tff-core
Core architectural linter and fitness function engine for data transformation pipelines.
tff-core executes layer boundary validation, structural graph policies, schema contracts, and duplicate logic detection across dbt, SQLMesh, and Google Cloud Dataform projects.
Installation
Install tff-core with the adapter corresponding to your transformation engine:
# dbt adapter
pip install "tff-core[dbt]"
# SQLMesh adapter
pip install "tff-core[sqlmesh]"
# Dataform adapter
pip install "tff-core[dataform]"
# All adapters
pip install "tff-core[all]"
Architecture
| Subsystem | Function & Scope |
|---|---|
| AST & Semantic Parser | Extracts AST nodes and semantic relationships using SQLGlot without database connections. |
| Check Registry | Unified execution harness evaluating layer integrity, syntax bans, and duplicate CTEs. |
| Health Scoring | Computes weighted quality metrics (0–100) and penalty distributions. |
| Adapter Interface | Normalizes project manifests and configurations across pipeline engines. |
Documentation
For CLI usage, configuration specifications, and rule authoring, refer to the main documentation and the tff repository.
Security & Trust Model
Trust model:
tffdynamically loads and executes custom Python linter rules from your project'slinter/directory (in SQLMesh projects) or configured plugin paths, and reads filesystem paths declared infitness_functions.yamland related JSON files (such as schema contract groups or exclusion files).Run
tffonly against repositories you trust, the same as you would runsqlmesh plan,dbt compile, ormake test. Do not runtff checkortff linton untrusted repositories without first reviewing project Python scripts and configuration files.
License
Distributed under the MIT License.
1 maintainer
Metadata
1 maintainer
Release files for tff-core 0.30.0
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| File | Size | Uploaded | Provenance | Actions |
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| tff_core-0.30.0-py3-none-any.whl | Python 3 | none | any | Details for tff_core-0.30.0-py3-none-any.whl |
Total release size: 1.2 MB
Release files / tff_core-0.30.0.tar.gz
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