magika

What it is and what it does

Magika is an AI-powered file type detection tool that uses a lightweight deep learning model to identify file content types by analyzing file bytes rather than relying on file extensions or magic numbers alone. It works as both a standalone command-line tool and a Python library, making it suitable for integration into larger systems or use as a utility.

The package wraps a custom-trained neural network model (a few MBs in size) that has been trained on approximately 100M samples across 200+ content types, covering both binary and textual formats. It provides structured output including the detected label, description, MIME type, file extensions, and a confidence score. The tool supports multiple output formats (plain text, JSON, JSONL) and can process files from disk, stdin, or byte streams in Python code.

Use it for:

• Validate uploaded file types in web applications without trusting user-supplied extensions or MIME type headers.
• Automatically categorize and organize files in bulk processing pipelines by their actual content rather than filename.
• Detect potentially malicious files disguised with incorrect extensions during security scanning workflows.
• Build content-aware indexing systems that need accurate file type information for search or filtering.
• Replace or supplement traditional file magic number detection in tools that need higher accuracy on modern formats.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Magika identifies file types using deep learning, analyzing file content to determine MIME types and file categories with high accuracy, available as both a command-line tool and Python library.

Yes. Magika is actively maintained, has low install friction, carries no security vulnerabilities, and uses a permissive license. It solves a real problem (accurate file type detection) with a well-engineered approach. Install it if you need reliable file type identification beyond simple extension or magic-byte checks; skip it only if your use case is limited to a handful of well-known formats where simpler tools suffice.

Install

magika on PyPI

pip install magika

uv add magika

poetry add magika

Installing magika

Before you install

Low friction install with only two runtime dependencies (click and onnxruntime). Active maintenance with recent commits and a large repository following (17950 stars). Supports Python 3.8 through 3.14, distributed as a pre-built wheel.

License in practice

Licensed under Apache-2.0 (permissive), allowing commercial and private use with minimal restrictions. Suitable for most projects without license compatibility concerns.

Quickstart

pip install magika

from magika import Magika
m = Magika()
res = m.identify_bytes(b'function log(msg) {console.log(msg);}')
print(res.output.label)  # outputs: javascript

onnxruntime must be available; the package includes platform-specific compiled wheels for common architectures, with a pure-Python fallback for unsupported platforms.

Verify before relying

• Whether the ~100M training samples and 200+ content types mentioned in the description are current for version 1.0.3.
• Performance characteristics (millisecond detection times) on typical hardware configurations.
• Exact list of all 200+ supported file formats and their detection accuracy breakdown.

Package facts

Evidence: magika-1.0.3-py3-none-any.whl

Keywords: content type detection, machine learning

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