QCArchive

Overview

QCArchive is infrastructure for organizing quantum chemistry computation and its resulting data. The project describes a workflow spanning calculation execution, database storage, retrieval, analysis, sharing and export. Its stated design scope is thousands to millions of computations; this is a source-described target, not a benchmark result established by the source excerpts. For computational chemists, its role is to connect calculation execution with persistent access to the accumulated data.

The repository contains four distinct Python packages. qcfractal supplies the QCFractal server, including the database and web API. qcportal is the Python client used to interact with that server, while qcfractalcompute provides workers deployed to perform computations. qcarchivetesting contains helpers and pytest harnesses for testing QCArchive components. This separation makes the repository relevant to both client-side data access and deployment of the underlying computation infrastructure.

At the workflow level, QCArchive handles quantum chemistry computations and stores their data for subsequent use. The project README does not specify molecular input schemas, supported calculation engines, result fields or export formats, so those details need to be checked in the linked documentation before planning an integration. The packages share a monorepo because changes across components are closely coupled, although they retain separate package setup information. The available excerpts establish the architecture and repository installation route, but not deployment requirements or measured scaling performance.

Key Features

• QCFractal server combines a database with a web API for managing quantum chemistry computation data.
• `qcportal` provides a Python client for interaction with the server.
• `qcfractalcompute` supplies deployable workers that run computations.
• Stored computation data can be retrieved, shared, analyzed or exported.
• `qcarchivetesting` provides testing helpers and pytest harnesses for QCArchive components.
• A monorepo holds four closely related Python packages, each with its own package setup information.

Use Cases

• Intended evaluation: assess QCArchive as a database-backed execution and storage layer for a large collection of quantum chemistry calculations.
• Intended evaluation: use `qcportal` to assess retrieval of stored computation data for downstream scientific analysis.
• Intended evaluation: assess the server, worker and client packages together for a workflow that shares or exports accumulated calculation data.
• Intended evaluation: explore the supplied testing helpers when developing changes that span multiple QCArchive components.

How to Use

1. Start with the repository README to understand the four-package layout and decide whether your evaluation concerns client access, server deployment, worker execution or component testing.
2. Consult the official documentation for input representations, calculation setup and deployment guidance. These details are not included in the project README excerpt.
3. If installing from the repository, follow its documented pip installation instructions for qcportal, qcfractal, qcfractalcompute and qcarchivetesting. The README also gives an editable installation route for development.
4. Plan a small representative evaluation before considering the stated large-scale design scope. Check how computations enter the workflow, how workers execute them and how the client accesses stored data.
5. Evaluate retrieval, sharing or export against your intended analysis needs, and consult the code licence separately from any data or service terms.