Getting Started

Get Salpa running on your machine in a few minutes.

System requirements

Disk space: ~500 MB for the app, plus additional space for node environments (varies by node).

No prerequisites required — Salpa bundles its own Python environment and all background services. You don’t need to install Python, pip, conda, or any other tooling.

Download and install

All Salpa builds are published on the Salpa releases page . Pick the latest tag and grab the file that matches your platform:

macOS

1. Open the DMG you downloaded and drag Salpa to your Applications folder.
2. On first launch, macOS may show a security prompt — right-click the app and select “Open”.

Linux (AppImage)

chmod +x Salpa-*.AppImage
./Salpa-*.AppImage

Windows

Run the .exe installer and follow the prompts. Launch Salpa from the Start Menu when it finishes.

First launch

When you open Salpa for the first time:

1. The app will set up its Python environment automatically (this takes 1-2 minutes on first run)
2. You’ll see the Home page with tips, recent workflows, and quick actions
3. The status bar at the bottom shows when Salpa is ready to use

Your first workflow

1. Click New Workflow in the top bar
2. Give your workflow a name (e.g., “My First Workflow”)
3. Open the Node Library (left sidebar) and browse available nodes
4. Drag a node (e.g., “Hello World”) onto the canvas
5. Click the node to open its configuration panel on the right
6. Click the round Play button in the bottom bar to run the workflow
7. Watch the progress in real-time — logs stream live to the execution panel

Key shortcuts

These work inside the workflow editor, once a workflow is open:

Everything else — creating, saving, and running a workflow, and switching theme — is a button or a Settings toggle rather than a keystroke.

Uninstalling

Removing the application takes the usual route for each platform — drag Salpa.app to the Trash, delete the AppImage, or use Add or Remove Programs on Windows. That removes the program. It does not remove what the program built, and the part that stays behind is the part that takes the space: the Python environments Salpa solved for its nodes, and the package cache they were built from. Your workflows and settings are kept on purpose; the environments are kept because an uninstaller that reaches into them is a riskier thing than one that does not.

From Salpa 0.4.0 the app does this for you. Open Environments and press Free disk space: it lists every environment and package cache Salpa built, on both sides of WSL where that applies, with the size of each, and removes them in one confirmed step — measured on a Windows machine with two packages installed: 12.9 GB, 10.2 GB of it inside WSL. Do it before uninstalling; afterwards the app that knew where everything was is gone, and the commands below are what is left.

What stays, and how to remove it by hand:

macOS

rm -rf ~/.bocoflow                                         # environments, pixi
rm -rf ~/Library/Application\ Support/bocoflow-electron    # profile: workflows, settings, logs

Linux

rm -rf ~/.bocoflow                     # environments, pixi
rm -rf ~/.config/bocoflow-electron     # profile: workflows, settings, logs
rm -rf ~/.cache/rattler                # the conda package cache

Windows. Two places, and the second is the one nobody finds. Packages that have no Windows build (GROMACS, ProMod3) run through WSL2, and their environments live inside the Linux distribution, where Windows tools like Disk Cleanup do not look. Measured after uninstalling with the pdbmdauto package installed: about 1 GB left on the Windows side and 11 GB inside WSL.

Remove-Item -Recurse -Force "$env:USERPROFILE\.bocoflow"                   # environments, pixi
Remove-Item -Recurse -Force "$env:APPDATA\bocoflow-electron"              # profile: workflows, settings, logs
wsl -e bash -c "rm -rf ~/.bocoflow ~/.cache/rattler"                       # the 11 GB: WSL-side environments + package cache

The profile directory holds your saved workflows. Copy anything you want to keep out of it first, or leave that line out and remove only the environments.

Next steps

• Features — Explore all capabilities
• Node System — Understand how nodes and workflows work
• Build Custom Nodes — Create your own computational nodes