DTCS — Data Transformation Contract Standard

Vendor-neutral contracts for data transformation semantics — describe what a transformation means without locking you to Spark, SQL, Polars, or any single runtime.

This repository contains:

• SPEC.md — normative DTCS 1.0 draft (26 chapters)
• Reference tools — parse, validate, and analyze contracts in Rust and Python

Spec status	Draft (1.0.0-draft)
Reference implementation	0.4.0 — validation, analysis, and registries
Document dtcsVersion	1.0.0 (accepted for compatible 1.0.x releases)
Try it now	pip install dtcs or cargo install dtcs

What you can do today: validate YAML/JSON contracts, resolve dtcs: identifiers through the embedded registry, compare versions for compatibility, analyze evolution between revisions, and trace dataset lineage — all read-only, no execution engine required.

Quick start · User docs · Examples · Changelog · Roadmap

Install

Requirements: Python 3.9+ (PyPI package); Rust 1.75+ (cargo install or building from source).

pip install dtcs
cargo install dtcs

dtcs version
dtcs validate examples/customer_normalize.dtcs.yaml

Both packages install the dtcs CLI on PATH:

validate · inspect · diagnostics · compat · evolve · lineage · registry · version

Develop from source (requires Rust + maturin): see CONTRIBUTING.md.

Quick start

# Validate a contract (exit 0 = valid)
dtcs validate examples/customer_normalize.dtcs.yaml

# Human-readable summary
dtcs inspect examples/customer_normalize.dtcs.yaml

# Compare two contract versions
dtcs compat examples/analysis/backward_old.yaml examples/analysis/backward_new.yaml

# Trace lineage impact
dtcs lineage examples/analysis/lineage_multi.yaml --impact customers

# Resolve a standard identifier
dtcs registry resolve dtcs:lowercase

import dtcs

report = dtcs.parse_and_validate(
    open("examples/customer_normalize.dtcs.yaml", "rb").read()
)
assert dtcs.is_valid(report)

Read docs/user/getting-started.md for a full walkthrough. For normative definitions, see SPEC.md — start with Chapter 3 (COM) and Chapter 9 (Validation).

Pipeline

The reference implementation through Phase 0.4:

DTCS Document
        │
        ▼
Parser → Canonical Object Model
        │
        ├──────────────────────────────┐
        ▼                              ▼
Validator (0.1–0.4)              Analyzer (0.3)
        │                              │
        │  registry::resolve           ├─ compatibility::analyze
        ▼                              ├─ analyze_evolution
Diagnostics                            ├─ versioning::validate
        │                              └─ lineage::analyze
        │                              │
        │                              ▼
        │                         Analysis reports
        ▼
   (valid contracts only for analysis)

Phase 0.2 adds metadata validation, extended type system checks, expression typing, and I/O interface depth. Phase 0.3 adds compatibility classification, evolution analysis, versioning validation, and dataset-level lineage analysis. Phase 0.4 adds the identifier registry, file/URI loading with offline cache, and registry-aware extension validation.

Execution, backend compilation, and runtime behavior remain out of scope. See docs/implementation/non-goals.md.

Repository layout

Path	Purpose
SPEC.md	Full DTCS 1.0 draft specification (26 chapters)
docs/user/	User guides — getting started, CLI, compatibility
docs/adoption/	Adoption overview for evaluators
docs/implementation/	Reference implementation design guides
docs/editorial/	Specification authoring process
examples/	Sample transformation contracts
src/	Rust crate source (dtcs)
python/	Python package source (dtcs on PyPI)
tests/	Integration tests and fixtures
ROADMAP.md	Reference implementation milestones

Contributing

See CONTRIBUTING.md for editorial conventions, implementation guidelines, and the review process.

When implementation guidance conflicts with the specification, SPEC.md wins. See docs/implementation/spec-usage.md.

License

Licensed under the Apache License, Version 2.0. See LICENSE.