import datetime
|
from io import BytesIO
|
import re
|
from warnings import catch_warnings
|
|
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:
|
with catch_warnings(record=True):
|
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.randn(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.randn(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.randn(10, 1))
|
df2 = DataFrame({"a": np.random.randn(10)})
|
df3 = DataFrame({(1, 2): np.random.randn(10)})
|
df4 = DataFrame({("1", 2): np.random.randn(10)})
|
df5 = DataFrame({("1", 2, object): np.random.randn(10)})
|
|
with ensure_clean_store(setup_path) as store:
|
name = f"df_{tm.rands(10)}"
|
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.rand(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.rand(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)
|
