Loguru relies on a stub file to document its types. This implies that these types are not
accessible during execution of your program, however they can be used by type checkers and IDE.
Also, this means that your Python interpreter has to support postponed evaluation of annotations
to prevent error at runtime. This is achieved with a
__future__ import in Python 3.7+ or by using
string literals for earlier versions.
A basic usage example could look like this:
from __future__ import annotations import loguru from loguru import logger def good_sink(message: loguru.Message): print("My name is", message.record["name"]) def bad_filter(record: loguru.Record): return record["invalid"] logger.add(good_sink, filter=bad_filter)
$ mypy test.py test.py:8: error: TypedDict "Record" has no key 'invalid' Found 1 error in 1 file (checked 1 source file)
There are several internal types to which you can be exposed using Loguru’s public API, they are listed here and might be useful to type hint your code:
Logger: the usual
Loggerobject (also returned by
Message: the formatted logging message sent to the sinks (a
dictcontaining all contextual information of the logged message.
Catcher: the context decorator returned by
Contextualizer: the context decorator returned by
AwaitableCompleter: the awaitable object returned by
pip install loguru-mypy
It helps to catch several possible runtime errors by performing additional checks like:
opt(lazy=True)loggers accepting only
opt(record=True)loggers wrongly calling log handler like so
- and even more…
For more details, go to official documentation of
See also: Source code for type hints.