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covalent

AgnostiqHQ/covalent

Pythonic tool for orchestrating workflows in diverse compute environments

GitHub Website

GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026

47views this month

868 stars113 forksLast push Aug 31, 2026 Python Apache-2.0

Decision brief

Covalent is designed for orchestrating workflows across multiple computing environments including machine learning, high-performance computing, and quantum computing using Python.

Good fit when

When developing machine-learning pipelines that must run in various heterogeneous compute environments.
If you require automation of high-performance computing tasks with a focus on Pythonic syntax.

Avoid when

In scenarios where the primary programming language is not Python, as Covalent heavily relies on its features and ecosystem for workflow development.
If your workflow orchestration needs are limited to a single compute environment without any requirement for cross-platform execution.

Observed Jul 17, 2026 · Source: enrich:decision_facts

covalent alternatives Trust report

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Maintenance and security

Full trust report

Maintenance: Active (19d since push); As of Sep 20, 2026
Provenance: Not a fork · Organization account; As of Sep 20, 2026
Security (OSV): No lockfile; As of Jul 15, 2026

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install covalent

PyPI

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

AgnostiqHQ/covalent offers functionality to orchestrate machine-learning, high-performance computing, and quantum-computing workflows across heterogeneous environments.

Capability facts

Deploy: Self-host
Source: dockerfile:Dockerfile · Sep 20, 2026
Docker: Dockerfile present
Source: dockerfile:Dockerfile · Sep 20, 2026
Languages: python
Source: github.language+pyproject.toml · Sep 20, 2026

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Sep 20, 2026)

Covalent is developed using Python on Linux and macOS. The easiest way to install Covalent is by using the PyPI pac

Source link

README

Installation Covalent is developed using Python on Linux and macOS. The easiest way to install Covalent is by using the PyPI package manager. For other methods of installation, please check the docs. Deployments <div Covalent offers flexible deployment options, from Docker image/...

For agents

This page has a .md twin and JSON over the API.

/tools/agnostiqhq-covalent.md GET /api/graphcanon/tools/agnostiqhq-covalent GET /api/graphcanon/graph?tool=agnostiqhq-covalent