code: def test_append_raise(setup_path):
      with ensure_clean_store(setup_path) as store:
          # test append with invalid input to get good error messages
  
          # list in column
          df = DataFrame(
              1.1 * np.arange(120).reshape((30, 4)),
              columns=Index(list("ABCD"), dtype=object),
              index=Index([f"i-{i}" for i in range(30)], dtype=object),
          )
          df["invalid"] = [["a"]] * len(df)
          assert df.dtypes["invalid"] == np.object_
          msg = re.escape(
              """Cannot serialize the column [invalid]
  because its data contents are not [string] but [mixed] object dtype"""
          )
          with pytest.raises(TypeError, match=msg):
              store.append("df", df)
  
          # multiple invalid columns
          df["invalid2"] = [["a"]] * len(df)
          df["invalid3"] = [["a"]] * len(df)
          with pytest.raises(TypeError, match=msg):
              store.append("df", df)
  
          # datetime with embedded nans as object
          df = DataFrame(
              1.1 * np.arange(120).reshape((30, 4)),
              columns=Index(list("ABCD"), dtype=object),
              index=Index([f"i-{i}" for i in range(30)], dtype=object),
          )
          s = Series(datetime.datetime(2001, 1, 2), index=df.index)
          s = s.astype(object)
          s[0:5] = np.nan
          df["invalid"] = s
          assert df.dtypes["invalid"] == np.object_
          msg = "too many timezones in this block, create separate data columns"
          with pytest.raises(TypeError, match=msg):
              store.append("df", df)
  
          # directly ndarray
          msg = "value must be None, Series, or DataFrame"
          with pytest.raises(TypeError, match=msg):
              store.append("df", np.arange(10))
  
          # series directly
          msg = re.escape(
              "cannot properly create the storer for: "
              "[group->df,value-><class 'pandas.core.series.Series'>]"
          )
          with pytest.raises(TypeError, match=msg):
              store.append("df", Series(np.arange(10)))
  
          # appending an incompatible table
          df = DataFrame(
              1.1 * np.arange(120).reshape((30, 4)),
              columns=Index(list("ABCD"), dtype=object),
              index=Index([f"i-{i}" for i in range(30)], dtype=object),
          )
          store.append("df", df)
  
          df["foo"] = "foo"
          msg = re.escape(
              "invalid combination of [non_index_axes] on appending data "
              "[(1, ['A', 'B', 'C', 'D', 'foo'])] vs current table "
              "[(1, ['A', 'B', 'C', 'D'])]"
          )
          with pytest.raises(ValueError, match=msg):
              store.append("df", df)
  
          # incompatible type (GH 41897)
          _maybe_remove(store, "df")
          df["foo"] = Timestamp("20130101")
          store.append("df", df)
          df["foo"] = "bar"
          msg = re.escape(
              "invalid combination of [values_axes] on appending data "
              "[name->values_block_1,cname->values_block_1,"
              "dtype->bytes24,kind->string,shape->(1, 30)] "
              "vs current table "
              "[name->values_block_1,cname->values_block_1,"
              "dtype->datetime64[s],kind->datetime64[s],shape->None]"
          )
          with pytest.raises(ValueError, match=msg):
              store.append("df", df)
  
imports: import datetime
  from datetime import timedelta
  import re
  import numpy
  import pytest
  from pandas._libs.tslibs import Timestamp
  import pandas
  from pandas import DataFrame, Index, Series, _testing, concat, date_range, read_hdf
  from pandas.tests.io.pytables.common import _maybe_remove, ensure_clean_store
label_desc: Use image node_id 14 for calling a global function with example usage: test_append_raise(setup_path) without return types