---
id: daiquiri
version: "3.4.0"
license: Apache 2.0
license_treatment: permissive
maintenance: active
---

# daiquiri — Library to configure Python logging easily

License: permissive · Maintenance: active · Downloads: 124.2K/mo

## What it is and what it does

Daiquiri is a Python logging configuration helper that reduces boilerplate when setting up logging in applications. Instead of manually configuring loggers, handlers, and formatters, you call daiquiri's setup function to get a working logging pipeline. It wraps python-json-logger to enable structured JSON logging and provides additional custom formatters and handlers for common use cases.

The package targets system administrators and IT professionals who need reliable, easy-to-configure logging for production applications. It's designed for POSIX/Linux environments and supports Python 3.10 and later. With low install friction and no security vulnerabilities, it's a straightforward addition to projects that want structured logging without extensive configuration code.

Use it for:

- Set up JSON-structured logging in a new application with a single function call instead of manual handler and formatter configuration.
- Configure logging for microservices or containerized applications where structured logs are parsed by log aggregation systems.
- Add consistent logging to system administration scripts and tools running on Linux servers.
- Replace ad-hoc print statements in CLI tools with proper logging that can be easily toggled between console and file output.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Daiquiri simplifies Python logging configuration by providing a single setup call and custom formatters and handlers for structured logging output.

Yes. Daiquiri is actively maintained, has no known vulnerabilities, carries a permissive Apache 2.0 license, and installs with minimal friction. It's a good fit if you want to reduce logging boilerplate in Python applications targeting Python 3.10 or later. Install it if you prefer declarative logging setup over manual configuration; skip it if your project already has a mature logging strategy.

## Install

pip install daiquiri
uv add daiquiri
poetry add daiquiri

## Installing daiquiri

Before you install: Low friction install with a single runtime dependency. The package is actively maintained with a recent commit on 2026-08-13 and supports Python 3.10, 3.11, 3.12, and 3.13.

License in practice: Licensed under Apache 2.0 (permissive), which allows free use, modification, and distribution with minimal restrictions—suitable for both open-source and commercial projects.

Quickstart:

pip install daiquiri

import daiquiri

daiquiri.setup()

Requires Python 3.10 or later.

Verify before relying:

- What specific custom formatters and handlers does daiquiri provide beyond python-json-logger's capabilities?
- Does daiquiri support async logging or only synchronous handlers?
- What are the typical performance characteristics when using daiquiri for high-volume logging?

## Package facts

- License: Apache 2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 124.2K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

python logging configuration, structured logging setup, logging formatter, json logging, easy logging setup, python logging helper, log handler configuration, logging, structured-logging, configuration

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