OpenHCS documentation

OpenHCS is a bioimage-analysis platform for high-content screening. It turns pipeline declarations into validated, per-plate execution plans and runs them across microscopy datasets using CPU or GPU processing libraries.

Choose a path

Using OpenHCS

Start with Getting started, then use the User guide for task-oriented workflows.

Understanding the model

Start with the Architecture quick start, then use Core Concepts for pipelines, steps, dimensions, sources, and processing semantics.

Extending or maintaining OpenHCS

Use Developer guide for contribution workflows and Architecture reference for system boundaries and invariants.

Quick start

OpenHCS requires Python 3.11 or newer. Install and launch the desktop GUI with:

python -m pip install "openhcs[gui]"
openhcs

Viewer integrations are optional:

python -m pip install "openhcs[gui,napari]"  # Napari
python -m pip install "openhcs[gui,fiji]"    # Fiji/ImageJ
python -m pip install "openhcs[gui,viz]"     # Both

The Textual terminal interface is deprecated and is not part of the published package.

System at a glance

OpenHCS uses ordinary Python declarations at its public boundary:

PipelineConfig + list[FunctionStep]
    -> ObjectState resolution
    -> StepSnapshot + CompilationSession
    -> typed CompiledStepPlan objects
    -> CompiledExecutionBundle
    -> runtime values, artifacts, and materialized outputs

CellProfiler .cppipe files lower directly into the same PipelineConfig and FunctionStep declarations. The compiler resolves configuration once and derives source, artifact, memory, and execution plans from the authoritative declarations.

Documentation

Indices