Python pyarrow.date64() Examples
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code examples of pyarrow.date64().
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Example #1
Source File: test_unischema.py From petastorm with Apache License 2.0 | 5 votes |
def test_arrow_schema_convertion(): fields = [ pa.field('string', pa.string()), pa.field('int8', pa.int8()), pa.field('int16', pa.int16()), pa.field('int32', pa.int32()), pa.field('int64', pa.int64()), pa.field('float', pa.float32()), pa.field('double', pa.float64()), pa.field('bool', pa.bool_(), False), pa.field('fixed_size_binary', pa.binary(10)), pa.field('variable_size_binary', pa.binary()), pa.field('decimal', pa.decimal128(3, 4)), pa.field('timestamp_s', pa.timestamp('s')), pa.field('timestamp_ns', pa.timestamp('ns')), pa.field('date_32', pa.date32()), pa.field('date_64', pa.date64()) ] arrow_schema = pa.schema(fields) mock_dataset = _mock_parquet_dataset([], arrow_schema) unischema = Unischema.from_arrow_schema(mock_dataset) for name in arrow_schema.names: assert getattr(unischema, name).name == name assert getattr(unischema, name).codec is None if name == 'bool': assert not getattr(unischema, name).nullable else: assert getattr(unischema, name).nullable # Test schema preserve fields order field_name_list = [f.name for f in fields] assert list(unischema.fields.keys()) == field_name_list
Example #2
Source File: test_pandas_extension.py From fletcher with MIT License | 5 votes |
def test_combine_add(self, data_repeated, dtype): if dtype.name in [ "fletcher_chunked[date64[ms]]", "fletcher_continuous[date64[ms]]", ]: pytest.skip( "unsupported operand type(s) for +: 'datetime.date' and 'datetime.date" ) else: BaseMethodsTests.test_combine_add(self, data_repeated)
Example #3
Source File: parquet_pio.py From sdc with BSD 2-Clause "Simplified" License | 5 votes |
def _get_numba_typ_from_pa_typ(pa_typ): import pyarrow as pa _typ_map = { # boolean pa.bool_(): types.bool_, # signed int types pa.int8(): types.int8, pa.int16(): types.int16, pa.int32(): types.int32, pa.int64(): types.int64, # unsigned int types pa.uint8(): types.uint8, pa.uint16(): types.uint16, pa.uint32(): types.uint32, pa.uint64(): types.uint64, # float types (TODO: float16?) pa.float32(): types.float32, pa.float64(): types.float64, # String pa.string(): string_type, # date pa.date32(): types.NPDatetime('ns'), pa.date64(): types.NPDatetime('ns'), # time (TODO: time32, time64, ...) pa.timestamp('ns'): types.NPDatetime('ns'), pa.timestamp('us'): types.NPDatetime('ns'), pa.timestamp('ms'): types.NPDatetime('ns'), pa.timestamp('s'): types.NPDatetime('ns'), } if pa_typ not in _typ_map: raise ValueError("Arrow data type {} not supported yet".format(pa_typ)) return _typ_map[pa_typ]