrieval of records within designated regions for files
+with tabix indexes via the fetch method. This requires the pysam module as a
+dependency. Pass in a chromosome, and, optionally, start and end coordinates,
+for the regions of interest::
+
+    >>> vcf_reader = vcf.Reader(filename='vcf/test/tb.vcf.gz')
+    >>> # fetch all records on chromosome 20 from base 1110696 through 1230237
+    >>> for record in vcf_reader.fetch('20', 1110695, 1230237):  # doctest: +SKIP
+    ...     print record
+    Record(CHROM=20, POS=1110696, REF=A, ALT=[G, T])
+    Record(CHROM=20, POS=1230237, REF=T, ALT=[None])
+
+Note that the start and end coordinates are in the zero-based, half-open
+coordinate system, similar to ``_Record.start`` and ``_Record.end``. The very
+first base of a chromosome is index 0, and the the region includes bases up
+to, but not including the base at the end coordinate. For example::
+
+    >>> # fetch all records on chromosome 4 from base 11 through 20
+    >>> vcf_reader.fetch('4', 10, 20)   # doctest: +SKIP
+
+would include all records overlapping a 10 base pair region from the 11th base
+of through the 20th base (which is at index 19) of chromosome 4. It would not
+include the 21st base (at index 20). (See
+http://genomewiki.ucsc.edu/index.php/Coordinate_Transforms for more
+information on the zero-based, half-open coordinate system.)
+
+The ``Writer`` class provides a way of writing a VCF file.  Currently, you must specify a
+template ``Reader`` which provides the metadata::
+
+    >>> vcf_reader = vcf.Reader(filename='vcf/test/tb.vcf.gz')
+    >>> vcf_writer = vcf.Writer(open('/dev/null', 'w'), vcf_reader)
+    >>> for record in vcf_reader:
+    ...     vcf_writer.write_record(record)
+
+An extensible script is available to filter vcf files in vcf_filter.py.  VCF filters
+declared by other packages will be available for use in this script.  Please
+see :doc:`FILTERS` for full description.
+
+
+%prep
+%autosetup -n PyVCF-0.6.8
+
+%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-PyVCF -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 0.6.8-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..6c15eba
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+3cc70aa59e62dab7b4a85bd5a9f2e714  PyVCF-0.6.8.tar.gz