Your message dated Wed, 02 Dec 2020 00:03:37 +0000
with message-id <[email protected]>
and subject line Bug#950932: fixed in q2-types 2020.11.0-1
has caused the Debian Bug report #950932,
regarding q2-types: FTBFS with pandas 1.0: test failures
to be marked as done.

This means that you claim that the problem has been dealt with.
If this is not the case it is now your responsibility to reopen the
Bug report if necessary, and/or fix the problem forthwith.

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-- 
950932: https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=950932
Debian Bug Tracking System
Contact [email protected] with problems
--- Begin Message ---
Source: q2-types
Version: 2019.10.0-1
Control: block 950430 by -1

With pandas 1.0 from experimental:

=================================== FAILURES =================================== ____________ TestTaxonomyFormatsToDataFrame.test_duplicate_columns _____________

self = <q2_types.feature_data.tests.test_transformer.TestTaxonomyFormatsToDataFrame testMethod=test_duplicate_columns>

    def test_duplicate_columns(self):
        with self.assertRaisesRegex(ValueError, 'duplicated: Column1'):
            _taxonomy_formats_to_dataframe(
                self.get_data_path(os.path.join(
>                   'taxonomy', 'duplicate-columns.tsv')))

q2_types/feature_data/tests/test_transformer.py:355:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    def _taxonomy_formats_to_dataframe(filepath, has_header=None):
        """Read any of the three taxonomy formats into a dataframe.

        Parameters
        ----------
        filepath : str
            The taxonomy-formatted file to be read.
        has_header : bool, optional
If `None`, autodetect the header: only `Feature ID<tab>Taxon` is recognized, optionally followed by other columns. If `True`, the file must have the expected header described above otherwise an error is
            raised. If `False`, the file is read without assuming a header.

        Returns
        -------
        pd.DataFrame
            Dataframe containing parsed contents of the taxonomy file. The
dataframe will have its index name set to `Feature ID` and its first column will be `Taxon`, followed by any other columns in the input
            file.

        """
# Using `dtype=object` and `set_index()` to avoid type casting/inference of
        # any columns or the index.
        df = pd.read_csv(filepath, sep='\t', skip_blank_lines=True,
                         header=None, dtype=object)

        if len(df.columns) < 2:
            raise ValueError(
                "Taxonomy format requires at least two columns, found %d."
                % len(df.columns))

        if has_header and not _has_expected_header(df):
            raise ValueError(
"Taxonomy format requires a header with `Feature ID` and `Taxon` "
                "as the first two columns.")

        if has_header or (has_header is None and _has_expected_header(df)):
            # Make first row the header:
            #     https://stackoverflow.com/a/26147330/3776794
            df.columns = df.iloc[0]
            df.columns.name = None
            df = df.reindex(df.index.drop(0))
        else:
            # No header
            unnamed_columns = ['Unnamed Column %d' % (i + 1)
                               for i in range(len(df.columns[2:]))]
            df.columns = TSVTaxonomyFormat.HEADER + unnamed_columns

        df.set_index(df.columns[0], drop=True, append=False, inplace=True)

        if len(df.index) < 1:
raise ValueError("Taxonomy format requires at least one row of data.")

        if df.index.has_duplicates:
            raise ValueError(
"Taxonomy format feature IDs must be unique. The following IDs " "are duplicated: %s" % ', '.join(df.index.get_duplicates()))

        if df.columns.has_duplicates:
            raise ValueError(
"Taxonomy format column names must be unique. The following "
                "column names are duplicated: %s" %
>               ', '.join(df.columns.get_duplicates()))
E           AttributeError: 'Index' object has no attribute 'get_duplicates'

q2_types/feature_data/_transformer.py:89: AttributeError
______________ TestTaxonomyFormatsToDataFrame.test_duplicate_ids _______________

self = <q2_types.feature_data.tests.test_transformer.TestTaxonomyFormatsToDataFrame testMethod=test_duplicate_ids>

    def test_duplicate_ids(self):
        with self.assertRaisesRegex(ValueError, 'duplicated: SEQUENCE1'):
            _taxonomy_formats_to_dataframe(
                self.get_data_path(os.path.join(
>                   'taxonomy', 'duplicate-ids.tsv')))

q2_types/feature_data/tests/test_transformer.py:349:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    def _taxonomy_formats_to_dataframe(filepath, has_header=None):
        """Read any of the three taxonomy formats into a dataframe.

        Parameters
        ----------
        filepath : str
            The taxonomy-formatted file to be read.
        has_header : bool, optional
If `None`, autodetect the header: only `Feature ID<tab>Taxon` is recognized, optionally followed by other columns. If `True`, the file must have the expected header described above otherwise an error is
            raised. If `False`, the file is read without assuming a header.

        Returns
        -------
        pd.DataFrame
            Dataframe containing parsed contents of the taxonomy file. The
dataframe will have its index name set to `Feature ID` and its first column will be `Taxon`, followed by any other columns in the input
            file.

        """
# Using `dtype=object` and `set_index()` to avoid type casting/inference of
        # any columns or the index.
        df = pd.read_csv(filepath, sep='\t', skip_blank_lines=True,
                         header=None, dtype=object)

        if len(df.columns) < 2:
            raise ValueError(
                "Taxonomy format requires at least two columns, found %d."
                % len(df.columns))

        if has_header and not _has_expected_header(df):
            raise ValueError(
"Taxonomy format requires a header with `Feature ID` and `Taxon` "
                "as the first two columns.")

        if has_header or (has_header is None and _has_expected_header(df)):
            # Make first row the header:
            #     https://stackoverflow.com/a/26147330/3776794
            df.columns = df.iloc[0]
            df.columns.name = None
            df = df.reindex(df.index.drop(0))
        else:
            # No header
            unnamed_columns = ['Unnamed Column %d' % (i + 1)
                               for i in range(len(df.columns[2:]))]
            df.columns = TSVTaxonomyFormat.HEADER + unnamed_columns

        df.set_index(df.columns[0], drop=True, append=False, inplace=True)

        if len(df.index) < 1:
raise ValueError("Taxonomy format requires at least one row of data.")

        if df.index.has_duplicates:
            raise ValueError(
"Taxonomy format feature IDs must be unique. The following IDs " > "are duplicated: %s" % ', '.join(df.index.get_duplicates()))
E           AttributeError: 'Index' object has no attribute 'get_duplicates'

q2_types/feature_data/_transformer.py:83: AttributeError
__________________ TestTaxonomyFormatsToDataFrame.test_jagged __________________

self = <q2_types.feature_data.tests.test_transformer.TestTaxonomyFormatsToDataFrame testMethod=test_jagged>

    def test_jagged(self):
>       with self.assertRaises(pandas.io.common.CParserError):
E AttributeError: module 'pandas.io.common' has no attribute 'CParserError'

q2_types/feature_data/tests/test_transformer.py:341: AttributeError
___________ TestDataFrameToTSVTaxonomyFormat.test_duplicate_columns ____________

self = <q2_types.feature_data.tests.test_transformer.TestDataFrameToTSVTaxonomyFormat testMethod=test_duplicate_columns>

    def test_duplicate_columns(self):
        index = pd.Index(['seq1', 'seq2'], name='Feature ID', dtype=object)
        columns = ['Taxon', 'Taxon']
        df = pd.DataFrame([['abc', 'def'], ['ghi', 'jkl']], index=index,
                          columns=columns, dtype=object)

        with self.assertRaisesRegex(ValueError, "duplicated: Taxon"):
>           _dataframe_to_tsv_taxonomy_format(df)

q2_types/feature_data/tests/test_transformer.py:497:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    def _dataframe_to_tsv_taxonomy_format(df):
        if len(df.index) < 1:
raise ValueError("Taxonomy format requires at least one row of data.")

        if len(df.columns) < 1:
            raise ValueError(
                "Taxonomy format requires at least one column of data.")

        if df.index.name != 'Feature ID':
            raise ValueError(
                "Taxonomy format requires the dataframe index name to be "
                "`Feature ID`, found %r" % df.index.name)

        if df.columns[0] != 'Taxon':
            raise ValueError(
"Taxonomy format requires the first column name to be `Taxon`, "
                "found %r" % df.columns[0])

        if df.index.has_duplicates:
            raise ValueError(
"Taxonomy format feature IDs must be unique. The following IDs " "are duplicated: %s" % ', '.join(df.index.get_duplicates()))

        if df.columns.has_duplicates:
            raise ValueError(
"Taxonomy format column names must be unique. The following "
                "column names are duplicated: %s" %
>               ', '.join(df.columns.get_duplicates()))
E           AttributeError: 'Index' object has no attribute 'get_duplicates'

q2_types/feature_data/_transformer.py:126: AttributeError
_____________ TestDataFrameToTSVTaxonomyFormat.test_duplicate_ids ______________

self = <q2_types.feature_data.tests.test_transformer.TestDataFrameToTSVTaxonomyFormat testMethod=test_duplicate_ids>

    def test_duplicate_ids(self):
        index = pd.Index(['seq1', 'seq2', 'seq1'], name='Feature ID',
                         dtype=object)
        columns = ['Taxon']
        df = pd.DataFrame([['abc'], ['def'], ['ghi']], index=index,
                          columns=columns, dtype=object)

        with self.assertRaisesRegex(ValueError, "duplicated: seq1"):
>           _dataframe_to_tsv_taxonomy_format(df)

q2_types/feature_data/tests/test_transformer.py:488:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

    def _dataframe_to_tsv_taxonomy_format(df):
        if len(df.index) < 1:
raise ValueError("Taxonomy format requires at least one row of data.")

        if len(df.columns) < 1:
            raise ValueError(
                "Taxonomy format requires at least one column of data.")

        if df.index.name != 'Feature ID':
            raise ValueError(
                "Taxonomy format requires the dataframe index name to be "
                "`Feature ID`, found %r" % df.index.name)

        if df.columns[0] != 'Taxon':
            raise ValueError(
"Taxonomy format requires the first column name to be `Taxon`, "
                "found %r" % df.columns[0])

        if df.index.has_duplicates:
            raise ValueError(
"Taxonomy format feature IDs must be unique. The following IDs " > "are duplicated: %s" % ', '.join(df.index.get_duplicates()))
E           AttributeError: 'Index' object has no attribute 'get_duplicates'

q2_types/feature_data/_transformer.py:120: AttributeError

--- End Message ---
--- Begin Message ---
Source: q2-types
Source-Version: 2020.11.0-1
Done: =?utf-8?q?=C3=89tienne_Mollier?= <[email protected]>

We believe that the bug you reported is fixed in the latest version of
q2-types, which is due to be installed in the Debian FTP archive.

A summary of the changes between this version and the previous one is
attached.

Thank you for reporting the bug, which will now be closed.  If you
have further comments please address them to [email protected],
and the maintainer will reopen the bug report if appropriate.

Debian distribution maintenance software
pp.
Étienne Mollier <[email protected]> (supplier of updated q2-types 
package)

(This message was generated automatically at their request; if you
believe that there is a problem with it please contact the archive
administrators by mailing [email protected])


-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA256

Format: 1.8
Date: Tue, 01 Dec 2020 22:34:10 +0100
Source: q2-types
Architecture: source
Version: 2020.11.0-1
Distribution: unstable
Urgency: medium
Maintainer: Debian Med Packaging Team 
<[email protected]>
Changed-By: Étienne Mollier <[email protected]>
Closes: 950932
Changes:
 q2-types (2020.11.0-1) unstable; urgency=medium
 .
   * Team upload.
   * New upstream version (Closes: #950932)
   * Standards-Version: 4.5.1 (routine-update)
   * debhelper-compat 13 (routine-update)
   * Add salsa-ci file (routine-update)
   * Rules-Requires-Root: no (routine-update)
   * Suppressed build time test in favor of autopkgtest, temporarily hopefully.
     This is due to the Qiime plugin mechanism not being fully available before
     installation, but needed to run the test suite.
   * Lintian override national-encoding on test data.
   * Updated dependency to qiime (>= 2020.11.0)
   * Cleaning egg-info files
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