code: def test_pandas_parquet_configuration_options(tempdir):
      size = 10000
      np.random.seed(0)
      df = pd.DataFrame(
          {
              "uint8": np.arange(size, dtype=np.uint8),
              "uint16": np.arange(size, dtype=np.uint16),
              "uint32": np.arange(size, dtype=np.uint32),
              "uint64": np.arange(size, dtype=np.uint64),
              "int8": np.arange(size, dtype=np.int16),
              "int16": np.arange(size, dtype=np.int16),
              "int32": np.arange(size, dtype=np.int32),
              "int64": np.arange(size, dtype=np.int64),
              "float32": np.arange(size, dtype=np.float32),
              "float64": np.arange(size, dtype=np.float64),
              "bool": np.random.randn(size) > 0,
          }
      )
      filename = tempdir / "pandas_roundtrip.parquet"
      arrow_table = pa.Table.from_pandas(df)
  
      for use_dictionary in [True, False]:
          _write_table(
              arrow_table,
              filename,
              version="2.6",
              use_dictionary=use_dictionary,
          )
          table_read = _read_table(filename)
          df_read = table_read.to_pandas()
          tm.assert_frame_equal(df, df_read)
  
      for write_statistics in [True, False]:
          _write_table(
              arrow_table,
              filename,
              version="2.6",
              write_statistics=write_statistics,
          )
          table_read = _read_table(filename)
          df_read = table_read.to_pandas()
          tm.assert_frame_equal(df, df_read)
  
      for compression in ["NONE", "SNAPPY", "GZIP", "LZ4", "ZSTD"]:
          if compression != "NONE" and not pa.lib.Codec.is_available(
              compression
          ):
              continue
          _write_table(
              arrow_table,
              filename,
              version="2.6",
              compression=compression,
          )
          table_read = _read_table(filename)
          df_read = table_read.to_pandas()
          tm.assert_frame_equal(df, df_read)
  
imports: import io
  import json
  import numpy
  import pytest
  import pyarrow
  from pyarrow.fs import LocalFileSystem, SubTreeFileSystem
  from pyarrow.util import guid
  from pyarrow.vendored.version import Version
label_desc: Use image node_id 10 for calling a global function with example usage: test_pandas_parquet_configuration_options(tempdir) without return types