pymsio 0.1.10

MS I/O readers with optional vendor bindings

Pymsio

Pymsio is a lightweight module for reading mass-spectrometry data files into a unified NumPy/Polars representation.
Its design and implementation are based on the AlphaRaw project: https://github.com/MannLabs/alpharaw/.

It currently supports:

• Thermo RAW files (via pythonnet + Thermo Fisher CommonCore DLLs)
• mzML files

Both formats are exposed through a common interface.

---

Requirements

• OS: Windows, Linux (macOS not tested)
• Python: >= 3.8
• Thermo RAW:
  • Requires Thermo Fisher CommonCore DLLs (ThermoFisher.CommonCore.Data.dll, ThermoFisher.CommonCore.RawFileReader.dll) obtained from the RawFileReader project (https://github.com/thermofisherlsms/RawFileReader).
  • Linux also needs Mono (use install_mono.sh).

---

Installation

1. Clone the repository

   git clone https://github.com/bertis-informatics/pymsio.git
   cd pymsio
   

2. Provide the Thermo DLLs (only needed for Thermo RAW)

   • Linux only: ensure Mono is installed (required by pythonnet). Use the helper script:

     ./install_mono.sh
     

   1. Download (or git clone) RawFileReader: https://github.com/thermofisherlsms/RawFileReader
   2. Copy the two DLLs from RawFileReader/Libs/Net471/:
      • ThermoFisher.CommonCore.Data.dll
      • ThermoFisher.CommonCore.RawFileReader.dll
   3. Make the DLLs discoverable:
      • Option A — Bundle DLLs inside the package <path-to-pymsio>/pymsio/dlls/thermo_fisher/
        • Copy the DLLs into pymsio/dlls/thermo_fisher/ before running pip install -e . so they ship with the installation.
        • Example:

          mkdir -p pymsio/dlls/thermo_fisher
          cp /path/to/RawFileReader/Libs/Net471/*.dll /path/to/pymsio/pymsio/dlls/thermo_fisher/
          

      • Option B — Set up an environment variable PYMSIO_THERMO_DLL_DIR
        • Windows example:

          setx PYMSIO_THERMO_DLL_DIR "<path-to-your-dll-folder>"
          

        • Linux example:

          export PYMSIO_THERMO_DLL_DIR="<path-to-your-dll-folder>"
          

          (Add the export line to ~/.bashrc to keep it persistent.)
        • Copy the DLLs into the folder referenced by the variable.

3. Install pymsio

   Option A — Conda environment

   conda create -n pymsio-env python=3.8 -y
   conda activate pymsio-env
   pip install .
   

   Option B — pip + venv (Python 3.8+)

   This project declares requires-python = ">=3.8", so you must have Python 3.8 or newer installed before creating a venv and running pip install ..

   Linux

   # Go to the folder where pyproject.toml is located.
   python3 -m venv .venv
   source .venv/bin/activate
   
   pip install .
   

   Windows PowerShell

   # Go to the folder where pyproject.toml is located.
   python -m venv .venv
   .\.venv\Scripts\Activate.ps1
   
   pip install .
   

pymsio is available on PyPI, so you can also install and use it directly inside your virtual environment with(DLLs download and path setting also required):

pip install pymsio

---

Quick Start

Read a file (Thermo RAW or mzML) via ReaderFactory

from pathlib import Path
from pymsio.readers import ReaderFactory 

path = Path("path/to/your/file.raw")   # or .mzML

# 1) Get appropriate reader
reader = ReaderFactory.get_reader(path)

# 2) Read metadata (Polars DataFrame)
meta_df = reader.get_meta_df()
print(meta_df.head())

# 3) Read one frame (np.ndarray, shape (N, 2), [mz, intensity])
frame_num = int(meta_df.item(0, "frame_num"))
peaks = reader.get_frame(frame_num)
print(peaks.shape)

# 4) Load full dataset 
msdata = reader.load()
print(msdata.peak_arr.shape)

Read multiple frames

frame_nums = meta_df["frame_num"].to_list() # or List[] which has frame numbers
peak_arr = reader.get_frames(frame_nums)
print(len(peak_arr), peak_arr[0].shape)

---

Notes

• If Thermo RAW fails with missing assemblies, double-check that the two DLLs are in: PYMSIO_THERMO_DLL_DIR (Environment variable) or .../{cwd}/dlls/thermo_fisher/