Repository navigation
[Bug]: matplotlib.set_loglevel() adds a console handler #23646
Description
Bug summary
matplotlib.set_loglevel() adds a logging console handler which then leads to duplicate messages in application code. The best practice is to allow the application code to add the handlers to its logger along with formatting, filtering, etc. The existing #13264 attempted to address this.
Code for reproduction
import logging
import matplotlib as mpl
mpl_logger = logging.getLogger("matplotlib")
mpl.set_loglevel("debug")
mpl_logger.hasHandlers()
logger = logging.getLogger()
ch = logging.StreamHandler()
logger.addHandler(ch)
logger.setLevel(logging.DEBUG)
import matplotlib.pyplot as pltActual outcome
True
DEBUG:matplotlib:CACHEDIR=C:\Users\ljohnsto.matplotlib
CACHEDIR=C:\Users\ljohnsto.matplotlib
DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\ljohnsto.matplotlib\fontlist-v330.json
Using fontManager instance from C:\Users\ljohnsto.matplotlib\fontlist-v330.json
Expected outcome
False
CACHEDIR=C:\Users\ljohnsto.matplotlib
Using fontManager instance from C:\Users\ljohnsto.matplotlib\fontlist-v330.json
Additional information
The workaround is:
In [1]: import logging
In [2]: import matplotlib as mpl
In [3]: mpl_logger = logging.getLogger("matplotlib")
In [4]: mpl.set_loglevel("debug")
In [5]: mpl_logger_handlers = mpl_logger.handlers.copy()
In [6]: for h in mpl_logger_handlers:
...: mpl_logger.removeHandler(h)
...:
In [7]: logger = logging.getLogger()
In [8]: ch = logging.StreamHandler()
In [9]: logger.addHandler(ch)
In [10]: logger.setLevel(logging.DEBUG)
In [11]: import matplotlib.pyplot as plt
CACHEDIR=C:\Users\ljohnsto\.matplotlib
Using fontManager instance from C:\Users\ljohnsto\.matplotlib\fontlist-v330.json
'''
### Operating system
Windows
### Matplotlib Version
3.5.2
### Matplotlib Backend
TkAgg
### Python version
3.9.13
### Jupyter version
_No response_
### Installation
pip
Activity
jklymak commentedon Aug 17, 2022
Yes agreed. But set_loglevel is meant to be a helper for endusers (eg our application) versus for downstream applications. Set matplotlibs log levels using the logging library if you have a downstream application.
l-johnston commentedon Aug 19, 2022
@jklymak
logging. So, I thought I had to opt-in to get logging information through this function call.matplotlibrepresents the library andmatplotlib.pyplotrepresents the application - is this correct?jklymak commentedon Aug 19, 2022
A link to the standard logging library would make sense. I don't really see the point of a deprecation cycle for the top-level set_loglevel - it is already also exposed as
pyplot.set_loglevel.tacaswell commentedon Aug 19, 2022
fair, will open a PR to fix that. I'm also thinking about adding a keyword arguement to opt-opt of us trying to install a handler.
We have not articulated in so many words, but this seems right. Historically the distinction has been a bit fuzzy, but we are slowly pushing things towards this state.
tacaswell commentedon Oct 20, 2022
xref #23681 (comment)