native-fisher-py 0.1.1

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native-fisher-py

Why native-fisher-py?

native-fisher-py is a high-performance, drop-in replacement for the legacy fisher-py reader. While the original fisher-py relies on pythonnet and a local .NET runtime (which often fails in CI/CD or specialized Linux environments), native-fisher-py utilizes .NET NativeAOT and Rust to provide a self-contained, high-speed binary bridge.

Features

• Drop-in Replacement: Designed to match the fisher_py.RawFile API for seamless migration.
• Zero .NET Dependency: No local .NET runtime or pythonnet required on the host machine. Everything is bundled.
• Cross-Platform: Native binaries for macOS (ARM64/x64), Linux (x64), and Windows (x64).
• Turbo-charged Performance: Significantly faster metadata discovery and spectral extraction than the legacy Python bridge.

How it works

This project is a clean native bridge to the official Thermo Fisher libraries. It uses a three-layer architecture to provide cross-platform compatibility:

1. Official DLLs: We use the original .dll assemblies provided by Thermo Fisher Scientific.
2. C# NativeAOT Wrapper: A thin, compiled layer (ThermoNativeReader) interfaces directly with the official DLLs and exports a simple C-compatible API.
3. Rust PyO3 Layer: A high-performance Rust bridge (native-fisher-py) provides the Python bindings and handles memory safety and NumPy integration.

This approach ensures that we maintain binary-level parity with the official reader while providing a lightweight, dependency-free experience for Python users.

Quick Start

# Just change the import, the rest of your code stays the same!
from native_fisher_py import RawFile

with RawFile("data.raw") as raw:
    print(f"Number of scans: {raw.number_of_scans}")
    
    # Get spectral data as high-speed NumPy arrays
    m, i, c, meta = raw.get_scan_from_scan_number(1)
    print(f"First peak at {m[0]} m/z with intensity {i[0]}")

Migrating from fisher-py

If you are currently using fisher-py, migration is as simple as:

1. pip install native-fisher-py
2. Update your imports:

- from fisher_py import RawFile
+ from native_fisher_py import RawFile

3. (Optional) Uninstall the old package: pip uninstall fisher-py

All core methods (get_scan_from_scan_number, get_spectrum, get_chromatogram, get_ms2_scan_number_from_retention_time, etc.) are implemented with identical signatures and return types.

Quick Local Build

For convenience, you can run the included build.sh script to build both parts of the project:

./build.sh

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Step-by-Step Manual Build

To build the project from source, you need .NET 8 SDK, Rust (cargo/maturin), and clang.

1. Build the C# NativeAOT Core

Navigate to the C# project and publish the NativeAOT shared library for your platform:

cd native/ThermoNativeReader

# Example for Apple Silicon (macOS arm64)
dotnet publish -r osx-arm64 -c Release -p:PublishAot=true

# Example for Linux (x64)
# dotnet publish -r linux-x64 -c Release -p:PublishAot=true

The output will be in publish/ThermoNativeReader.dylib (or .so / .dll).

2. Build the Rust Bridge

Navigate to the native_fisher_py folder and use maturin to build and install the Python package. You must point to the location of the C# library.

cd native_fisher_py

# Point to your build from Step 1
export THERMO_NATIVE_LIB=$(pwd)/../native/ThermoNativeReader/bin/Release/net8.0/osx-arm64/publish/ThermoNativeReader.dylib

maturin develop

Credits & Legal Notice

This project is powered by the Thermo Fisher Scientific RawFileReader (copyright © 2016-2026 Thermo Fisher Scientific, Inc.). All rights reserved.

The native-fisher-py package includes the official RawFileReader libraries, which remain the property of Thermo Fisher Scientific. By using this software, you agree to the terms specified in their license.