code: def test_append(setup_path):
      with ensure_clean_store(setup_path) as store:
          # this is allowed by almost always don't want to do it
          # tables.NaturalNameWarning):
          df = DataFrame(
              np.random.default_rng(2).standard_normal((20, 4)),
              columns=Index(list("ABCD"), dtype=object),
              index=date_range("2000-01-01", periods=20, freq="B"),
          )
          _maybe_remove(store, "df1")
          store.append("df1", df[:10])
          store.append("df1", df[10:])
          tm.assert_frame_equal(store["df1"], df)
  
          _maybe_remove(store, "df2")
          store.put("df2", df[:10], format="table")
          store.append("df2", df[10:])
          tm.assert_frame_equal(store["df2"], df)
  
          _maybe_remove(store, "df3")
          store.append("/df3", df[:10])
          store.append("/df3", df[10:])
          tm.assert_frame_equal(store["df3"], df)
  
          # this is allowed by almost always don't want to do it
          # tables.NaturalNameWarning
          _maybe_remove(store, "/df3 foo")
          store.append("/df3 foo", df[:10])
          store.append("/df3 foo", df[10:])
          tm.assert_frame_equal(store["df3 foo"], df)
  
          # dtype issues - mizxed type in a single object column
          df = DataFrame(data=[[1, 2], [0, 1], [1, 2], [0, 0]])
          df["mixed_column"] = "testing"
          df.loc[2, "mixed_column"] = np.nan
          _maybe_remove(store, "df")
          store.append("df", df)
          tm.assert_frame_equal(store["df"], df)
  
          # uints - test storage of uints
          uint_data = DataFrame(
              {
                  "u08": Series(
                      np.random.default_rng(2).integers(
                          0, high=255, size=5
                      ),
                      dtype=np.uint8,
                  ),
                  "u16": Series(
                      np.random.default_rng(2).integers(
                          0, high=65535, size=5
                      ),
                      dtype=np.uint16,
                  ),
                  "u32": Series(
                      np.random.default_rng(2).integers(
                          0, high=2**30, size=5
                      ),
                      dtype=np.uint32,
                  ),
                  "u64": Series(
                      [2**58, 2**59, 2**60, 2**61, 2**62],
                      dtype=np.uint64,
                  ),
              },
              index=np.arange(5),
          )
          _maybe_remove(store, "uints")
          store.append("uints", uint_data)
          tm.assert_frame_equal(
              store["uints"], uint_data, check_index_type=True
          )
  
          # uints - test storage of uints in indexable columns
          _maybe_remove(store, "uints")
          # 64-bit indices not yet supported
          store.append(
              "uints", uint_data, data_columns=["u08", "u16", "u32"]
          )
          tm.assert_frame_equal(
              store["uints"], uint_data, check_index_type=True
          )
  
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 1 for calling a global function with example usage: test_append(setup_path) without return types