# msconvert-cli
A Python wrapper around the ProteoWizard msconvert Docker image for converting mass spectrometry files.
## Installation
```bash
uv pip install msconvert-cli
```
Or install from source:
```bash
git clone https://github.com/pgarrett-scripps/msconvert-cli.git
cd msconvert-cli
uv pip install -e .
```
## Quick Start
Basic conversion with a preset config:
```bash
# Convert files using Sage preset (mzML, 32-bit, compressed)
mscli /path/to/raw/files/ -o /output/dir --sage
# Convert with multiple workers (runs 1 file per worker due to Wine limitations)
mscli /data/*.raw -o /output --blitzff --workers 4
# Verbose logging
mscli /data/*.raw -o /output --casanovo -v
```
## Available Presets
- `--sage`: mzML, 32-bit, zlib/gzip compression
- `--biosaur`: mzML format
- `--blitzff`: mzML, MS1 only, 32-bit, zlib/gzip
- `--casanovo`: mzML, MS2 only, m/z [50-2500], denoised, top 200 peaks
- `--casanovo_mgf`: Same as casanovo but MGF format
## Usage Examples
```bash
# Convert all RAW files in a directory
mscli /data/raw_files/ -o /output --sage
# Convert specific files with custom config
mscli file1.raw file2.raw -o /output -c my_config.txt
# Parallel conversion (4 workers, 1 file per worker)
mscli /data/*.raw -o /output --blitzff --workers 4
# Parallel conversion with resource limits
mscli /data/*.raw -o /output --sage --workers 4 --worker-cores 2.0 --worker-memory 4g
# Limit memory and disable swap
mscli /data/*.raw -o /output --sage --worker-memory 4g --worker-swap 4g
# Increase shared memory for large files
mscli /data/*.raw -o /output --sage --worker-shm-size 2g
# Verbose logging to custom file
mscli /data/*.raw -o /output --sage -v --log conversion.log
# Use a specific Docker image version
mscli /data/*.raw -o /output --sage --docker-image proteowizard/pwiz-skyline-i-agree-to-the-vendor-licenses:3.0.23310
# Pass additional msconvert arguments
mscli data.raw -o /output --filter "peakPicking vendor msLevel=1"
```
## Docker Resource Limits
You can control resource allocation for each worker container:
- `--worker-cores`: CPU cores per container (e.g., `2.0`, `0.5`)
- `--worker-memory`: RAM limit (e.g., `4g`, `2048m`)
- `--worker-swap`: Swap limit (e.g., `1g`). Set equal to memory to disable swap.
- `--worker-shm-size`: Shared memory size (default: `512m`). Increase for large files.
Example with all limits:
```bash
mscli /data/*.raw -o /output --sage \
--workers 4 \
--worker-cores 2.0 \
--worker-memory 4g \
--worker-swap 4g \
--worker-shm-size 1g
```
## Logging
Logs are automatically created in the output directory when using `-v` (verbose mode):
```bash
# Auto-generates: /output/msconvert_20251023_144550.log
mscli /data/*.raw -o /output --sage -v
# Or specify a custom log file
mscli /data/*.raw -o /output --sage -v --log my_run.log
```
Log files include:
- Full command details
- Processing progress for each file
- stdout/stderr from msconvert
- Error details when conversions fail
## Notes
- Requires Docker to be installed and running
- Uses `proteowizard/pwiz-skyline-i-agree-to-the-vendor-licenses` Docker image
- Multi-worker mode processes 1 file per worker
- Supports: `.raw`, `.wiff`, `.d`, `.baf`, and other vendor formats
## Development
```bash
# Install with dev dependencies
uv sync
# Run pre-commit hooks
uv run pre-commit run -a
# Run the CLI locally
uv run mscli --help
```
---
Repository initiated with [fpgmaas/cookiecutter-uv](https://github.com/fpgmaas/cookiecutter-uv).
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