---
id: pydantic-tes
version: "0.4.0"
license: MIT
license_treatment: permissive
maintenance: active
---

# pydantic-tes — Pydantic Models for the GA4GH Task Execution Service

License: permissive · Maintenance: active · Downloads: 106.6K/mo

## What it is and what it does

pydantic-tes bridges Python applications to the GA4GH Task Execution Service specification by providing validated Pydantic data models for TES task definitions, requests, and responses. It includes a lightweight HTTP client built on requests that handles serialization and deserialization of TES objects, allowing developers to interact with any TES-compliant server using type-safe Python code.

The package is designed for bioinformatics and workflow automation contexts where tasks need to be submitted to and monitored on distributed execution systems. It requires pydantic, requests, and typing-extensions, making it a minimal addition to existing Python environments. The models enforce schema compliance automatically, reducing the risk of malformed requests to TES servers.

Use it for:

- Submit and monitor computational tasks to a GA4GH-compliant TES server from a Python workflow.
- Build a service that translates requests into validated TES task submissions.
- Test a TES implementation by generating and validating task payloads programmatically.
- Integrate task execution into a Python bioinformatics pipeline with schema validation.
- Work with Funnel or other TES implementations using type-safe Python models.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides Pydantic models and a lightweight HTTP client for the GA4GH Task Execution Service (TES) specification, enabling structured interaction with TES-compliant task execution systems.

Yes, if you need to interact with a GA4GH Task Execution Service from Python. The package is actively maintained, has no known vulnerabilities, requires only common dependencies, and enforces schema compliance through Pydantic. Install it only if you have a TES server to target; otherwise it provides no value.

## Install

pip install pydantic-tes
uv add pydantic-tes
poetry add pydantic-tes

## Installing pydantic-tes

Before you install: Low friction: pure Python wheel with three lightweight runtime dependencies (pydantic, requests, typing-extensions). Actively maintained as of 2026-04-13, requires Python 3.10 or later.

License in practice: MIT license permits unrestricted use, modification, and distribution with minimal attribution requirements—suitable for both open-source and proprietary projects.

Quickstart:

pip install pydantic-tes

from pydantic_tes import TESClient
client = TESClient(url='http://tes-server')
task = client.get_task(task_id='task-123')

Requires Python >=3.10; target TES server must be accessible at the provided URL.

Verify before relying:

- Whether the client supports all TES specification features or a specific subset.
- What authentication mechanisms the client supports beyond extra headers.
- Performance characteristics when working with large task lists or concurrent requests.
- Whether TESClient is the actual class name exported by the package.

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 106.6K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

GA4GH task execution service models, TES pydantic client, task execution service python, GA4GH TES API, pydantic TES models, task execution workflow, bioinformatics task service, bioinformatics, workflow-orchestration, ga4gh-standards

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