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quacc is an open-source Python framework for building and running computational materials science and quantum chemistry workflows. It organizes calculations as jobs and combines them into workflows called “flows,” with options to run locally, through a workflow manager on remote systems, or on HPC and cloud infrastructure you provide.
What quacc does
Pronounced “quack,” quacc is maintained by the Rosen Research Group at Princeton University. Built around the Atomic Simulation Environment (ASE), it supplies reusable recipes for computational workflows and a way to connect them into larger sequences. Its source repository identifies the software as BSD 3-Clause licensed. Project repository · Official project website
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In quacc’s terminology, an individual calculation is a job; a flow combines jobs into a workflow. The framework is an orchestration layer, not a quantum chemistry code or a source of compute capacity. You select and configure the calculator that performs the scientific calculation, then use quacc to organize and dispatch the work.
How jobs and flows fit together
A documented bulk_to_slabs_flow example begins with bulk copper, generates slabs, and runs slab relaxation and static calculations. Parameters can be set for an individual job or applied across jobs in a flow. This structure is useful when a research task naturally consists of dependent calculations and you want a reusable Python workflow rather than a sequence of manually repeated steps. Workflow documentation
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Run a simple workflow locally
A basic flow can run locally and serially, without a workflow engine. This is a straightforward way to learn how a recipe is configured and how jobs relate before introducing remote execution or parallel scheduling.
Use a workflow manager when needed
For parallel execution across one or more remote machines, quacc can work with workflow managers. The documentation also describes writing ordinary Python scripts and submitting them through a preferred machine and scheduler without a workflow engine. The choice is therefore not “quacc or scripts”: quacc workflows can be used with different execution approaches, including no engine at all. Workflow documentation · Official FAQ
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Which calculation codes and calculators work with quacc?
quacc recipes connect to external calculation codes and calculators. The official setup guide gives examples for DFTB+, EMT, Gaussian, ONETEP, ORCA, Psi4, Q-Chem, and Quantum ESPRESSO, and documents native support for several pre-trained machine-learned interatomic potentials. This list describes examples in the setup guide, not a claim that every code is bundled with quacc or ready to run without configuration. Calculator setup guide
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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchInstallation is calculator-specific. A setup may require an executable or separate package, command configuration, pseudopotentials, or other prerequisites. Follow the instructions for the particular calculator and confirm its availability in your environment. Because quacc is based on ASE, the FAQ also notes that users can add recipes for codes with an existing ASE Calculator even when quacc does not already provide a recipe for that code. Calculator setup guide · Official FAQ
Where calculations can run
The project describes local, HPC, and cloud execution, including combinations of those environments. quacc provides a consistent way to work with supported workflow-management solutions while also allowing engine-free scripts. It does not provide the machines, cluster access, cloud resources, or licenses for external codes: those must come from your own environment and software setup. Project repository · Workflow documentation · Official FAQ
How to choose a practical starting setup
- Choose the scientific calculator first. Identify the code or physical model appropriate to your research question, then check its setup requirements in the official calculator guide.
- Start from a documented recipe or flow. The guide uses EMT to demonstrate a materials workflow. Treat it as an example for learning the workflow mechanics, not as evidence that EMT is appropriate for every research problem. Workflow documentation
- Decide how jobs should be managed. For a small local run, begin with a serial flow or a Python script. Add a workflow manager if you need its supported remote or parallel execution features. Workflow documentation
- Match execution to available resources. Choose local machines, an HPC system, cloud resources, or a combination based on workload and access. Configure the relevant scheduler, calculator, and environment separately; quacc coordinates workflows rather than supplying compute capacity.
What quacc does not establish
The project documentation does not provide a general speedup or throughput figure that applies across workloads. Performance depends on the scientific calculation, calculator, hardware, and execution setup; a numeric efficiency claim needs a benchmark for the workload in question. The project’s NSF award number, OAC-2514141, is a funding identifier, not a performance measure. Project repository
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Citing quacc
For publications, the project repository directs users to cite quacc using DOI 10.5281/zenodo.7720998. Check the repository’s citation guidance for the format appropriate to your work.
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