{"id":2110,"library":"magika","title":"Magika","description":"Magika is an AI-powered file type detection tool developed by Google. It leverages deep learning to accurately identify content types, supporting over 200 formats including binary and textual files. It boasts high accuracy (~99%) and fast inference times, making it suitable for security, data processing, and development workflows. The current version is 1.0.2, and it receives active development and regular updates.","status":"active","version":"1.0.2","language":"en","source_language":"en","source_url":"https://github.com/google/magika/","tags":["file type detection","deep learning","machine learning","security","content analysis"],"install":[{"cmd":"pip install magika","lang":"bash","label":"Install latest stable version"}],"dependencies":[{"reason":"Required for running the deep learning model inference.","package":"onnxruntime","optional":false},{"reason":"Used for command-line interface utilities; part of the Python package distribution.","package":"click","optional":false}],"imports":[{"symbol":"Magika","correct":"from magika import Magika"},{"note":"Used for custom instantiation of the Magika class to control prediction confidence.","symbol":"PredictionMode","correct":"from magika import Magika, PredictionMode"}],"quickstart":{"code":"from magika import Magika\nimport os\n\nm = Magika()\n\n# Example 1: Identify from bytes\nfile_content_bytes = b\"console.log('Hello, Magika!');\"\nresult_bytes = m.identify_bytes(file_content_bytes)\nprint(f\"Content type (bytes): {result_bytes.output.label}\")\n\n# Example 2: Identify from a dummy file path\n# Create a dummy file for demonstration\ndummy_file_path = \"./dummy_script.js\"\nwith open(dummy_file_path, \"wb\") as f:\n    f.write(file_content_bytes)\n\nresult_path = m.identify_path(dummy_file_path)\nprint(f\"Content type (path): {result_path.output.label}\")\n\nos.remove(dummy_file_path)\n","lang":"python","description":"Instantiate the `Magika` class and use `identify_bytes` or `identify_path` to determine the content type of a file or byte string. The `output.label` field provides the identified content type. For optimal performance with large files, `identify_path` or `identify_stream` are recommended as they avoid loading the entire content into memory."},"warnings":[{"fix":"Manually load `.env` files using `python-dotenv` if needed, before initializing Magika, or explicitly pass configuration to Magika if such options become available.","message":"Starting with version 1.0.2, Magika no longer automatically loads `.env` files. If your application relied on `python-dotenv` being implicitly managed by Magika, this behavior has changed.","severity":"breaking","affected_versions":">=1.0.2"},{"fix":"Consult the official documentation and changelogs for specific migration paths and updated API usage when upgrading from 0.x versions. Review `Magika` class constructor arguments and identification methods.","message":"Magika 1.0 represents a significant rewrite, with the core engine and CLI implemented in Rust, and the Python module being 'revamped.' While intended for easier integration, users migrating from pre-1.0 experimental versions (0.x.x) might encounter API changes or behavioral differences requiring code updates. The Python CLI itself also shifted from a pure Python implementation to a Rust binary wrapper around version 0.6.0.","severity":"breaking","affected_versions":">=1.0.0 (from <1.0.0)"},{"fix":"Prefer `magika.identify_path(path)` or `magika.identify_stream(file_stream)` for large files, as these methods are optimized to read only necessary portions of the file by seeking, reducing memory footprint.","message":"For large files, using `magika.identify_bytes()` can lead to high memory consumption as it loads the entire file content into memory. This is not efficient for very large files.","severity":"gotcha","affected_versions":"All versions"},{"fix":"Ensure you have a compatible `onnxruntime` version for your Python environment and operating system. In case of installation issues, check `onnxruntime`'s official documentation for troubleshooting.","message":"The `onnxruntime` dependency, while crucial for Magika's performance, can be substantial in size and may introduce platform-specific installation complexities. While Magika 1.0.2 improved support for Python 3.14 and removed some Windows-specific pins, `onnxruntime` itself has had historical issues with specific Python versions or architectures.","severity":"gotcha","affected_versions":"All versions"}],"env_vars":null,"last_verified":"2026-04-09T00:00:00.000Z","next_check":"2026-07-08T00:00:00.000Z"}