There are a number of answers on this website detailing how one can ignore specific warnings in python (either by category or by providing a regex to match a warning message).
However, none of these seem to work when I try try to suppress PerformanceWarnings coming from PyTables.
Here's an MWE:
import pandas as pd
import warnings
from tables import NaturalNameWarning, PerformanceWarning
data = {
'a' : 1,
'b' : 'two'
}
df = pd.DataFrame.from_dict(data, orient = 'index') # mixed types will trigger PerformanceWarning
dest = pd.HDFStore('warnings.h5', 'w')
#dest.put('data', df) # mixed type will produce a PerformanceWarning
#dest.put('data 1', df) # space in 'data 1' will trigger NaturalNameWarning in addition to the PerformanceWarning
warnings.filterwarnings('ignore', category = NaturalNameWarning) # NaturalNameWarnings ignored
warnings.filterwarnings('ignore', category = PerformanceWarning) # no effect
warnings.filterwarnings('ignore', message='.*PyTables will pickle') # no effect
#warnings.filterwarnings('ignore') # kills all warnings, not what I want
dest.put('data 2', df) # PerformanceWarning
dest.close()
Using a context manager doesn't help either:
with warnings.catch_warnings():
warnings.filterwarnings("ignore", category=PerformanceWarning) # no effect
warnings.filterwarnings('ignore', message='.*PyTables') # no effect
dest.put('data 6', df)
Nor does using warnings.simplefilter() instead of warnings.filterwarnings().
Perhaps relevant, here is the PerformanceWarning:
test.py:21: PerformanceWarning:
your performance may suffer as PyTables will pickle object types that it cannot
map directly to c-types [inferred_type->mixed-integer,key->block0_values] [items->Int64Index([0], dtype='int64')]
dest.put('data 2', df) # PerformanceWarning
Contrast this with the NaturalNameWarning, which doesn't come from the offending line in test.py, but from tables/path.py:
/home/user/.local/lib/python3.8/site-packages/tables/path.py:137: NaturalNameWarning: object name is not a valid Python identifier: 'data 2'; it does not match the pattern ``^[a-zA-Z_][a-zA-Z0-9_]*$``; you will not be able to use natural naming to access this object; using ``getattr()`` will still work, though
check_attribute_name(name)
This is with tables 3.7.0/python 3.8.10. Any ideas?
This may be confusing but the
PerformanceWarningis not emitted by thetablespackage but bypandas:Try:
Example:
Only the
NaturalNameWarningshould remain in the above example.