[python-h5netcdf] 04/06: merge patched into master

Ghislain Vaillant ghisvail-guest at moszumanska.debian.org
Sat Jan 14 18:57:08 UTC 2017


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ghisvail-guest pushed a commit to branch master
in repository python-h5netcdf.

commit af6cbc457c51dc9243d3c46b9521e6854c5ada7f
Merge: fdc8d9b 1768652
Author: Ghislain Antony Vaillant <ghisvail at gmail.com>
Date:   Sat Jan 14 12:05:12 2017 +0000

    merge patched into master

 debian/.git-dpm                                  |   4 +-
 debian/patches/0001-Add-missing-test-suite.patch | 533 +++++++++++++++++++++++
 debian/patches/series                            |   1 +
 h5netcdf/tests/test_h5netcdf.py                  | 517 ++++++++++++++++++++++
 4 files changed, 1053 insertions(+), 2 deletions(-)

diff --cc debian/.git-dpm
index 41507fb,0000000..b6468f0
mode 100644,000000..100644
--- a/debian/.git-dpm
+++ b/debian/.git-dpm
@@@ -1,11 -1,0 +1,11 @@@
 +# see git-dpm(1) from git-dpm package
- 8327ac208e171ed2aa3a0fddfe8d09e5ae94006e
- 8327ac208e171ed2aa3a0fddfe8d09e5ae94006e
++1768652ff6e94492572286ecdd8108ec460a4b9f
++1768652ff6e94492572286ecdd8108ec460a4b9f
 +8327ac208e171ed2aa3a0fddfe8d09e5ae94006e
 +8327ac208e171ed2aa3a0fddfe8d09e5ae94006e
 +python-h5netcdf_0.3.1.orig.tar.gz
 +fd63ae25cec094ad76acb9519e37c7d1a2e6d30b
 +11252
 +debianTag="debian/%e%v"
 +patchedTag="patched/%e%v"
 +upstreamTag="upstream/%e%u"
diff --cc debian/patches/0001-Add-missing-test-suite.patch
index 0000000,0000000..d7a2a8e
new file mode 100644
--- /dev/null
+++ b/debian/patches/0001-Add-missing-test-suite.patch
@@@ -1,0 -1,0 +1,533 @@@
++From 1768652ff6e94492572286ecdd8108ec460a4b9f Mon Sep 17 00:00:00 2001
++From: Ghislain Antony Vaillant <ghisvail at gmail.com>
++Date: Sat, 14 Jan 2017 12:05:00 +0000
++Subject: Add missing test suite
++
++---
++ h5netcdf/tests/test_h5netcdf.py | 517 ++++++++++++++++++++++++++++++++++++++++
++ 1 file changed, 517 insertions(+)
++ create mode 100644 h5netcdf/tests/test_h5netcdf.py
++
++diff --git a/h5netcdf/tests/test_h5netcdf.py b/h5netcdf/tests/test_h5netcdf.py
++new file mode 100644
++index 0000000..07b5269
++--- /dev/null
+++++ b/h5netcdf/tests/test_h5netcdf.py
++@@ -0,0 +1,517 @@
+++import netCDF4
+++import numpy as np
+++import sys
+++import gc
+++
+++import h5netcdf
+++from h5netcdf import legacyapi
+++from h5netcdf.compat import PY2, unicode
+++import h5py
+++import pytest
+++
+++from pytest import fixture, raises
+++
+++
+++ at pytest.fixture
+++def tmp_netcdf(tmpdir):
+++    return str(tmpdir.join('testfile.nc'))
+++
+++
+++def string_to_char(arr):
+++    """Like nc4.stringtochar, but faster and more flexible.
+++    """
+++    # ensure the array is contiguous
+++    arr = np.array(arr, copy=False, order='C')
+++    kind = arr.dtype.kind
+++    if kind not in ['U', 'S']:
+++        raise ValueError('argument must be a string')
+++    return arr.reshape(arr.shape + (1,)).view(kind + '1')
+++
+++
+++def array_equal(a, b):
+++    a, b = map(np.array, (a[...], b[...]))
+++    if a.shape != b.shape:
+++        return False
+++    try:
+++        return np.allclose(a, b)
+++    except TypeError:
+++        return (a == b).all()
+++
+++
+++_char_array = string_to_char(np.array(['a', 'b', 'c', 'foo', 'bar', 'baz'],
+++                                      dtype='S'))
+++
+++_string_array = np.array([['foobar0', 'foobar1', 'foobar3'],
+++                          ['foofoofoo', 'foofoobar', 'foobarbar']])
+++
+++def is_h5py_char_working(tmp_netcdf, name):
+++    # https://github.com/Unidata/netcdf-c/issues/298
+++    with h5py.File(tmp_netcdf, 'r') as ds:
+++        v = ds[name]
+++        try:
+++            assert array_equal(v, _char_array)
+++            return True
+++        except Exception as e:
+++            if e.args[0] == "Can't read data (No appropriate function for conversion path)":
+++                return False
+++            else:
+++                raise
+++
+++def write_legacy_netcdf(tmp_netcdf, write_module):
+++    ds = write_module.Dataset(tmp_netcdf, 'w')
+++    ds.setncattr('global', 42)
+++    ds.other_attr = 'yes'
+++    ds.createDimension('x', 4)
+++    ds.createDimension('y', 5)
+++    ds.createDimension('z', 6)
+++    ds.createDimension('empty', 0)
+++    ds.createDimension('string3', 3)
+++
+++    v = ds.createVariable('foo', float, ('x', 'y'), chunksizes=(4, 5),
+++                          zlib=True)
+++    v[...] = 1
+++    v.setncattr('units', 'meters')
+++
+++    v = ds.createVariable('y', int, ('y',), fill_value=-1)
+++    v[:4] = np.arange(4)
+++
+++    v = ds.createVariable('z', 'S1', ('z', 'string3'), fill_value=b'X')
+++    v[...] = _char_array
+++
+++    v = ds.createVariable('scalar', np.float32, ())
+++    v[...] = 2.0
+++
+++    # test creating a scalar with compression option (with should be ignored)
+++    v = ds.createVariable('intscalar', np.int64, (), zlib=6, fill_value=None)
+++    v[...] = 2
+++
+++    with raises(TypeError):
+++        ds.createVariable('boolean', np.bool_, ('x'))
+++
+++    g = ds.createGroup('subgroup')
+++    v = g.createVariable('subvar', np.int32, ('x',))
+++    v[...] = np.arange(4.0)
+++
+++    g.createDimension('y', 10)
+++    g.createVariable('y_var', float, ('y',))
+++
+++    ds.createDimension('mismatched_dim', 1)
+++    ds.createVariable('mismatched_dim', int, ())
+++
+++    v = ds.createVariable('var_len_str', str, ('x'))
+++    v[0] = u'foo'
+++
+++    ds.close()
+++
+++
+++def write_h5netcdf(tmp_netcdf):
+++    ds = h5netcdf.File(tmp_netcdf, 'w')
+++    ds.attrs['global'] = 42
+++    ds.attrs['other_attr'] = 'yes'
+++    ds.dimensions = {'x': 4, 'y': 5, 'z': 6, 'empty': 0}
+++
+++    v = ds.create_variable('foo', ('x', 'y'), float, chunks=(4, 5),
+++                           compression='gzip', shuffle=True)
+++    v[...] = 1
+++    v.attrs['units'] = 'meters'
+++
+++    v = ds.create_variable('y', ('y',), int, fillvalue=-1)
+++    v[:4] = np.arange(4)
+++
+++    v = ds.create_variable('z', ('z', 'string3'), data=_char_array,
+++                           fillvalue=b'X')
+++
+++    v = ds.create_variable('scalar', data=np.float32(2.0))
+++
+++    v = ds.create_variable('intscalar', data=np.int64(2))
+++
+++    with raises(TypeError):
+++        ds.create_variable('boolean', data=True)
+++
+++    g = ds.create_group('subgroup')
+++    v = g.create_variable('subvar', ('x',), np.int32)
+++    v[...] = np.arange(4.0)
+++    with raises(AttributeError):
+++        v.attrs['_Netcdf4Dimid'] = -1
+++
+++    g.dimensions['y'] = 10
+++    g.create_variable('y_var', ('y',), float)
+++    g.flush()
+++
+++    ds.dimensions['mismatched_dim'] = 1
+++    ds.create_variable('mismatched_dim', dtype=int)
+++    ds.flush()
+++
+++    dt = h5py.special_dtype(vlen=unicode)
+++    v = ds.create_variable('var_len_str', ('x',), dtype=dt)
+++    v[0] = u'foo'
+++
+++    ds.close()
+++
+++
+++def read_legacy_netcdf(tmp_netcdf, read_module, write_module):
+++    ds = read_module.Dataset(tmp_netcdf, 'r')
+++    assert ds.ncattrs() == ['global', 'other_attr']
+++    assert ds.getncattr('global') == 42
+++    if not PY2 and write_module is not netCDF4:
+++        # skip for now: https://github.com/Unidata/netcdf4-python/issues/388
+++        assert ds.other_attr == 'yes'
+++    assert set(ds.dimensions) == set(['x', 'y', 'z', 'empty', 'string3',
+++                                      'mismatched_dim'])
+++    assert set(ds.variables) == set(['foo', 'y', 'z', 'intscalar', 'scalar',
+++                                     'var_len_str', 'mismatched_dim'])
+++    assert set(ds.groups) == set(['subgroup'])
+++    assert ds.parent is None
+++
+++    v = ds.variables['foo']
+++    assert array_equal(v, np.ones((4, 5)))
+++    assert v.dtype == float
+++    assert v.dimensions == ('x', 'y')
+++    assert v.ndim == 2
+++    assert v.ncattrs() == ['units']
+++    if not PY2 and write_module is not netCDF4:
+++        assert v.getncattr('units') == 'meters'
+++    assert tuple(v.chunking()) == (4, 5)
+++    assert v.filters() == {'complevel': 4, 'fletcher32': False,
+++                           'shuffle': True, 'zlib': True}
+++
+++    v = ds.variables['y']
+++    assert array_equal(v, np.r_[np.arange(4), [-1]])
+++    assert v.dtype == int
+++    assert v.dimensions == ('y',)
+++    assert v.ndim == 1
+++    assert v.ncattrs() == ['_FillValue']
+++    assert v.getncattr('_FillValue') == -1
+++    assert v.chunking() == 'contiguous'
+++    assert v.filters() == {'complevel': 0, 'fletcher32': False,
+++                           'shuffle': False, 'zlib': False}
+++    ds.close()
+++
+++    #Check the behavior if h5py. Cannot expect h5netcdf to overcome these errors:
+++    if is_h5py_char_working(tmp_netcdf, 'z'):
+++        ds = read_module.Dataset(tmp_netcdf, 'r')
+++        v = ds.variables['z']
+++        assert array_equal(v, _char_array)
+++        assert v.dtype == 'S1'
+++        assert v.ndim == 2
+++        assert v.dimensions == ('z', 'string3')
+++        assert v.ncattrs() == ['_FillValue']
+++        assert v.getncattr('_FillValue') == b'X'
+++    else:
+++        ds = read_module.Dataset(tmp_netcdf, 'r')
+++
+++    v = ds.variables['scalar']
+++    assert array_equal(v, np.array(2.0))
+++    assert v.dtype == 'float32'
+++    assert v.ndim == 0
+++    assert v.dimensions == ()
+++    assert v.ncattrs() == []
+++
+++    v = ds.variables['intscalar']
+++    assert array_equal(v, np.array(2))
+++    assert v.dtype == 'int64'
+++    assert v.ndim == 0
+++    assert v.dimensions == ()
+++    assert v.ncattrs() == []
+++
+++    v = ds.variables['var_len_str']
+++    assert v.dtype == str
+++    assert v[0] == u'foo'
+++
+++    v = ds.groups['subgroup'].variables['subvar']
+++    assert ds.groups['subgroup'].parent is ds
+++    assert array_equal(v, np.arange(4.0))
+++    assert v.dtype == 'int32'
+++    assert v.ndim == 1
+++    assert v.dimensions == ('x',)
+++    assert v.ncattrs() == []
+++
+++    v = ds.groups['subgroup'].variables['y_var']
+++    assert v.shape == (10,)
+++    assert 'y' in ds.groups['subgroup'].dimensions
+++
+++    ds.close()
+++
+++
+++def read_h5netcdf(tmp_netcdf, write_module):
+++    ds = h5netcdf.File(tmp_netcdf, 'r')
+++    assert ds.name == '/'
+++    assert list(ds.attrs) == ['global', 'other_attr']
+++    assert ds.attrs['global'] == 42
+++    if not PY2 and write_module is not netCDF4:
+++        # skip for now: https://github.com/Unidata/netcdf4-python/issues/388
+++        assert ds.attrs['other_attr'] == 'yes'
+++    assert set(ds.dimensions) == set(['x', 'y', 'z', 'empty', 'string3', 'mismatched_dim'])
+++    assert set(ds.variables) == set(['foo', 'y', 'z', 'intscalar', 'scalar',
+++                                     'var_len_str', 'mismatched_dim'])
+++    assert set(ds.groups) == set(['subgroup'])
+++    assert ds.parent is None
+++
+++    v = ds['foo']
+++    assert v.name == '/foo'
+++    assert array_equal(v, np.ones((4, 5)))
+++    assert v.dtype == float
+++    assert v.dimensions == ('x', 'y')
+++    assert v.ndim == 2
+++    assert list(v.attrs) == ['units']
+++    if not PY2 and write_module is not netCDF4:
+++        assert v.attrs['units'] == 'meters'
+++    assert v.chunks == (4, 5)
+++    assert v.compression == 'gzip'
+++    assert v.compression_opts == 4
+++    assert not v.fletcher32
+++    assert v.shuffle
+++
+++    v = ds['y']
+++    assert array_equal(v, np.r_[np.arange(4), [-1]])
+++    assert v.dtype == int
+++    assert v.dimensions == ('y',)
+++    assert v.ndim == 1
+++    assert list(v.attrs) == ['_FillValue']
+++    assert v.attrs['_FillValue'] == -1
+++    assert v.chunks == None
+++    assert v.compression == None
+++    assert v.compression_opts == None
+++    assert not v.fletcher32
+++    assert not v.shuffle
+++    ds.close()
+++
+++    if is_h5py_char_working(tmp_netcdf, 'z'):
+++        ds = h5netcdf.File(tmp_netcdf, 'r')
+++        v = ds['z']
+++        assert v.dtype == 'S1'
+++        assert v.ndim == 2
+++        assert v.dimensions == ('z', 'string3')
+++        assert list(v.attrs) == ['_FillValue']
+++        assert v.attrs['_FillValue'] == b'X'
+++    else:
+++        ds = h5netcdf.File(tmp_netcdf, 'r')
+++
+++    v = ds['scalar']
+++    assert array_equal(v, np.array(2.0))
+++    assert v.dtype == 'float32'
+++    assert v.ndim == 0
+++    assert v.dimensions == ()
+++    assert list(v.attrs) == []
+++
+++    v = ds.variables['intscalar']
+++    assert array_equal(v, np.array(2))
+++    assert v.dtype == 'int64'
+++    assert v.ndim == 0
+++    assert v.dimensions == ()
+++    assert list(v.attrs) == []
+++
+++    v = ds['var_len_str']
+++    assert h5py.check_dtype(vlen=v.dtype) == unicode
+++    assert v[0] == u'foo'
+++
+++    v = ds['/subgroup/subvar']
+++    assert v is ds['subgroup']['subvar']
+++    assert v is ds['subgroup/subvar']
+++    assert v is ds['subgroup']['/subgroup/subvar']
+++    assert v.name == '/subgroup/subvar'
+++    assert ds['subgroup'].name == '/subgroup'
+++    assert ds['subgroup'].parent is ds
+++    assert array_equal(v, np.arange(4.0))
+++    assert v.dtype == 'int32'
+++    assert v.ndim == 1
+++    assert v.dimensions == ('x',)
+++    assert list(v.attrs) == []
+++
+++    assert ds['/subgroup/y_var'].shape == (10,)
+++    assert ds['/subgroup'].dimensions['y'] == 10
+++
+++    ds.close()
+++
+++
+++def roundtrip_legacy_netcdf(tmp_netcdf, read_module, write_module):
+++    write_legacy_netcdf(tmp_netcdf, write_module)
+++    read_legacy_netcdf(tmp_netcdf, read_module, write_module)
+++
+++
+++def test_write_legacyapi_read_netCDF4(tmp_netcdf):
+++    roundtrip_legacy_netcdf(tmp_netcdf, netCDF4, legacyapi)
+++
+++
+++def test_roundtrip_h5netcdf_legacyapi(tmp_netcdf):
+++    roundtrip_legacy_netcdf(tmp_netcdf, legacyapi, legacyapi)
+++
+++
+++def test_write_netCDF4_read_legacyapi(tmp_netcdf):
+++    roundtrip_legacy_netcdf(tmp_netcdf, legacyapi, netCDF4)
+++
+++
+++def test_write_h5netcdf_read_legacyapi(tmp_netcdf):
+++    write_h5netcdf(tmp_netcdf)
+++    read_legacy_netcdf(tmp_netcdf, legacyapi, h5netcdf)
+++
+++
+++def test_write_h5netcdf_read_netCDF4(tmp_netcdf):
+++    write_h5netcdf(tmp_netcdf)
+++    read_legacy_netcdf(tmp_netcdf, netCDF4, h5netcdf)
+++
+++
+++def test_roundtrip_h5netcdf(tmp_netcdf):
+++    write_h5netcdf(tmp_netcdf)
+++    read_h5netcdf(tmp_netcdf, h5netcdf)
+++
+++
+++def test_write_netCDF4_read_h5netcdf(tmp_netcdf):
+++    write_legacy_netcdf(tmp_netcdf, netCDF4)
+++    read_h5netcdf(tmp_netcdf, netCDF4)
+++
+++
+++def test_write_legacyapi_read_h5netcdf(tmp_netcdf):
+++    write_legacy_netcdf(tmp_netcdf, legacyapi)
+++    read_h5netcdf(tmp_netcdf, legacyapi)
+++
+++
+++def test_repr(tmp_netcdf):
+++    write_h5netcdf(tmp_netcdf)
+++    f = h5netcdf.File(tmp_netcdf, 'r')
+++    assert 'h5netcdf.File' in repr(f)
+++    assert 'subgroup' in repr(f)
+++    assert 'foo' in repr(f)
+++    assert 'other_attr' in repr(f)
+++
+++    assert 'h5netcdf.attrs.Attributes' in repr(f.attrs)
+++    assert 'global' in repr(f.attrs)
+++
+++    d = f.dimensions
+++    assert 'h5netcdf.Dimensions' in repr(d)
+++    assert 'x=4' in repr(d)
+++
+++    g = f['subgroup']
+++    assert 'h5netcdf.Group' in repr(g)
+++    assert 'subvar' in repr(g)
+++
+++    v = f['foo']
+++    assert 'h5netcdf.Variable' in repr(v)
+++    assert 'float' in repr(v)
+++    assert 'units' in repr(v)
+++    f.close()
+++
+++    assert 'Closed' in repr(f)
+++    assert 'Closed' in repr(d)
+++    assert 'Closed' in repr(g)
+++    assert 'Closed' in repr(v)
+++
+++
+++def test_attrs_api(tmp_netcdf):
+++    with h5netcdf.File(tmp_netcdf) as ds:
+++        ds.attrs['conventions'] = 'CF'
+++        ds.dimensions['x'] = 1
+++        v = ds.create_variable('x', ('x',), 'i4')
+++        v.attrs.update({'units': 'meters', 'foo': 'bar'})
+++    assert ds._closed
+++    with h5netcdf.File(tmp_netcdf) as ds:
+++        assert len(ds.attrs) == 1
+++        assert dict(ds.attrs) == {'conventions': 'CF'}
+++        assert list(ds.attrs) == ['conventions']
+++        assert dict(ds['x'].attrs) == {'units': 'meters', 'foo': 'bar'}
+++        assert len(ds['x'].attrs) == 2
+++        assert sorted(ds['x'].attrs) == ['foo', 'units']
+++
+++
+++def test_optional_netcdf4_attrs(tmp_netcdf):
+++    with h5py.File(tmp_netcdf) as f:
+++        foo_data = np.arange(50).reshape(5, 10)
+++        f.create_dataset('foo', data=foo_data)
+++        f.create_dataset('x', data=np.arange(5))
+++        f.create_dataset('y', data=np.arange(10))
+++        f['foo'].dims.create_scale(f['x'])
+++        f['foo'].dims.create_scale(f['y'])
+++        f['foo'].dims[0].attach_scale(f['x'])
+++        f['foo'].dims[1].attach_scale(f['y'])
+++    with h5netcdf.File(tmp_netcdf, 'r') as ds:
+++        assert ds['foo'].dimensions == ('x', 'y')
+++        assert ds.dimensions == {'x': 5, 'y': 10}
+++        assert array_equal(ds['foo'], foo_data)
+++
+++
+++def test_error_handling(tmp_netcdf):
+++    with h5netcdf.File(tmp_netcdf, 'w') as ds:
+++        with raises(NotImplementedError):
+++            ds.dimensions['x'] = None
+++        ds.dimensions['x'] = 1
+++        with raises(ValueError):
+++            ds.dimensions['x'] = 2
+++        with raises(ValueError):
+++            ds.dimensions = {'x': 2}
+++        with raises(ValueError):
+++            ds.dimensions = {'y': 3}
+++        ds.create_variable('x', ('x',), dtype=float)
+++        with raises(ValueError):
+++            ds.create_variable('x', ('x',), dtype=float)
+++        ds.create_group('subgroup')
+++        with raises(ValueError):
+++            ds.create_group('subgroup')
+++
+++
+++def test_invalid_netcdf4(tmp_netcdf):
+++    with h5py.File(tmp_netcdf) as f:
+++        f.create_dataset('foo', data=np.arange(5))
+++        # labeled dimensions but no dimension scales
+++        f['foo'].dims[0].label = 'x'
+++    with h5netcdf.File(tmp_netcdf, 'r') as ds:
+++        with raises(ValueError):
+++            ds.variables['foo'].dimensions
+++
+++
+++def test_hierarchical_access_auto_create(tmp_netcdf):
+++    ds = h5netcdf.File(tmp_netcdf, 'w')
+++    ds.create_variable('/foo/bar', data=1)
+++    g = ds.create_group('foo/baz')
+++    g.create_variable('/foo/hello', data=2)
+++    assert set(ds) == set(['foo'])
+++    assert set(ds['foo']) == set(['bar', 'baz', 'hello'])
+++    ds.close()
+++
+++    ds = h5netcdf.File(tmp_netcdf, 'r')
+++    assert set(ds) == set(['foo'])
+++    assert set(ds['foo']) == set(['bar', 'baz', 'hello'])
+++    ds.close()
+++
+++def test_reading_str_array_from_netCDF4(tmp_netcdf):
+++    # This tests reading string variables created by netCDF4
+++    with netCDF4.Dataset(tmp_netcdf, 'w') as ds:
+++        ds.createDimension('foo1', _string_array.shape[0])
+++        ds.createDimension('foo2', _string_array.shape[1])
+++        ds.createVariable('bar', str, ('foo1', 'foo2'))
+++        ds.variables['bar'][:] = _string_array
+++
+++    ds = h5netcdf.File(tmp_netcdf, 'r')
+++
+++    v = ds.variables['bar']
+++    assert array_equal(v, _string_array)
+++    ds.close()
+++
+++def test_nc_properties(tmp_netcdf):
+++    with h5netcdf.File(tmp_netcdf, 'w') as ds:
+++        pass
+++    with h5py.File(tmp_netcdf, 'r') as f:
+++        assert 'h5netcdf' in f.attrs['_NCProperties']
+++
+++def test_failed_read_open_and_clean_delete(tmpdir):
+++    # A file that does not exist but is opened for
+++    # reading should only raise an IOError and
+++    # no AttributeError at garbage collection.
+++    path = str(tmpdir.join('this_file_does_not_exist.nc'))
+++    try:
+++        with h5netcdf.File(path, 'r') as ds:
+++            pass
+++    except IOError:
+++        pass
+++
+++    # Look at garbage collection:
+++    # A simple gc.collect() does not raise an exception.
+++    # Must seek the File object and imitate its del command
+++    # by forcing it to close.
+++    obj_list = gc.get_objects()
+++    for obj in obj_list:
+++        try:
+++            is_h5netcdf_File = isinstance(obj, h5netcdf.File)
+++        except AttributeError as e:
+++            is_h5netcdf_File = False
+++        if is_h5netcdf_File:
+++            obj.close()
diff --cc debian/patches/series
index 0000000,0000000..c20898e
new file mode 100644
--- /dev/null
+++ b/debian/patches/series
@@@ -1,0 -1,0 +1,1 @@@
++0001-Add-missing-test-suite.patch

-- 
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