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* PyArrow native S3 filesystem * add sse-s3 tests * update * minor * ENABLE_SSE_S3 * Update test_pyarrow_native_s3.py * clean up * refactoring * Update test_pyarrow_native_s3.py
42 lines
1.2 KiB
Python
42 lines
1.2 KiB
Python
"""
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Shared utility functions for PyArrow Parquet tests.
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This module provides common test utilities used across multiple test scripts
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to avoid code duplication and ensure consistency.
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"""
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import pyarrow as pa
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def create_sample_table(num_rows: int = 5) -> pa.Table:
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"""Create a sample PyArrow table for testing.
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Args:
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num_rows: Number of rows to generate (default: 5)
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Returns:
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PyArrow Table with test data containing:
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- id: int64 sequential IDs (0 to num_rows-1)
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- name: string user names (user_0, user_1, ...)
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- value: float64 values (id * 1.5)
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- flag: bool alternating True/False based on even/odd id
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Example:
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>>> table = create_sample_table(3)
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>>> print(table)
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pyarrow.Table
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id: int64
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name: string
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value: double
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flag: bool
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"""
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return pa.table(
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{
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"id": pa.array(range(num_rows), type=pa.int64()),
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"name": pa.array([f"user_{i}" for i in range(num_rows)], type=pa.string()),
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"value": pa.array([float(i) * 1.5 for i in range(num_rows)], type=pa.float64()),
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"flag": pa.array([i % 2 == 0 for i in range(num_rows)], type=pa.bool_()),
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}
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)
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