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https://github.com/guillotinaweb/aiofluent


https://github.com/guillotinaweb/aiofluent

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README

          

A Python structured logger for Fluentd
======================================

WARNING: This is a fork of the https://github.com/fluent/fluent-logger-python
project to work with asyncio.

Many web/mobile applications generate huge amount of event logs (c,f.
login, logout, purchase, follow, etc). To analyze these event logs could
be really valuable for improving the service. However, the challenge is
collecting these logs easily and reliably.

`Fluentd `__ solves that problem by
having: easy installation, small footprint, plugins, reliable buffering,
log forwarding, etc.

**aiofluent** is a Python library, to record the events from
Python application.

Requirements
------------

- Python 3.5 or greater
- ``msgpack-python``

Installation
------------

This library is distributed as 'aiofluent' python package. Please
execute the following command to install it.

.. code:: sh

$ pip install aiofluent

Configuration
-------------

Fluentd daemon must be launched with a tcp source configuration:

::


type forward
port 24224

To quickly test your setup, add a matcher that logs to the stdout:

::


type stdout

Usage
-----

FluentSender Interface
~~~~~~~~~~~~~~~~~~~~~~

`sender.FluentSender` is a structured event logger for Fluentd.

By default, the logger assumes fluentd daemon is launched locally. You
can also specify remote logger by passing the options.

.. code:: python

from aiofluent import sender

# for local fluent
logger = sender.FluentSender('app')

# for remote fluent
logger = sender.FluentSender('app', host='host', port=24224)

For sending event, call `emit` method with your event. Following example will send the event to
fluentd, with tag 'app.follow' and the attributes 'from' and 'to'.

.. code:: python

# Use current time
logger.emit('follow', {'from': 'userA', 'to': 'userB'})

# Specify optional time
cur_time = int(time.time())
logger.emit_with_time('follow', cur_time, {'from': 'userA', 'to':'userB'})

You can detect an error via return value of `emit`. If an error happens in `emit`, `emit` returns `False` and get an error object using `last_error` method.

.. code:: python

if not logger.emit('follow', {'from': 'userA', 'to': 'userB'}):
print(logger.last_error)
logger.clear_last_error() # clear stored error after handled errors

If you want to shutdown the client, call `close()` method.

.. code:: python

logger.close()

Event-Based Interface
~~~~~~~~~~~~~~~~~~~~~

This API is a wrapper for `sender.FluentSender`.

First, you need to call ``sender.setup()`` to create global `sender.FluentSender` logger
instance. This call needs to be called only once, at the beginning of
the application for example.

Initialization code of Event-Based API is below:

.. code:: python

from aiofluent import sender

# for local fluent
sender.setup('app')

# for remote fluent
sender.setup('app', host='host', port=24224)

Then, please create the events like this. This will send the event to
fluentd, with tag 'app.follow' and the attributes 'from' and 'to'.

.. code:: python

from aiofluent import event

# send event to fluentd, with 'app.follow' tag
event.Event('follow', {
'from': 'userA',
'to': 'userB'
})

`event.Event` has one limitation which can't return success/failure result.

Other methods for Event-Based Interface.

.. code:: python

sender.get_global_sender # get instance of global sender
sender.close # Call FluentSender#close

Handler for buffer overflow
~~~~~~~~~~~~~~~~~~~~~~~~~~~

You can inject your own custom proc to handle buffer overflow in the event of connection failure. This will mitigate the loss of data instead of simply throwing data away.

.. code:: python

import msgpack
from io import BytesIO

def handler(pendings):
unpacker = msgpack.Unpacker(BytesIO(pendings))
for unpacked in unpacker:
print(unpacked)

logger = sender.FluentSender('app', host='host', port=24224, buffer_overflow_handler=handler)

You should handle any exception in handler. aiofluent ignores exceptions from ``buffer_overflow_handler``.

This handler is also called when pending events exist during `close()`.

Python logging.Handler interface
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

This client-library also has ``FluentHandler`` class for Python logging
module.

.. code:: python

import logging
from aiofluent import handler

custom_format = {
'host': '%(hostname)s',
'where': '%(module)s.%(funcName)s',
'type': '%(levelname)s',
'stack_trace': '%(exc_text)s'
}

logging.basicConfig(level=logging.INFO)
l = logging.getLogger('fluent.test')
h = handler.FluentHandler('app.follow', host='host', port=24224)
formatter = handler.FluentRecordFormatter(custom_format)
h.setFormatter(formatter)
l.addHandler(h)
l.info({
'from': 'userA',
'to': 'userB'
})
l.info('{"from": "userC", "to": "userD"}')
l.info("This log entry will be logged with the additional key: 'message'.")

You can also customize formatter via logging.config.dictConfig

.. code:: python

import logging.config
import yaml

with open('logging.yaml') as fd:
conf = yaml.load(fd)

logging.config.dictConfig(conf['logging'])

A sample configuration ``logging.yaml`` would be:

.. code:: python

logging:
version: 1

formatters:
brief:
format: '%(message)s'
default:
format: '%(asctime)s %(levelname)-8s %(name)-15s %(message)s'
datefmt: '%Y-%m-%d %H:%M:%S'
fluent_fmt:
'()': fluent.handler.FluentRecordFormatter
format:
level: '%(levelname)s'
hostname: '%(hostname)s'
where: '%(module)s.%(funcName)s'

handlers:
console:
class : logging.StreamHandler
level: DEBUG
formatter: default
stream: ext://sys.stdout
fluent:
class: fluent.handler.FluentHandler
host: localhost
port: 24224
tag: test.logging
formatter: fluent_fmt
level: DEBUG
none:
class: logging.NullHandler

loggers:
amqp:
handlers: [none]
propagate: False
conf:
handlers: [none]
propagate: False
'': # root logger
handlers: [console, fluent]
level: DEBUG
propagate: False

License
-------

Apache License, Version 2.0