avilabs-ml-metrics 1.1.0

Metrics for Machine Learning

ML Metrics

A simple and flexible API to log metrics. Currently a metrics logger for logging to SQLite is implemented. Other backends can be implemented as needed.

Quickstart

Write Logs

from mlmetrics.sqlitemetrics.sqlite_metric import SqliteMetric

db = './metrics.db'
metric = SqliteMetric(db, name='fuel_gauge', labels={'model', 'trip'})
metric.log(model='toyota', trip='short', value=1.2)

Query Logs

from mlmetrics.sqlitemetrics.sqlite_metric import SqliteMetric

db = './metrics.db'
logs = metric.logs(start=1550554038.80172, end=1550554038.80265)
for row in logs:
    for fld in row.keys():
        print(fld, row[fld])

For more details see the Homepage