pydantic-tes
Pydantic Models for the GA4GH Task Execution Service
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python >=3.10; target TES server must be accessible at the provided URL.
- 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 · maintenance · safety
MIT (permissive) — MIT license permits unrestricted use, modification, and distribution with minimal attribution requirements—suitable for both open-source and proprietary projects.
last release 2026-04-13 (123 days) · last repo commit 2026-04-13 · 2 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 106,593 downloads/mo, #12,648 on PyPI
Alternatives
Verify before relying
pip install pydantic-tes
from pydantic_tes import TESClient
client = TESClient(url='http://tes-server')
task = client.get_task(task_id='task-123')- 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.
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 on this page. Verify before relying on it.
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
pydantic-tes on PyPI
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.
Requires Python >=3.10; target TES server must be accessible at the provided URL.
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')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 the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagespydanticrequeststyping-extensions |
| Maintenance | Actively maintained 123 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 106,593 / month, #12,648 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14 |
Evidence: pydantic_tes-0.4.0-py3-none-any.whl
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See also pydantic-ai-todo · pydantic-ai-slim · fasta2a · openresponses-types · pydantic-graph · pydantic-ai · pydantic-function-models · scim2-models · pydantic_yaml · google-cloud-tasks