Highly opinionated logging configurator

pip install uberlogging==0.7.0


Uberlogging - Python logging the way I like it

Highly opinionated wrapper/configuration around structlog and stdlib logger.

Python 3.7+ only. To use contextvar, minimum Python 3.7.1 is required.


Every project starts with burden of logging configuration. We want colors for interactive debugging, plain text in local dev when redirecting to file, and JSON when running in production with central log collection system. Finally, I like structlog, but most of the libraries do not use it, so I need to configure both libraries in compatible way.

This library does exactly that - configures logging as described above. It does it both for structlog and standard library logging.


Yes it is, since it merely configures great tools written by other great people to behave the way I personally prefer.

For instance, I prefer not to render structlog's key/val arguments as separate attributes in JSON output, since I find it much more convenient to read them as part of the text message, even in centralized logging UIs such as Graylog - processing them as separate fields will require me to enable million field columns, since each log message has its own context; and I don't use logs, but metrics for broader analysis.


import uberlogging

That's all. You are ready to go. Simply import structlog or stdlib logging, create your logger and start writing your app.

import structlog
logger = structlog.get_logger("main")
logger.info("Rocky road", to="Dublin")

Define UBERLOGGING_FORCE_TEXT=1 environment variable to force text output in non-tty streams. Useful for local environments when running your app with output redirection.


Structlog's context (key/value pairs passed to logging call) is rendered as <key1>=<value1> <key2>=<value2> (or empty string otherwise) and is available as {context} formatting variable. If non empty it will be 4-space padded (yes, it's not generic, but I find it very convenient with the default configuration).

If you employ contextvars, they will be rendered similarly and available as {contextvars}} formatting variable. Similarly, it's either single or 4-space padded depending whether exists non-empty structlog context for the current log record. See dedicated section on contextvars below.

Envrionment overrides

Sometimes people want things their own way and that's without changing actual code. To address that uberlogging provides ability to control some of its configuration though environment variables:

Define to non-empty value to force textual (not JSON) output. Colouring is autodetected
Same as above, but with with colours always enabled
Same as above, but with with colours always disabled
String that overrides logging message format. E.g. "{asctime} {levelname} {message}. Note that only "{" styles are supported.

Contextual logging

Structlogs's logger.bind(request_id="foo") is great for simple things but when you have multi-layer request handling, passing the same instance of bound logger is a). cumbersome and b). requires the same logger to be used by everything that handles the request.

I've long missed log4cxx Nested Diagnostic Contexts in Python and now with contextvars we can finally achieve that. The best part is that it works both in threaded and asyncio code!

If you never heard of contextvars, please read official documentation. In the nutshell it "kinda" replaces thread local storage and is natively supported in asyncio, i.e. it's both thread-safe and concurrent safe.

To employ contextvars in uberlogging you need to:

  • Create a contextvar somewhere in your code
  • Pass this context var to uberlogging.configure()
  • Set contextvar values whenever your like and all subsequent log messages will have its value rendered as part of the contextvar extra section

Here is an example:

import asyncio
from contextvars import ContextVar

import structlog
import uberlogging

ctx_request_id: ContextVar = ContextVar("request_id")
logger = structlog.get_logger(__name__)

async def handle_request(request_id: str) -> None:
    logger.info("Handling request")  # Will produce "Handling request    request_id=<request_id>

async def server():
    logger.info("Main server handling two requests")
    t1 = asyncio.create_task(handle_request("Zf1glE"))
    t2 = asyncio.create_task(handle_request("YcEf73"))
    await asyncio.wait((t1, t2))
    logger.info("Main server done")

if __name__ == "__main__":

This code will produce the following:

2019-10-07T13:41:17.669 __main__        INFO    ## Main server handling two requests   ctx.server:17
2019-10-07T13:41:17.669 __main__        INFO    ## Handling request    request_id='Zf1glE'    ctx.handle_request:13
2019-10-07T13:41:17.669 __main__        INFO    ## Handling request    request_id='YcEf73'    ctx.handle_request:13
2019-10-07T13:41:17.669 __main__        INFO    ## Main server done    ctx.server:21

Note that logger invocations inside the request handler do not mention any request_id - it's injected by logging formatter from the context.

Where are tests?

No tests, only deadlines :) Seriously though, there is demo.sh script that's good enough for now, since this library is not going to see much of a development.


echo 'layout pipenv' > .envrc
direnv allow  # will take a while
make bootstrap