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
Release files for avilabs-ml-metrics 1.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| avilabs-ml-metrics-1.1.0.tar.gz | 4.1 kB | Details |
Release files / avilabs-ml-metrics-1.1.0.tar.gz
| Download URL | avilabs-ml-metrics-1.1.0.tar.gz |
|---|---|
| Size | 4.1 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
2645bd0f5adb44267acf2609839673ea91f0e4dfb177773183121200dd21c587
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twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.2
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