FAST-HEP Workshop

fasthep-workshop contains tutorials, examples, and complete analysis workflows for the FAST-HEP ecosystem.

The workshop is designed to help users learn the FAST-HEP workflow language step-by-step, from reading ROOT files to running distributed analyses on HTCondor or Slurm.

Getting Started

Clone the repository:

git clone https://github.com/FAST-HEP/fasthep-workshop.git
cd fasthep-workshop

Install Pixi (Recommended)

FAST-HEP tutorials use Pixi to provide reproducible environments.

Follow the Pixi installation instructions:

https://pixi.sh/latest/

Then create the environment:

pixi install

Run commands inside the environment:

pixi run fasthep --help

Alternative: pip

If you prefer not to use Pixi, install the required FAST-HEP packages manually:

pip install \
  fasthep-flow \
  fasthep-carpenter \
  fasthep-curator \
  fasthep-render \
  fasthep-toolbench \
  fasthep-cli \
  fasthep-workshop

Please note that all instructions include pixi run - if you do not use pixi, please exclude this prefix to the commands.

Repository Layout

tutorials/
    Step-by-step learning material

examples/
    Standalone examples and demonstrations

data/
    Example datasets and download manifests

docs/
    Additional documentation

Tutorials

The tutorials are organised as a learning path.

00-overview/
    Introduction to FAST-HEP

01-read-data/
    Reading ROOT files and datasets

02-transform-data/
    Derived quantities and selections

03-summarise-data/
    Histograms and cutflows

04-save-data/
    Skims and outputs

05-systematics/
    Variations and uncertainties

06-organise-workflows/
    Profiles, registries, and modular workflows

07-scale-execution/
    Distributed execution and resource pools

08-accelerators/
    GPU execution

09-extend-fasthep/
    Custom operations and extensions

10-complete/
    End-to-end analysis examples

Start here:

tutorials/00-overview/first-workflow/

Running a Tutorial

Most tutorials contain a dedicated README with instructions.

For example:

pixi run fasthep compile tutorials/00-overview/first-workflow/author.yaml

or:

pixi run fasthep run tutorials/00-overview/first-workflow/author.yaml

See the tutorial README for expected outputs and explanations.

Expected Tutorial Outputs

Expected tutorial outputs are documentation fixtures, not full build snapshots. They are synced with per-tutorial expected/manifest.yaml files:

pixi run python scripts/sync_expected.py tutorials/03-summarise-data/04-cutflow-tables --build build/tutorials/03-summarise-data/04-cutflow-tables

Manifests copy only curated outputs such as plots, small tables, and compact JSON snippets into expected/.

Example Data

Several tutorials use small CMS datasets based on the classic Z → μμ analysis.

Download the tutorial files:

pixi run fasthep download tutorials/data/CMS/Zmumu/files.json --outdir data

The downloaded files are intentionally small so that tutorials can run on a laptop.

Output Structure

FAST-HEP workflows write outputs into a build directory.

Typical contents include:

build/
├── artifacts/
├── compile/
├── debug/
├── graph/
├── render/
└── reports/

• compile/ – compiler outputs such as normalized workflows and execution plans
• graph/ – workflow visualisations
• render/ – rendering metadata
• reports/ – structured reports and summaries
• artifacts/ – user-facing outputs
• debug/ – backend and runtime diagnostics

Next Steps

After completing the introductory tutorials, explore:

• distributed execution with HTCondor or Slurm,
• heterogeneous CPU/GPU worker pools,
• skimming workflows,
• complete analysis examples.

📝 The long-term goal is to build fully reproducible public analysis records using FAST-HEP.