code: def test_center_ljust_rjust_fillchar(any_string_dtype):
      if any_string_dtype == "string[pyarrow_numpy]":
          pytest.skip(
              "Arrow logic is different, "
              "see https://github.com/pandas-dev/pandas/pull/54533/files#r1299808126",
          )
      s = Series(
          ["a", "bb", "cccc", "ddddd", "eeeeee"], dtype=any_string_dtype
      )
  
      result = s.str.center(5, fillchar="X")
      expected = Series(
          ["XXaXX", "XXbbX", "Xcccc", "ddddd", "eeeeee"],
          dtype=any_string_dtype,
      )
      tm.assert_series_equal(result, expected)
      expected = np.array(
          [v.center(5, "X") for v in np.array(s)], dtype=np.object_
      )
      tm.assert_numpy_array_equal(
          np.array(result, dtype=np.object_), expected
      )
  
      result = s.str.ljust(5, fillchar="X")
      expected = Series(
          ["aXXXX", "bbXXX", "ccccX", "ddddd", "eeeeee"],
          dtype=any_string_dtype,
      )
      tm.assert_series_equal(result, expected)
      expected = np.array(
          [v.ljust(5, "X") for v in np.array(s)], dtype=np.object_
      )
      tm.assert_numpy_array_equal(
          np.array(result, dtype=np.object_), expected
      )
  
      result = s.str.rjust(5, fillchar="X")
      expected = Series(
          ["XXXXa", "XXXbb", "Xcccc", "ddddd", "eeeeee"],
          dtype=any_string_dtype,
      )
      tm.assert_series_equal(result, expected)
      expected = np.array(
          [v.rjust(5, "X") for v in np.array(s)], dtype=np.object_
      )
      tm.assert_numpy_array_equal(
          np.array(result, dtype=np.object_), expected
      )
  
imports: from datetime import datetime
  import operator
  import numpy
  import pytest
  from pandas import Series, _testing
label_desc: Use image node_id 18 for calling a global function with example usage: test_center_ljust_rjust_fillchar(any_string_dtype) without return types