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http-logging

Non-blocking HTTP handler for Python `logging` with local SQLite buffer/cache.


Maintainers
1

Asynchronous HTTP Logging

Non-blocking HTTP handler for Python logging with local SQLite buffer/cache.

Test Coverage Maintained Maintainability Technical Debt Issues CodeFactor

Requirements Status PyPI License

Code Style Code Formatter Test Framework

Documentation

Please refer to the project Wiki.

Installation

Virtual environment is highly recommended.

pip install http_logging

Basic usage

import logging

from http_logging import HttpHost
from http_logging.handler import AsyncHttpHandler

log_handler = AsyncHttpHandler(http_host=HttpHost(name='your-domain.com'))

logger = logging.getLogger()
logger.addHandler(log_handler)

# Works with simple log messages like:
logger.info('Some useful information...')

# Can also handle extra fields:
logger.warning('You\'ve been warned!', extra={'foo': 'bar'})

# And, of course, captures exception with full stack-trace
try:
    1/0
except Exception as exc:
    logger.error('Ooops!', exc_info=exc)

These log messages are cached in a local SQLite database and periodically delivered (asynchronously, in a separate thread) to your host in a POST request with a body similar to this one:

[
    {
        "type": "async-http-logging",
        "created": 1610393068.365492,
        "relative_created": 1505.5122375488281,
        "message": "Some useful information...",
        "level": {
            "number": 20,
            "name": "INFO"
        },
        "stack_trace": null,
        "sourcecode": {
            "pathname": "/path/to/your/python/script.py",
            "function": "function_name",
            "line": 123
        },
        "process": {
            "id": 1234,
            "name": "MainProcess"
        },
        "thread": {
            "id": 1234567890,
            "name": "MainThread"
        }
    },
    {
        "type": "async-http-logging",
        "created": 1610393068.3663092,
        "relative_created": 1506.3292980194092,
        "message": "You've been warned!",
        "level": {
            "number": 30,
            "name": "WARNING"
        },
        "stack_trace": null,
        "sourcecode": {
            "pathname": "/path/to/your/python/script.py",
            "function": "function_name",
            "line": 456
        },
        "process": {
            "id": 1234,
            "name": "MainProcess"
        },
        "thread": {
            "id": 1234567890,
            "name": "MainThread"
        }
    },
    {
        "type": "async-http-logging",
        "created": 1610393068.3663092,
        "relative_created": 1506.3292980194092,
        "message": "Ooops!",
        "level": {
            "number": 40,
            "name": "ERROR"
        },
        "stack_trace": "Traceback (most recent call last):\n  File \"/path/to/your/python/script.py\", line 17, in function_name\n    1/0\nZeroDivisionError: division by zero\n",
        "sourcecode": {
            "pathname": "/path/to/your/python/script.py",
            "function": "function_name",
            "line": 17
        },
        "process": {
            "id": 1234,
            "name": "MainProcess"
        },
        "thread": {
            "id": 1234567890,
            "name": "MainThread"
        }
    }
]

In your backend, you can funnel these logs to wherever suits you best: database, ElasticSearch index, third-party monitoring service, etc.

Learn more about these and other features in the project Wiki.

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