linkml-runtime
Runtime environment for LinkML, the Linked open data modeling language
Decision gist · record as of 2026-08-14
Yes, if you are using LinkML to generate Python dataclasses from schemas. This package is a required dependency for any generated model to work. It is actively maintained, has low install friction, carries a permissive license, and has no known security vulnerabilities. Install it as part of your LinkML workflow.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; designed to work with dataclasses generated by the LinkML schema compiler.
- Low install friction with a pure-Python wheel and active maintenance status.
- The package carries 14 runtime dependencies including jsonschema, pydantic, rdflib, and requests, which are all widely-used libraries.
License · maintenance · safety
CC0-1.0 (permissive) — Licensed under CC0-1.0 (public domain equivalent), permissive treatment means you can use, modify, and distribute this package with minimal restrictions.
last release 2026-05-20 (86 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 466,751 downloads/mo, #6,502 on PyPI
Alternatives
Verify before relying
pip install linkml-runtime
from linkml_runtime.loaders import yaml_loader
from linkml_runtime.dumpers import yaml_dumper
# Load YAML data into a LinkML-generated dataclass instance
instance = yaml_loader.load(yaml_string, MyDataClass)
# Dump instance back to YAML
output = yaml_dumper.dumps(instance)- Whether the package is actively maintained by the LinkML project or community-driven; maintenance.status shows 'active' but repo metadata is unavailable.
- Performance characteristics when handling large RDF graphs or deeply nested YAML structures.
- Whether all 14 runtime dependencies are always required or if some are optional for specific loaders/dumpers.
What it is and what it does
linkml-runtime is the companion library for LinkML, a linked data modeling language. When you use LinkML's schema compiler to generate Python dataclasses from a schema definition, those generated classes depend on this package to function. It provides the machinery to load data from external formats (JSON, YAML, RDF, TSV) into your generated dataclass instances and dump them back out, making it easy to work with structured data that conforms to a LinkML schema.
The package also bundles the Python representation of the LinkML metamodel itself and includes SchemaView, a utility for programmatically inspecting and manipulating LinkML schemas. It's designed for developers building data pipelines, knowledge graphs, or domain-specific data systems where schema-driven serialization and deserialization are central to the workflow.
Use it for
- Load YAML or JSON configuration files into strongly-typed Python objects generated from a LinkML schema.
- Convert RDF data into Python dataclass instances for easier manipulation in application code.
- Serialize Python objects back to JSON, YAML, or RDF for storage or downstream processing.
- Programmatically inspect and validate LinkML schemas using SchemaView for code generation or documentation.
- Build data pipelines that move data between multiple formats (TSV, JSON, RDF) while maintaining schema compliance.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are using LinkML to generate Python dataclasses from schemas.
This package is a required dependency for any generated model to work. It is actively maintained, has low install friction, carries a permissive license, and has no known security vulnerabilities. Install it as part of your LinkML workflow.
Install
linkml-runtime on PyPI
Before you install
Low install friction with a pure-Python wheel and active maintenance status. The package carries 14 runtime dependencies including jsonschema, pydantic, rdflib, and requests, which are all widely-used libraries.
Requires Python 3.10 or later; designed to work with dataclasses generated by the LinkML schema compiler.
License in practice
Licensed under CC0-1.0 (public domain equivalent), permissive treatment means you can use, modify, and distribute this package with minimal restrictions.
Quickstart
pip install linkml-runtime
from linkml_runtime.loaders import yaml_loader
from linkml_runtime.dumpers import yaml_dumper
# Load YAML data into a LinkML-generated dataclass instance
instance = yaml_loader.load(yaml_string, MyDataClass)
# Dump instance back to YAML
output = yaml_dumper.dumps(instance)Verify before relying
- Whether the package is actively maintained by the LinkML project or community-driven; maintenance.status shows 'active' but repo metadata is unavailable.
- Performance characteristics when handling large RDF graphs or deeply nested YAML structures.
- Whether all 14 runtime dependencies are always required or if some are optional for specific loaders/dumpers.
Package facts
| License | CC0-1.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 14 packagesclickcuriesdeprecatedhbreaderisodatejson-flattenerjsonasobj2jsonschemaprefixcommonsprefixmapspydanticpyyamlrdflibrequests |
| Maintenance | Actively maintained 86 days since the last release |
| First released | |
| Downloads | 466,751 / month, #6,502 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/StableEnvironment :: ConsoleIntended Audience :: DevelopersIntended Audience :: Healthcare IndustryIntended Audience :: Science/ResearchProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: Software Development :: Libraries :: Python Modules |
Evidence: linkml_runtime-1.11.1-py3-none-any.whl
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See also linkml · dataclass-wizard · schema-salad · rdflib-jsonld · datafiles · ShExJSG · databind.json · databind · SPARQLWrapper · openjd-model