structlog-sentry-logger 0.4.0

Log without the setup via a pre-configured structlog logger with optional Sentry integration

Structlog-Sentry-Logger

A multi-purpose, pre-configured structlog logger with (optional) Sentry integration via structlog-sentry.

Why

1. Makes logging as easy as using print statements, but prettier and less smelly!
2. Highly opinionated! There are only two (2) distinct configurations.
3. Structured logs in JSON format means they are ready to be ingested by many of your favorite log analysis tools!

What You Get

Powerful Automatic Context Fields

The pre-configured options include:

1. Timestamps
   • DATETIME_FORMAT = "%Y-%m-%d %H:%M:%S"
2. Log levels
   • Added to the JSON context for filtering and categorization
3. Logger names
   • Automatically assigned to namespaced versions of the initializing python modules (.py files), relative to your project directory.
     • e.g., the logger in tests/structlog_sentry_logger/test_logger.py is named tests.structlog_sentry_logger.test_logger

With fields sorted by key for easier at-a-glance analysis.

Performance

structlog-sentry-logger is fully-tuned and leverages ORJSON as the JSON serializer for lightning-fast logging. Let cross-cutting concerns cripple performance no longer!

For further reference, see:

• "ORJSON: Serialize" for benchmarks
• "structlog: Performance" for salient performance-related configurations.

Built-in Sentry Integration (Optional)

Automatically add much richer context to your Sentry reports.

• Your entire logging context is sent as a Sentry event when the structlog-sentry-logger log level is error or higher.
  • i.e., logger.error(""), logger.exception("")
• See structlog-sentry for more details.

---

Table of Contents

• Installation
• Usage
  • Pure structlog Logging (Without Sentry)
  • Sentry Integration
• Output: Formatting & Storage
• Summary
• Further Reading
  • structlog
  • Sentry
  • structlog-sentry

Installation

pip install structlog-sentry-logger

Usage

Pure structlog Logging (Without Sentry)

At the top of your Python module, import and instantiate the logger:

import structlog_sentry_logger
LOGGER = structlog_sentry_logger.get_logger()

Now anytime you want to print anything, don't. Instead do this:

LOGGER.info("Information that's useful for future me and others", extra_field="extra_value")

Note: all the regular Python logging levels are supported.

{
    "event": "Information that's useful for future me and others",
    "extra_field": "extra_value",
    "level": "info",
    "logger": "<input>",
    "timestamp": "2020-09-25 17:21:26",
}

With structlog, you can even incorporate custom messages in your exception handling:

import uuid

import structlog_sentry_logger
LOGGER = structlog_sentry_logger.get_logger()

curr_user_logger = LOGGER.bind(uuid=uuid.uuid4().hex)  # LOGGER instance with bound UUID
try:
    curr_user_logger.warn("A dummy error for testing purposes is about to be thrown!")
    assert False
except AssertionError as err:
    err_msg = ("I threw an error on purpose for this example!\n"
               "Now throwing another that explicitly chains from that one!")
    curr_user_logger.exception(err_msg)
    raise RuntimeError(err_msg) from err

{
    "event": "A dummy error for testing purposes is about to be thrown!",
    "level": "warning",
    "logger": "<input>",
    "timestamp": "2020-09-25 17:19:02",
    "uuid": "68f595440e69478a97a26b002f9cbf44",
}
{
    "event": "I threw an error on purpose for this example!\nNow throwing another that explicitly chains from that one!",
    "exception": 'Traceback (most recent call last):\n  File "<input>", line 8, in <module>\nAssertionError',
    "level": "error",
    "logger": "<input>",
    "timestamp": "2020-09-25 17:19:02",
    "uuid": "68f595440e69478a97a26b002f9cbf44",
}
Traceback (most recent call last):
  File "<input>", line 8, in <module>
AssertionError
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
  File "<input>", line 13, in <module>
RuntimeError: I threw an error on purpose for this example!
Now throwing another that explicitly chains from that one!

Sentry Integration

Export your Sentry DSN into your local environment.

• An easy way to do this is to put it into a local .env file and use python-dotenv to populate your environment:

# On the command line:
SENTRY_DSN=YOUR_SENTRY_DSN
echo "SENTRY_DSN=${SENTRY_DSN}" > .env

# In your Python code, prior to instantiating the logger:
from dotenv import find_dotenv, load_dotenv
load_dotenv(find_dotenv())

Output: Formatting & Storage

The default behavior is to stream JSON logs directly to the standard output stream like a proper 12 Factor App.

For local development, it often helps to prettify logging to stdout and save JSON logs to a .logs folder at the root of your project directory. To enable this behavior, set the following environment variable:

CI_ENVIRONMENT_SLUG=dev-local

In doing so, with our previous exception handling example we would get:

Summary

That's it. Now no excuses. Get out there and program with pride knowing no one will laugh at you in production! For not logging properly, that is. You're on your own for that other observability stuff.

Further Reading

structlog: Structured Logging for Python

Sentry: Monitor and fix crashes in realtime.

structlog-sentry: Provides the structlog SentryProcessor for Sentry integration.