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eliot

Logging library that tells you why it happened

Worth itPyPI LoggingReleased May 202694.7K downloads / moApache 2.0Pure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — eliot-1.18.0-py3-none-any.whl
v1.18.0 · released 2026-05-07 · Python >=3.10.0 · 4 runtime deps: zope.interface, pyrsistent, boltons, orjson

Yes. Eliot is actively maintained, has low install friction, carries no known vulnerabilities, and solves a real problem—standard logging cannot answer causal questions. It's well-suited for debugging complex systems and distributed tracing. The Apache 2.0 license is permissive. Install it if you need to understand not just what happened, but why.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires Python 3.10 or later (3.10, 3.11, 3.12, 3.13, 3.14, or PyPy 3.11).
  • Low install friction with four runtime dependencies (zope.interface, pyrsistent, boltons, orjson).
  • Actively maintained with recent commits and steady development.

License · maintenance · safety

Apache 2.0 (permissive) — Released under Apache 2.0, a permissive license allowing commercial and private use with minimal restrictions.

last release 2026-05-07 (99 days) · last repo commit 2026-05-07 · 1,186 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 94,708 downloads/mo, #13,312 on PyPI

Verify before relying

pip install eliot

from eliot import start_action

with start_action(action_type="my_action"):
    # your code here
    pass
  • Whether the asyncio/Trio/Twisted support is production-ready or experimental.
  • Performance overhead of structured logging compared to standard logging in typical workloads.
  • Integration maturity with Logstash and ElasticSearch for multi-machine log aggregation.
Same gist for agents: .md · .json

What it is and what it does

Eliot replaces Python's standard logging model with a causal-chain approach: instead of isolated log lines, it records actions that spawn other actions, ultimately succeeding or failing. This lets you trace the story of what your application did—not just what happened, but why it happened and what caused each decision or failure.

The package is designed for single-process logging, distributed tracing across systems, and scientific computing with built-in support for NumPy and Dask. It also integrates with asyncio, Trio, and Twisted for coroutine and networking contexts. For multi-machine deployments, you typically pair it with external aggregation tools to store and query logs.

Use it for

  • Pinpoint performance bottlenecks by tracing causal chains of actions and their timing.
  • Debug complex failures in distributed systems by following the action chain from request to error.
  • Correlate user actions across services using Eliot's task UUID in logs sent to monitoring systems.
  • Instrument scientific computing workflows with NumPy and Dask to understand computation flow.
  • Trace async coroutine execution in asyncio or Trio to understand concurrency issues.

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

Worth it

Yes.

Eliot is actively maintained, has low install friction, carries no known vulnerabilities, and solves a real problem—standard logging cannot answer causal questions. It's well-suited for debugging complex systems and distributed tracing. The Apache 2.0 license is permissive. Install it if you need to understand not just what happened, but why.

Install

eliot on PyPI

Before you install

Low install friction with four runtime dependencies (zope.interface, pyrsistent, boltons, orjson). Actively maintained with recent commits and steady development.

Requires Python 3.10 or later (3.10, 3.11, 3.12, 3.13, 3.14, or PyPy 3.11).

License in practice

Released under Apache 2.0, a permissive license allowing commercial and private use with minimal restrictions.

Quickstart

pip install eliot

from eliot import start_action

with start_action(action_type="my_action"):
    # your code here
    pass

Verify before relying

  • Whether the asyncio/Trio/Twisted support is production-ready or experimental.
  • Performance overhead of structured logging compared to standard logging in typical workloads.
  • Integration maturity with Logstash and ElasticSearch for multi-machine log aggregation.

Package facts

LicenseApache 2.0 permissive
Python supportSupports the current Python release >=3.10.0
Install frictionLow. Pure-Python wheel
Runtime dependencies
4 packages
zope.interfacepyrsistentboltonsorjson
MaintenanceActively maintained 99 days since the last release
Last repo commit
First released
Downloads94,708 / month, #13,312 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Intended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPyTopic :: System :: Logging

Evidence: eliot-1.18.0-py3-none-any.whl

Tags

Capabilities
structured logging pythoncausal tracing loggingdistributed tracingaction-based loggingwhy did this happen loggingapplication event tracingperformance debugging logs
Topics
structured-loggingdistributed-tracingdebugging
PyPI keywords
logging

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See also structlog-sentry · mo-logs · mlflow-tracing · django-guid · Autologging · django-cid · causallib · pgmpy · robocorp-log · asgi-correlation-id