code: def test_parquet_1_0_roundtrip(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,
              "str": [str(x) for x in range(size)],
              "str_with_nulls": [None]
              + [str(x) for x in range(size - 2)]
              + [None],
              "empty_str": [""] * size,
          }
      )
      filename = tempdir / "pandas_roundtrip.parquet"
      arrow_table = pa.Table.from_pandas(df)
      _write_table(arrow_table, filename, version="1.0")
      table_read = _read_table(filename)
      df_read = table_read.to_pandas()
  
      # We pass uint32_t as int64_t if we write Parquet version 1.0
      df["uint32"] = df["uint32"].values.astype(np.int64)
  
      tm.assert_frame_equal(df, df_read)
  
imports: import decimal
  import io
  import numpy
  import pytest
  import pyarrow
  from pyarrow.tests import util
  from pyarrow.tests.parquet.common import _check_roundtrip
label_desc: Use image node_id 2 for calling a global function with example usage: test_parquet_1_0_roundtrip(tempdir) without return types