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import datetime
from io import BytesIO
import re
import numpy as np
import pytest
from pandas import (
CategoricalIndex,
DataFrame,
HDFStore,
Index,
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 = 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),
)
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[ns]]")
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 = 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[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 = 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["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 = "|".join(
[
re.escape(
"Cannot serialize the column [datetime1]\nbecause its data "
"contents are not [string] but [date] object dtype"
),
re.escape("[date] is not implemented as a table column"),
]
)
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 = DataFrame(
np.random.default_rng(2).standard_normal((10, 4)),
columns=Index(list("ABCD"), dtype=object),
index=date_range("2000-01-01", periods=10, freq="B"),
)
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, key="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, key="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, key="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, key="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, key="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)
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