cg

What it is and what it does

cg is a clinical sequencing platform developed at SciLifeLab that acts as a command center for genomic analysis workflows. It provides both HTTP REST APIs (powering the clinical.scilifelab.se web portal) and a command-line interface to automate interactions between sequencing tools and manage cross-tool communication. The package bundles a substantial dependency stack including Flask for the web layer, SQLAlchemy for data persistence, cryptography for secure operations, and specialized bioinformatics libraries like genologics for instrument integration.

The platform is designed to bridge multiple genomic analysis tools and expose their capabilities through unified interfaces. It runs on Python 3.11 or later and is actively maintained, with recent releases. The large runtime dependency footprint reflects its role as a full-stack system rather than a lightweight library, combining web serving, database management, authentication, and domain-specific genomics integration.

Use it for:

• Orchestrate multi-step clinical sequencing workflows across different bioinformatics tools and instruments.
• Expose genomic analysis capabilities via REST API for a web-based clinical reporting portal.
• Automate routine genomic data processing and sample tracking from the command line.
• Integrate with laboratory information systems and sequencing instruments via standardized APIs.
• Manage authentication and authorization for clinical genomics platforms using OAuth and cryptographic controls.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

cg is a clinical sequencing platform that provides REST APIs and CLI tools to orchestrate interactions between genomic analysis tools, exposing both HTTP endpoints for web portals and command-line interfaces for automation.

Yes, if you are operating a clinical genomics platform or integrating with SciLifeLab's infrastructure. The package is actively maintained, has no known vulnerabilities, and low install friction. However, verify the license terms before use, and note that it is tightly scoped to clinical sequencing workflows—not a general-purpose library. The Python version requirement and large dependency footprint make it suitable for dedicated backend deployment rather than lightweight embedding.

Install

cg on PyPI

pip install cg

uv add cg

poetry add cg

Installing cg

Before you install

Low install friction with a pure-Python wheel distribution. Active maintenance with a release within the last day. Requires Python 3.11 or later; the capped upper bound suggests compatibility testing against specific versions rather than forward compatibility.

License in practice

License status is unclear—no SPDX identifier or raw license text is available in the package metadata. Verify the actual license terms before using in proprietary or restricted contexts.

Quickstart

pip install cg

from cg import SomeModule  # Exact import depends on cg's public API
# Use CLI: cg --help

Requires Python 3.11 or later (not compatible with Python 3.13 or later). Intended for clinical genomics workflows; runtime dependencies include database (SQLAlchemy, PyMySQL), web framework (Flask stack), and bioinformatics tools (genologics).

Verify before relying

• Exact public API surface and recommended import patterns are not documented in the excerpt.
• Whether the package is intended for end-user installation or primarily as a backend service component.
• Specific genomic file formats and sequencing platforms supported by the orchestration layer.

Package facts

Evidence: cg-88.2.1-py3-none-any.whl

Tags

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