code: def test_repr(dtype):
      df = pd.DataFrame({"A": pd.array(["a", pd.NA, "b"], dtype=dtype)})
      if dtype.storage == "pyarrow_numpy":
          expected = "     A\n0    a\n1  NaN\n2    b"
      else:
          expected = "      A\n0     a\n1  <NA>\n2     b"
      assert repr(df) == expected
  
      if dtype.storage == "pyarrow_numpy":
          expected = (
              "0      a\n1    NaN\n2      b\nName: A, dtype: string"
          )
      else:
          expected = (
              "0       a\n1    <NA>\n2       b\nName: A, dtype: string"
          )
      assert repr(df.A) == expected
  
      if dtype.storage == "pyarrow":
          arr_name = "ArrowStringArray"
          expected = f"<{arr_name}>\n['a', <NA>, 'b']\nLength: 3, dtype: string"
      elif dtype.storage == "pyarrow_numpy":
          arr_name = "ArrowStringArrayNumpySemantics"
          expected = (
              f"<{arr_name}>\n['a', nan, 'b']\nLength: 3, dtype: string"
          )
      else:
          arr_name = "StringArray"
          expected = f"<{arr_name}>\n['a', <NA>, 'b']\nLength: 3, dtype: string"
      assert repr(df.A.array) == expected
  
imports: import operator
  import numpy
  import pytest
  from pandas.compat.pyarrow import pa_version_under12p0
  from pandas.core.dtypes.common import is_dtype_equal
  import pandas
  import pandas._testing
  from pandas.core.arrays.string_arrow import ArrowStringArray, ArrowStringArrayNumpySemantics
label_desc: Use image node_id 4 for calling a global function with example usage: test_repr(dtype) without return types