jsonlog 4.0.0

JSON formatter for the builtin logging module

jsonlog

A drop-in formatter for Python's logging module that outputs messages as line delimited JSON.

While jsonlog provides it's own basicConfig method so you can get started quickly, all of it's features and classes can be used with the logging module.

Usage

You can use jsonlog as a drop-in replacement for logging:

import jsonlog

jsonlog.warning("Hello world.")

{"timestamp": "2019-06-21T19:06:25.285730", "level": "WARNING", "name": "root", "message": "Hello world."}

It's implemented as a log formatter, so you can use logging just like you normally would.

import jsonlog
import logging

jsonlog.basicConfig(level=jsonlog.INFO)
jsonlog.warning("Works with functions in the jsonlog module.")
logging.warning("And works with functions in the logging module.")

Configuration using jsonlog.basicConfig

The jsonlog.basicConfig function accepts slightly different parameters to logging.basicConfig. It's shown here with the defaults for each parameter.

The filename, filemode and stream parameters work the same way as their equivalents in logging.basicConfig, and as such filename and stream are exclusive.

import jsonlog

jsonlog.basicConfig(
    level=jsonlog.INFO,
    indent=None,
    keys=("timestamp", "level", "message"),
    timespec="auto",
    # filename=None,
    # filemode="a",
    # stream=None,
)

Configuration using logging.config.dictConfig

Any of the configuration methods in logging.config can be used to configure a handler that uses jsonlog.formmatters.JSONFormatter to format records as JSON.

import logging.config

logging.config.dictConfig(
    {
        "version": 1,
        "formatters": {"json": {"()": "jsonlog.JSONFormatter"}},
        "handlers": {"stream": {"class": "logging.StreamHandler", "formatter": "json"}},
        "loggers": {"": {"handlers": ["stream"]}},
    }
)

Adding extra attributes to JSON output

Record attributes provided with extra= will be included in the JSON object.

import jsonlog
import logging

jsonlog.basicConfig()
logging.warning("User clicked a button", extra={"user": 123})

{"timestamp": "2019-06-21T19:06:54.293929", "level": "WARNING", "name": "root", "message": "User clicked a button", "user": 123}

If a mapping is passed as the only positional argument, attributes from the mapping will also be included.

import jsonlog
import logging

jsonlog.basicConfig()
logging.warning("User clicked a button", {"user": 123})

Pipelining

Try piping logs through jq if you want to read them on the command line!

python examples/hello.py 2> >(jq .)

{
  "timestamp": "2019-06-21T19:07:43.211782",
  "level": "WARNING",
  "name": "root",
  "message": "Hello world."
}

Tracebacks

Tracebacks are included as a single string - it's not very nice to read, but means it'll play nicely with any systems that read the JSON logs you output.

{"timestamp": "2019-06-21T19:08:37.326897", "level": "ERROR", "name": "root", "message": "Encountered an error", "traceback": "Traceback (most recent call last):\n  File \"examples/error.py\", line 6, in <module>\n    raise ValueError(\"Example exception\")\nValueError: Example exception"}

Tools like jq make it easy to extract and read the traceback:

python examples/error.py 2> >(jq -r ".traceback")

Traceback (most recent call last):
  File "examples/error.py", line 6, in <module>
    raise ValueError("Example exception")
ValueError: Example exception

Compatibility

jsonlog is written for Python 3.7 and above. Compatibility patches will be accepted for Python 3.5 and above, but patches for Python 2 will be rejected.

To use jsonlog on Python 3.6 you will need to install the dataclasses package alongside it. This isn't a dependency as it breaks the builtin dataclasses module when installed on Python 3.7 and above.

References

• Build for use with the logging module.
• Partially based on colorlog.
• Works great with jq!

Authors

• Sam Clements