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34 | 34 |
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35 | 35 | def read_parquet(
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36 | 36 | path: str | pathlib.Path,
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37 |
| - table_partition_cols: list[tuple[str, pa.DataType]] | None = None, |
| 37 | + table_partition_cols: list[tuple[str, str | pa.DataType]] | None = None, |
38 | 38 | parquet_pruning: bool = True,
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39 | 39 | file_extension: str = ".parquet",
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40 | 40 | skip_metadata: bool = True,
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@@ -83,7 +83,7 @@ def read_json(
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83 | 83 | schema: pa.Schema | None = None,
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84 | 84 | schema_infer_max_records: int = 1000,
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85 | 85 | file_extension: str = ".json",
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86 |
| - table_partition_cols: list[tuple[str, pa.DataType]] | None = None, |
| 86 | + table_partition_cols: list[tuple[str, str | pa.DataType]] | None = None, |
87 | 87 | file_compression_type: str | None = None,
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88 | 88 | ) -> DataFrame:
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89 | 89 | """Read a line-delimited JSON data source.
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@@ -124,7 +124,7 @@ def read_csv(
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124 | 124 | delimiter: str = ",",
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125 | 125 | schema_infer_max_records: int = 1000,
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126 | 126 | file_extension: str = ".csv",
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127 |
| - table_partition_cols: list[tuple[str, pa.DataType]] | None = None, |
| 127 | + table_partition_cols: list[tuple[str, str | pa.DataType]] | None = None, |
128 | 128 | file_compression_type: str | None = None,
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129 | 129 | ) -> DataFrame:
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130 | 130 | """Read a CSV data source.
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@@ -171,7 +171,7 @@ def read_csv(
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171 | 171 | def read_avro(
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172 | 172 | path: str | pathlib.Path,
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173 | 173 | schema: pa.Schema | None = None,
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174 |
| - file_partition_cols: list[tuple[str, str]] | None = None, |
| 174 | + file_partition_cols: list[tuple[str, str | pa.DataType]] | None = None, |
175 | 175 | file_extension: str = ".avro",
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176 | 176 | ) -> DataFrame:
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177 | 177 | """Create a :py:class:`DataFrame` for reading Avro data source.
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