import datetime from io import BytesIO import re import numpy as np import pytest from pandas import ( CategoricalIndex, DataFrame, HDFStore, MultiIndex, _testing as tm, date_range, read_hdf, ) from pandas.tests.io.pytables.common import ensure_clean_store from pandas.io.pytables import ( Term, _maybe_adjust_name, ) pytestmark = pytest.mark.single_cpu def test_pass_spec_to_storer(setup_path): df = tm.makeDataFrame() with ensure_clean_store(setup_path) as store: store.put("df", df) msg = ( "cannot pass a column specification when reading a Fixed format " "store. this store must be selected in its entirety" ) with pytest.raises(TypeError, match=msg): store.select("df", columns=["A"]) msg = ( "cannot pass a where specification when reading from a Fixed " "format store. this store must be selected in its entirety" ) with pytest.raises(TypeError, match=msg): store.select("df", where=[("columns=A")]) def test_table_index_incompatible_dtypes(setup_path): df1 = DataFrame({"a": [1, 2, 3]}) df2 = DataFrame({"a": [4, 5, 6]}, index=date_range("1/1/2000", periods=3)) with ensure_clean_store(setup_path) as store: store.put("frame", df1, format="table") msg = re.escape("incompatible kind in col [integer - datetime64]") with pytest.raises(TypeError, match=msg): store.put("frame", df2, format="table", append=True) def test_unimplemented_dtypes_table_columns(setup_path): with ensure_clean_store(setup_path) as store: dtypes = [("date", datetime.date(2001, 1, 2))] # currently not supported dtypes #### for n, f in dtypes: df = tm.makeDataFrame() df[n] = f msg = re.escape(f"[{n}] is not implemented as a table column") with pytest.raises(TypeError, match=msg): store.append(f"df1_{n}", df) # frame df = tm.makeDataFrame() df["obj1"] = "foo" df["obj2"] = "bar" df["datetime1"] = datetime.date(2001, 1, 2) df = df._consolidate() with ensure_clean_store(setup_path) as store: # this fails because we have a date in the object block...... msg = re.escape( """Cannot serialize the column [datetime1] because its data contents are not [string] but [date] object dtype""" ) with pytest.raises(TypeError, match=msg): store.append("df_unimplemented", df) def test_invalid_terms(tmp_path, setup_path): with ensure_clean_store(setup_path) as store: df = tm.makeTimeDataFrame() df["string"] = "foo" df.loc[df.index[0:4], "string"] = "bar" store.put("df", df, format="table") # some invalid terms msg = re.escape("__init__() missing 1 required positional argument: 'where'") with pytest.raises(TypeError, match=msg): Term() # more invalid msg = re.escape( "cannot process expression [df.index[3]], " "[2000-01-06 00:00:00] is not a valid condition" ) with pytest.raises(ValueError, match=msg): store.select("df", "df.index[3]") msg = "invalid syntax" with pytest.raises(SyntaxError, match=msg): store.select("df", "index>") # from the docs path = tmp_path / setup_path dfq = DataFrame( np.random.default_rng(2).standard_normal((10, 4)), columns=list("ABCD"), index=date_range("20130101", periods=10), ) dfq.to_hdf(path, "dfq", format="table", data_columns=True) # check ok read_hdf(path, "dfq", where="index>Timestamp('20130104') & columns=['A', 'B']") read_hdf(path, "dfq", where="A>0 or C>0") # catch the invalid reference path = tmp_path / setup_path dfq = DataFrame( np.random.default_rng(2).standard_normal((10, 4)), columns=list("ABCD"), index=date_range("20130101", periods=10), ) dfq.to_hdf(path, "dfq", format="table") msg = ( r"The passed where expression: A>0 or C>0\n\s*" r"contains an invalid variable reference\n\s*" r"all of the variable references must be a reference to\n\s*" r"an axis \(e.g. 'index' or 'columns'\), or a data_column\n\s*" r"The currently defined references are: index,columns\n" ) with pytest.raises(ValueError, match=msg): read_hdf(path, "dfq", where="A>0 or C>0") def test_append_with_diff_col_name_types_raises_value_error(setup_path): df = DataFrame(np.random.default_rng(2).standard_normal((10, 1))) df2 = DataFrame({"a": np.random.default_rng(2).standard_normal(10)}) df3 = DataFrame({(1, 2): np.random.default_rng(2).standard_normal(10)}) df4 = DataFrame({("1", 2): np.random.default_rng(2).standard_normal(10)}) df5 = DataFrame({("1", 2, object): np.random.default_rng(2).standard_normal(10)}) with ensure_clean_store(setup_path) as store: name = "df_diff_valerror" store.append(name, df) for d in (df2, df3, df4, df5): msg = re.escape( "cannot match existing table structure for [0] on appending data" ) with pytest.raises(ValueError, match=msg): store.append(name, d) def test_invalid_complib(setup_path): df = DataFrame( np.random.default_rng(2).random((4, 5)), index=list("abcd"), columns=list("ABCDE"), ) with tm.ensure_clean(setup_path) as path: msg = r"complib only supports \[.*\] compression." with pytest.raises(ValueError, match=msg): df.to_hdf(path, "df", complib="foolib") @pytest.mark.parametrize( "idx", [ date_range("2019", freq="D", periods=3, tz="UTC"), CategoricalIndex(list("abc")), ], ) def test_to_hdf_multiindex_extension_dtype(idx, tmp_path, setup_path): # GH 7775 mi = MultiIndex.from_arrays([idx, idx]) df = DataFrame(0, index=mi, columns=["a"]) path = tmp_path / setup_path with pytest.raises(NotImplementedError, match="Saving a MultiIndex"): df.to_hdf(path, "df") def test_unsuppored_hdf_file_error(datapath): # GH 9539 data_path = datapath("io", "data", "legacy_hdf/incompatible_dataset.h5") message = ( r"Dataset\(s\) incompatible with Pandas data types, " "not table, or no datasets found in HDF5 file." ) with pytest.raises(ValueError, match=message): read_hdf(data_path) def test_read_hdf_errors(setup_path, tmp_path): df = DataFrame( np.random.default_rng(2).random((4, 5)), index=list("abcd"), columns=list("ABCDE"), ) path = tmp_path / setup_path msg = r"File [\S]* does not exist" with pytest.raises(OSError, match=msg): read_hdf(path, "key") df.to_hdf(path, "df") store = HDFStore(path, mode="r") store.close() msg = "The HDFStore must be open for reading." with pytest.raises(OSError, match=msg): read_hdf(store, "df") def test_read_hdf_generic_buffer_errors(): msg = "Support for generic buffers has not been implemented." with pytest.raises(NotImplementedError, match=msg): read_hdf(BytesIO(b""), "df") @pytest.mark.parametrize("bad_version", [(1, 2), (1,), [], "12", "123"]) def test_maybe_adjust_name_bad_version_raises(bad_version): msg = "Version is incorrect, expected sequence of 3 integers" with pytest.raises(ValueError, match=msg): _maybe_adjust_name("values_block_0", version=bad_version)