def test_cached_data(self):
# GH 26565, GH26617
# Calling RangeIndex._data caches an int64 array of the same length at
# self._cached_data. This test checks whether _cached_data has been set
idx = RangeIndex(0, 100, 10)
assert idx._cached_data is None
repr(idx)
assert idx._cached_data is None
str(idx)
assert idx._cached_data is None
idx.get_loc(20)
assert idx._cached_data is None
90 in idx
assert idx._cached_data is None
91 in idx
assert idx._cached_data is None
idx.all()
assert idx._cached_data is None
idx.any()
assert idx._cached_data is None
idx.format()
assert idx._cache == {}
df = pd.DataFrame({"a": range(10)}, index=idx)
str(df)
assert idx._cache == {}
df.loc[50]
assert idx._cached_data is None
with pytest.raises(KeyError, match="51"):
df.loc[51]
assert idx._cached_data is None
df.loc[10:50]
assert idx._cached_data is None
df.iloc[5:10]
assert idx._cached_data is None
# actually calling idx._data
assert isinstance(idx._data, np.ndarray)
assert isinstance(idx._cached_data, np.ndarray)
def test_cache(self):
# GH 26565, GH26617, GH35432
# This test checks whether _cache has been set.
# Calling RangeIndex._cache["_data"] creates an int64 array of the same length
# as the RangeIndex and stores it in _cache.
idx = RangeIndex(0, 100, 10)
assert idx._cache == {}
repr(idx)
assert idx._cache == {}
str(idx)
assert idx._cache == {}
idx.get_loc(20)
assert idx._cache == {}
90 in idx # True
assert idx._cache == {}
91 in idx # False
assert idx._cache == {}
idx.all()
assert idx._cache == {}
idx.any()
assert idx._cache == {}
for _ in idx:
pass
assert idx._cache == {}
idx.format()
assert idx._cache == {}
df = pd.DataFrame({"a": range(10)}, index=idx)
str(df)
assert idx._cache == {}
df.loc[50]
assert idx._cache == {}
with pytest.raises(KeyError, match="51"):
df.loc[51]
assert idx._cache == {}
df.loc[10:50]
assert idx._cache == {}
df.iloc[5:10]
assert idx._cache == {}
# idx._cache should contain a _data entry after call to idx._data
idx._data
assert isinstance(idx._data, np.ndarray)
assert idx._data is idx._data # check cached value is reused
assert len(idx._cache) == 4
expected = np.arange(0, 100, 10, dtype="int64")
tm.assert_numpy_array_equal(idx._cache["_data"], expected)