Python Logger#
You can use NeptuneHandler
to track logs from the Python Logger
.
Related
Logger
reference in the Python documentation
NeptuneHandler
#
A handler that sends the records created by the logger to Neptune.
Logs will be stored as a StringSeries
field.
Parameters
Name | Type | Default | Description |
---|---|---|---|
run |
Run , optional |
None |
An existing run reference, as returned by neptune.init_run() . |
level |
int , optional |
logging.NOTSET |
Log level of the logs to be captured by the handler. Defaults to logging.NOTSET , which captures all logs that match the logger level. |
path |
str , optional |
None |
Path to the StringSeries field used for captured logs. If None , tracked metadata will be stored under the monitoring namespace. |
Examples
Create a logger:
Create a Neptune run:
If Neptune can't find your project name or API token
As a best practice, you should save your Neptune API token and project name as environment variables:
export NEPTUNE_API_TOKEN="h0dHBzOi8aHR0cHM6Lkc78ghs74kl0jvYh3Kb8"
export NEPTUNE_PROJECT="ml-team/classification"
You can, however, also pass them as arguments when initializing Neptune:
run = neptune.init_run(
api_token="h0dHBzOi8aHR0cHM6Lkc78ghs74kl0jvYh3Kb8", # your token here
project="ml-team/classification", # your full project name here
)
- API token: In the bottom-left corner, expand the user menu and select Get my API token.
- Project name: in the top-right menu: → Edit project details.
If you haven't registered, you can also log anonymously to a public project (make sure not to publish sensitive data through your code!):
Create a NeptuneHandler object to capture the logs: