fastflowtransform 0.6.19

Python framework for SQL & Python data transformation, ETL pipelines, and dbt-style data modeling

FastFlowTransform

FastFlowTransform (FFT) is a SQL + Python data modeling engine with a deterministic DAG, level-wise parallelism, optional caching, incremental builds, auto-docs, and built-in data-quality tests. Projects are plain directories containing models, seeds, and YAML config; the fft CLI handles compilation, execution, docs, and validation across multiple execution engines.

Highlights

• SQL or Python models (*.ff.sql / *.ff.py) wired with ref() / source() / deps=[...].
• Executors for DuckDB, Postgres, BigQuery (pandas + BigFrames), Databricks/Spark, and Snowflake Snowpark.
• Level-wise parallel scheduler with cache fingerprints, rebuild flags, and state/result selectors.
• Incremental and materialized models with engine-specific merge/append hooks.
• Tests everywhere: schema/YAML checks, reconciliation rules, and fast model unit tests (fft utest).
• Docs on demand: fft dag --html and fft docgen generate a browsable site plus JSON artifacts; optional sync-db-comments to push descriptions to Postgres/Snowflake.
• HTTP helpers for Python models (fastflowtransform.api.http) and Jinja macros/config for templating.

Requirements

• Python 3.12+
• Engine extras installed only as needed (e.g. BigQuery, Snowflake, Spark/Delta, Postgres drivers). The core DuckDB path works out of the box.

Install & Quickstart

• Pick the engine extras you need (combine as pkg[a,b]):
  • DuckDB/core: pip install fastflowtransform
  • Postgres: pip install fastflowtransform[postgres]
  • BigQuery (pandas): pip install fastflowtransform[bigquery]
  • BigQuery (BigFrames): pip install fastflowtransform[bigquery_bf]
  • Databricks/Spark + Delta: pip install fastflowtransform[spark]
  • Snowflake Snowpark: pip install fastflowtransform[snowflake]
  • Everything: pip install fastflowtransform[full]
• Installation and first run: see docs/Quickstart.md (venv + editable install, DuckDB demo, and init walkthrough).
• CLI usage and flags: see docs/CLI_Guide.md.
• Makefile shortcut: make demo runs the simple DuckDB example end-to-end and opens the DAG (examples/simple_duckdb).

Docs & examples

• Docs hub: docs/index.md or https://fastflowtransform.com.
• Operational guide & architecture: docs/Technical_Overview.md.
• Modeling reference & macros: docs/Config_and_Macros.md.
• Parallelism, cache, and state selection: docs/Cache_and_Parallelism.md, docs/State_Selection.md.
• Incremental models: docs/Incremental.md.
• Data-quality + YAML tests: docs/Data_Quality_Tests.md, docs/YAML_Tests.md, docs/Unit_Tests.md.
• CLI details and troubleshooting: docs/CLI_Guide.md, docs/Troubleshooting.md.
• Runnable demos live under examples/ (basic, materializations, incremental, DQ, macros, cache, env matrix, API, events).

Contributing

Issues and PRs are welcome. See Contributing.md for development setup, testing (make demo, uv run pytest, fft utest), and code-style guidelines.

License

Apache 2.0 — see License.md.