Eliminating warnings from scikit-learn [duplicate]

Question

I would like to ignore warnings from all packages when I am teaching, but scikit-learn seems to work around the use of the warnings package to control this. For example:

with warnings.catch_warnings():     warnings.simplefilter("ignore")     from sklearn import preprocessing  /usr/local/lib/python3.5/site-packages/sklearn/utils/fixes.py:66: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() instead   if 'order' in inspect.getargspec(np.copy)[0]: /usr/local/lib/python3.5/site-packages/sklearn/utils/fixes.py:358: DeprecationWarning: inspect.getargspec() is deprecated, use inspect.signature() instead   if 'exist_ok' in inspect.getargspec(os.makedirs).args: 

Am I using this module incorrectly, or is sklearn doing something its not supposed to?

Answer 1

It annoys me to the extreme that sklearn forces warnings.

I started using this at the top of main.py:

def warn(*args, **kwargs):     pass import warnings warnings.warn = warn  #... import sklearn stuff... 

Answer 2

They have changed their warning policy in 2013. You can ignore warnings (also specific types) with something like this:

import warnings warnings.filterwarnings("ignore", category=DeprecationWarning) 

//EDIT: in the comments below, Reed Richards points out that the filterwarnings call needs to be in the file that calls the function that gives the warning. I hope this helps those who experienced problems with this solution.