FM / tests

/usr/local/lib64/python3.6/site-packages/pyarrow/tests/

/usr/local/lib64/python3.6/site-packages/pyarrow/tests

Name	Size	Mode	Actions
data/	-	0755	rm
parquet/	-	0755	rm
__pycache__/	-	0755	rm
arrow_7980.py	1094	0644	edit dl rm
bound_function_visit_strings.pyx	2047	0644	edit dl rm
conftest.py	7982	0644	edit dl rm
deserialize_buffer.py	961	0644	edit dl rm
pandas_examples.py	5115	0644	edit dl rm
pandas_threaded_import.py	1429	0644	edit dl rm
pyarrow_cython_example.pyx	1951	0644	edit dl rm
strategies.py	12525	0644	edit dl rm
test_adhoc_memory_leak.py	1410	0644	edit dl rm
test_array.py	100157	0644	edit dl rm
test_builder.py	2184	0644	edit dl rm
test_cffi.py	13090	0644	edit dl rm
test_compute.py	83551	0644	edit dl rm
test_convert_builtin.py	71768	0644	edit dl rm
test_csv.py	68943	0644	edit dl rm
test_cuda.py	27863	0644	edit dl rm
test_cuda_numba_interop.py	8730	0644	edit dl rm
test_cython.py	5948	0644	edit dl rm
test_dataset.py	143023	0644	edit dl rm
test_deprecations.py	891	0644	edit dl rm
test_extension_type.py	24437	0644	edit dl rm
test_feather.py	23209	0644	edit dl rm
test_filesystem.py	2106	0644	edit dl rm
test_flight.py	73715	0644	edit dl rm
test_fs.py	54133	0644	edit dl rm
test_gandiva.py	14385	0644	edit dl rm
test_hdfs.py	13452	0644	edit dl rm
test_io.py	53066	0644	edit dl rm
test_ipc.py	31267	0644	edit dl rm
test_json.py	11325	0644	edit dl rm
test_jvm.py	15471	0644	edit dl rm
test_memory.py	4928	0644	edit dl rm
test_misc.py	4927	0644	edit dl rm
test_orc.py	9221	0644	edit dl rm
test_pandas.py	157909	0644	edit dl rm
test_plasma.py	44011	0644	edit dl rm
test_plasma_tf_op.py	3523	0644	edit dl rm
test_scalars.py	21074	0644	edit dl rm
test_schema.py	21282	0644	edit dl rm
test_serialization.py	42026	0644	edit dl rm
test_serialization_deprecated.py	1775	0644	edit dl rm
test_sparse_tensor.py	17436	0644	edit dl rm
test_strategies.py	1739	0644	edit dl rm
test_table.py	53168	0644	edit dl rm
test_tensor.py	6270	0644	edit dl rm
test_types.py	31487	0644	edit dl rm
test_util.py	1791	0644	edit dl rm
util.py	9011	0644	edit dl rm
__init__.py	0	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/pyarrow/tests/test_orc.py (9221B)

# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.

import pytest
import decimal
import datetime

import pyarrow as pa

# Marks all of the tests in this module
# Ignore these with pytest ... -m 'not orc'
pytestmark = pytest.mark.orc

try:
    from pandas.testing import assert_frame_equal
    import pandas as pd
except ImportError:
    pass

@pytest.fixture(scope="module")
def datadir(base_datadir):
    return base_datadir / "orc"

def fix_example_values(actual_cols, expected_cols):
    """
    Fix type of expected values (as read from JSON) according to
    actual ORC datatype.
    """
    for name in expected_cols:
        expected = expected_cols[name]
        actual = actual_cols[name]
        if (name == "map" and
                [d.keys() == {'key', 'value'} for m in expected for d in m]):
            # convert [{'key': k, 'value': v}, ...] to [(k, v), ...]
            for i, m in enumerate(expected):
                expected_cols[name][i] = [(d['key'], d['value']) for d in m]
            continue

typ = actual[0].__class__
        if issubclass(typ, datetime.datetime):
            # timestamp fields are represented as strings in JSON files
            expected = pd.to_datetime(expected)
        elif issubclass(typ, datetime.date):
            # date fields are represented as strings in JSON files
            expected = expected.dt.date
        elif typ is decimal.Decimal:
            converted_decimals = [None] * len(expected)
            # decimal fields are represented as reals in JSON files
            for i, (d, v) in enumerate(zip(actual, expected)):
                if not pd.isnull(v):
                    exp = d.as_tuple().exponent
                    factor = 10 ** -exp
                    converted_decimals[i] = (
                        decimal.Decimal(round(v * factor)).scaleb(exp))
            expected = pd.Series(converted_decimals)

expected_cols[name] = expected

def check_example_values(orc_df, expected_df, start=None, stop=None):
    if start is not None or stop is not None:
        expected_df = expected_df[start:stop].reset_index(drop=True)
    assert_frame_equal(orc_df, expected_df, check_dtype=False)

def check_example_file(orc_path, expected_df, need_fix=False):
    """
    Check a ORC file against the expected columns dictionary.
    """
    from pyarrow import orc

orc_file = orc.ORCFile(orc_path)
    # Exercise ORCFile.read()
    table = orc_file.read()
    assert isinstance(table, pa.Table)
    table.validate()

# This workaround needed because of ARROW-3080
    orc_df = pd.DataFrame(table.to_pydict())

assert set(expected_df.columns) == set(orc_df.columns)

# reorder columns if necessary
    if not orc_df.columns.equals(expected_df.columns):
        expected_df = expected_df.reindex(columns=orc_df.columns)

if need_fix:
        fix_example_values(orc_df, expected_df)

check_example_values(orc_df, expected_df)
    # Exercise ORCFile.read_stripe()
    json_pos = 0
    for i in range(orc_file.nstripes):
        batch = orc_file.read_stripe(i)
        check_example_values(pd.DataFrame(batch.to_pydict()),
                             expected_df,
                             start=json_pos,
                             stop=json_pos + len(batch))
        json_pos += len(batch)
    assert json_pos == orc_file.nrows

@pytest.mark.pandas
@pytest.mark.parametrize('filename', [
    'TestOrcFile.test1.orc',
    'TestOrcFile.testDate1900.orc',
    'decimal.orc'
])
def test_example_using_json(filename, datadir):
    """
    Check a ORC file example against the equivalent JSON file, as given
    in the Apache ORC repository (the JSON file has one JSON object per
    line, corresponding to one row in the ORC file).
    """
    # Read JSON file
    path = datadir / filename
    table = pd.read_json(str(path.with_suffix('.jsn.gz')), lines=True)
    check_example_file(path, table, need_fix=True)

def test_orcfile_empty(datadir):
    from pyarrow import orc

table = orc.ORCFile(datadir / "TestOrcFile.emptyFile.orc").read()
    assert table.num_rows == 0

expected_schema = pa.schema([
        ("boolean1", pa.bool_()),
        ("byte1", pa.int8()),
        ("short1", pa.int16()),
        ("int1", pa.int32()),
        ("long1", pa.int64()),
        ("float1", pa.float32()),
        ("double1", pa.float64()),
        ("bytes1", pa.binary()),
        ("string1", pa.string()),
        ("middle", pa.struct(
            [("list", pa.list_(
                pa.struct([("int1", pa.int32()),
                           ("string1", pa.string())])))
             ])),
        ("list", pa.list_(
            pa.struct([("int1", pa.int32()),
                       ("string1", pa.string())])
        )),
        ("map", pa.map_(pa.string(),
                        pa.struct([("int1", pa.int32()),
                                   ("string1", pa.string())])
                        )),
    ])
    assert table.schema == expected_schema

def test_orcfile_readwrite():
    from pyarrow import orc

buffer_output_stream = pa.BufferOutputStream()
    a = pa.array([1, None, 3, None])
    b = pa.array([None, "Arrow", None, "ORC"])
    table = pa.table({"int64": a, "utf8": b})
    orc.write_table(table, buffer_output_stream)
    buffer_reader = pa.BufferReader(buffer_output_stream.getvalue())
    orc_file = orc.ORCFile(buffer_reader)
    output_table = orc_file.read()
    assert table.equals(output_table)

# deprecated keyword order
    buffer_output_stream = pa.BufferOutputStream()
    with pytest.warns(FutureWarning):
        orc.write_table(buffer_output_stream, table)
    buffer_reader = pa.BufferReader(buffer_output_stream.getvalue())
    orc_file = orc.ORCFile(buffer_reader)
    output_table = orc_file.read()
    assert table.equals(output_table)

def test_column_selection(tempdir):
    from pyarrow import orc

# create a table with nested types
    inner = pa.field('inner', pa.int64())
    middle = pa.field('middle', pa.struct([inner]))
    fields = [
        pa.field('basic', pa.int32()),
        pa.field(
            'list', pa.list_(pa.field('item', pa.int32()))
        ),
        pa.field(
            'struct', pa.struct([middle, pa.field('inner2', pa.int64())])
        ),
        pa.field(
            'list-struct', pa.list_(pa.field(
                'item', pa.struct([
                    pa.field('inner1', pa.int64()),
                    pa.field('inner2', pa.int64())
                ])
            ))
        ),
        pa.field('basic2', pa.int64()),
    ]
    arrs = [
        [0], [[1, 2]], [{"middle": {"inner": 3}, "inner2": 4}],
        [[{"inner1": 5, "inner2": 6}, {"inner1": 7, "inner2": 8}]], [9]]
    table = pa.table(arrs, schema=pa.schema(fields))

path = str(tempdir / 'test.orc')
    orc.write_table(table, path)
    orc_file = orc.ORCFile(path)

# default selecting all columns
    result1 = orc_file.read()
    assert result1.equals(table)

# selecting with columns names
    result2 = orc_file.read(columns=["basic", "basic2"])
    assert result2.equals(table.select(["basic", "basic2"]))

result3 = orc_file.read(columns=["list", "struct", "basic2"])
    assert result3.equals(table.select(["list", "struct", "basic2"]))

# using dotted paths
    result4 = orc_file.read(columns=["struct.middle.inner"])
    expected4 = pa.table({"struct": [{"middle": {"inner": 3}}]})
    assert result4.equals(expected4)

result5 = orc_file.read(columns=["struct.inner2"])
    expected5 = pa.table({"struct": [{"inner2": 4}]})
    assert result5.equals(expected5)

result6 = orc_file.read(
        columns=["list", "struct.middle.inner", "struct.inner2"]
    )
    assert result6.equals(table.select(["list", "struct"]))

result7 = orc_file.read(columns=["list-struct.inner1"])
    expected7 = pa.table({"list-struct": [[{"inner1": 5}, {"inner1": 7}]]})
    assert result7.equals(expected7)

# selecting with (Arrow-based) field indices
    result2 = orc_file.read(columns=[0, 4])
    assert result2.equals(table.select(["basic", "basic2"]))

result3 = orc_file.read(columns=[1, 2, 3])
    assert result3.equals(table.select(["list", "struct", "list-struct"]))

# error on non-existing name or index
    with pytest.raises(IOError):
        # liborc returns ParseError, which gets translated into IOError
        # instead of ValueError
        orc_file.read(columns=["wrong"])

with pytest.raises(ValueError):
        orc_file.read(columns=[5])

cmd: