Adding context to log records
Project description
Python Logging Context
pylogctx is a library for enriching each logs records from a context. Typical usage is for adding some request_id to all logs in order to make troubleshooting more comfortable. This context is shared by all app using logging, transparently.
Usage
You have two options to inject context to the log output: inject context as extra fields in records or append context to the each message.
Using filter
This method allow to pass fields to JSON formatters, SaaS log servers, etc. or to use extra fields in format string.
LOGGING = {
'version': 1,
'formatters': {
'extra': {
# rid stands for request_id and comes from context
'format': '%(levelname)s %(rid)s %(name)s %(message)s',
},
},
'filters': {
'context_filter': {
# This filter inject context into each log records.
'()': 'pylogctx.AddContextFilter',
# Default values for string formatting
'default': {'rid': None},
}
},
'handlers': {
'console': {
'class': 'logging.StreamHandler',
'filters': ['context_filter'],
},
},
'root': {
'handlers': ['console'],
'level': 'DEBUG',
},
}Using formatter
If you do not want to bother with custom log format and default context values for a filter, you can use pylogctx.AddContextFormatter.
LOGGING = {
'version': 1,
'formatters': {
'append': {
'()': 'pylogctx.AddContextFormatter'
'format': '%(levelname)s %(name)s %(message)s'
},
},
'handlers': {
'console': {
'class': 'logging.StreamHandler',
'formatter': 'append',
},
},
'root': {
'handlers': ['console'],
'level': 'DEBUG',
},
}As you can see in this case we doesn’t add any context related fields to a log format string. This is because pylogctx.AddContextFormatter will append all context information to every log.
Feeding the context
The context object is just a thread local instance. It is used as local registry to inject shared fields in log records. Here is a full example:
from pylogctx.log import context as log_context
log_context.update(userId=user.pk)
# code, log, etc.
for article in blog.articles:
with log_context(articleId=article.pk):
# code, log, ...
# code, log, etc.
log_context.remove('userId')
...
log_context.clear()Automatic feeding with middleware
A middleware is provided to inject extra fields in context. It will also clear the context after each requests.
MIDDLEWARE_CLASSES = [
'pylogctx.django.ExtractRequestContextMiddleware',
# rest middlewares...
]
PYLOGCTX_REQUEST_EXTRACTOR = lambda request: {'rid': request.GET.getlist('rid')}Here PYLOGCTX_REQUEST_EXTRACTOR is a callable which takes django.http.request.HttpRequest and returns dictionary with extracted context.
Note: ExtractRequestContextMiddleware will fail with exception if no PYLOGCTX_REQUEST_EXTRACTOR specified.
Automatic feeding for celery task
A task class is provided to inject clear log context after each task. Use it like this.
app = Celery(task_cls='pylogctx.celery.LoggingTask')
@app.task
def my_task():
logger.info("Logging from task!")Adapt object to log record fields
It can be cumbersome and error-prone to repeat every where in the codebase the association field name, object property. pylogctx allow a simple way to register adapter to class.
import uuid
from pylogctx import log_adapter
from django.http.request import HttpRequest
@log_adapter(HttpRequest)
def adapt_django_requests(request):
return {
djangoRequestId: str(uuid.uuid4()),
}Triggering the adapt logic is as easy as pushing the objects right into the context.
from pylogctx import log_context
log_context.update(request)Contributors
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