Application and Access Logging#

Logging Requests#

To log requests, it is strongly recommended to use the access_logger of your broker, as it is available from the Context of your application.

from faststream import Logger
from faststream.rabbit import RabbitBroker

broker = RabbitBroker()

@broker.subscriber("test")
async def func(logger: Logger):
    logger.info("message received")

This approach offers several advantages:

• The logger already contains the request context, including the message ID and broker-based parameters.
• By replacing the logger when initializing the broker, you will automatically replace all loggers inside your functions.

Logging Levels#

If you use the FastStream CLI, you can change the current logging level of the entire application directly from the command line.

The --log-level flag sets the current logging level for both the broker and the FastStream app. This allows you to configure the levels of not only the default loggers but also your custom loggers, if you use them inside FastStream.

faststream run serve:app --log-level debug

If you want to completely disable the default logging of FastStream, you can set logger=None

from faststream import FastStream
from faststream.rabbit import RabbitBroker

broker = RabbitBroker(logger=None)     # Disables broker logs
app = FastStream(broker, logger=None)  # Disables application logs

If you don't want to lose access to the `logger' inside your context but want to disable the default logs of FastStream, you can lower the level of logs that the broker publishes itself.

import logging
from faststream.rabbit import RabbitBroker

# Sets the broker logs to the DEBUG level
broker = RabbitBroker(log_level=logging.DEBUG)

Formatting Logs#

If you are not satisfied with the current format of your application logs, you can change it directly in your broker's constructor.

from faststream.rabbit import RabbitBroker
broker = RabbitBroker(log_fmt="%(asctime)s %(levelname)s - %(message)s")

Using Your Own Loggers#

Since FastStream works with the standard logging.Logger object, you can initiate an application and a broker using your own logger.

import logging
from faststream import FastStream
from faststream.rabbit import RabbitBroker

logger = logging.getLogger("my_logger")

broker = RabbitBroker(logger=logger)
app = FastStream(broker, logger=logger)

By doing this, you will lose information about the context of the current request. However, you can retrieve it directly from the context anywhere in your code.

from faststream import context
log_context: dict[str, str] = context.get_local("log_context")

This way, all broker handlers can get access to your broker logger right from the context:

from faststream import Logger

@broker.subscriber(...)
async def handler(
    msg,
    logger: Logger,  # <-- YOUR logger here
):
    logger.info(msg)

Structlog Example#

Structlog is a production-ready logging solution for Python. It can be easily integrated with any log storage system, making it suitable for use in production projects.

Here is a quick tutorial on integrating Structlog with FastStream:

Start with the Structlog guide example:

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import sys
import structlog

shared_processors = (
    structlog.processors.add_log_level,
    structlog.processors.StackInfoRenderer(),
    structlog.dev.set_exc_info,
    structlog.processors.TimeStamper(fmt="iso"),
)

if sys.stderr.isatty():
    # terminal session
    processors = [
        *shared_processors,
        structlog.dev.ConsoleRenderer(),
    ]
else:
    # Docker container session
    processors = [
        *shared_processors,
        structlog.processors.dict_tracebacks,
        structlog.processors.JSONRenderer(),
    ]

structlog.configure(
    processors=processors,
    logger_factory=structlog.PrintLoggerFactory(),
    cache_logger_on_first_use=False,
)

logger = structlog.get_logger()

We created a logger that prints messages to the console in a user-friendly format during development and uses JSON-formatted logs in production.

To integrate this logger with our FastStream application, we just need to access it through context information and pass it to our objects:

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import logging

import structlog

from faststream import FastStream, context
from faststream.kafka import KafkaBroker

def merge_contextvars(
    logger: structlog.types.WrappedLogger,
    method_name: str,
    event_dict: structlog.types.EventDict,
) -> structlog.types.EventDict:
    event_dict["extra"] = event_dict.get(
        "extra",
        context.get_local("log_context") or {},
    )
    return event_dict

shared_processors = [
    merge_contextvars,
    ...
]

...

broker = KafkaBroker(logger=logger, log_level=logging.DEBUG)
app = FastStream(broker, logger=logger)

And the job is done! Now you have a perfectly structured logs using Structlog.

TIMESPAMP [info     ] FastStream app starting...     extra={}
TIMESPAMP [debug    ] `Handler` waiting for messages extra={'topic': 'topic', 'group_id': 'group', 'message_id': ''}
TIMESPAMP [debug    ] `Handler` waiting for messages extra={'topic': 'topic', 'group_id': 'group2', 'message_id': ''}
TIMESPAMP [info     ] FastStream app started successfully! To exit, press CTRL+C extra={'topic': '', 'group_id': '', 'message_id': ''}