---
id: magic-filter
version: "1.0.12"
license: unclear
license_treatment: permissive
maintenance: dormant
---

# magic-filter

License: permissive · Maintenance: dormant · Downloads: 3.0M/mo

## What it is and what it does

magic-filter is a lightweight Python library that lets you build filters using dynamic attribute access and a fluent syntax. Instead of writing nested conditionals or lambda functions, you construct filter expressions by accessing attributes on a special filter object, then apply those expressions to check or filter data. The library has no runtime dependencies and supports Python 3.7 through 3.11.

The package is in alpha status and has been dormant since late 2023, so it is stable for existing use cases but should not be expected to receive active maintenance or new features. It carries permissive licensing and is commonly associated with the aiogram ecosystem.

Use it for:

- Build declarative filters for message routing in Telegram bot handlers without writing nested conditionals.
- Validate object attributes against multiple conditions using a readable, expression-like syntax.
- Create reusable filter expressions that can be composed and applied to different data structures.
- Filter collections of objects by attribute values using a fluent API instead of list comprehensions.

## Worth the install?

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

Provides a filter mechanism based on dynamic attribute access that enables declarative filtering of objects using a fluent, expression-like syntax.

Yes, if you need declarative filtering and are comfortable with dormant maintenance. The package is stable, has no dependencies, and carries permissive licensing. It is well-suited for attribute-based filtering tasks where readability matters more than active development. Do not expect bug fixes or new features.

## Install

pip install magic-filter
uv add magic-filter
poetry add magic-filter

## Installing magic-filter

Before you install: Low friction installation with no runtime dependencies. Maintenance is dormant—last commit was 2023-09-25—so expect no active bug fixes or feature development, though the package is stable enough for existing use.

License in practice: Licensed under MIT (permissive), so you can use, modify, and distribute it freely with minimal restrictions.

Quickstart:

pip install magic-filter

from magic_filter import F

filter_expr = F.name == 'example'
result = filter_expr.check({'name': 'example'})

Verify before relying:

- Exact semantics and typical use patterns beyond 'dynamic attribute getter' are not detailed in the fact sheet.
- Whether this is primarily for data validation, query building, or both remains unclear from the excerpt.
- How the package is typically used in practice beyond the aiogram ecosystem.

## Package facts

- License: not declared (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: dormant
- Downloads: 3.0M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

dynamic attribute filtering, magic filter library, declarative object filtering, filter expressions, attribute-based filtering, fluent filter api, validation filtering, filtering, declarative

[View on SkillFed](https://skillfed.io/packages/magic-filter) · [View on PyPI](https://pypi.org/project/magic-filter/)