log_method_calls¶

A context manager to log method calls.

All method calls will be logged by default. This behavior can be overriden by passing filtering functions.

Parameters¶

class_condition

Type → typing.Callable[[typing.Any], bool] | None

Default → None

A function which determines if a class should be logged or not.
method_condition

Type → typing.Callable[[typing.Any], bool] | None

Default → None

A function which determines if a method should be logged or not.

Examples¶

import io
import logging
from river import anomaly
from river import compose
from river import datasets
from river import preprocessing
from river import utils

model = compose.Pipeline(
    preprocessing.MinMaxScaler(),
    anomaly.HalfSpaceTrees(seed=42)
)

class_condition = lambda x: x.__class__.__name__ in ('MinMaxScaler', 'HalfSpaceTrees')

logger = logging.getLogger()
logger.setLevel(logging.DEBUG)

logs = io.StringIO()
sh = logging.StreamHandler(logs)
sh.setLevel(logging.DEBUG)
logger.addHandler(sh)

with utils.log_method_calls(class_condition):
    for x, y in datasets.CreditCard().take(1):
        score = model.score_one(x)
        model = model.learn_one(x)

print(logs.getvalue())

MinMaxScaler.learn_one
MinMaxScaler.transform_one
HalfSpaceTrees.score_one
MinMaxScaler.transform_one
HalfSpaceTrees.learn_one

logs.close()