smartjoin-py 0.1.1

Deterministic relationship discovery for structured datasets.

smartjoin: data relationship discovery in seconds

Stop guessing how your tables connect - smartjoin automatically discovers relationships between structured datasets — no schema, no docs, no manual SQL detective work.

When working with unfamiliar datasets, one of the hardest problems is understanding how files relate to each other.

smartjoin helps by scanning structured datasets, identifying candidate relationships, producing explainable outputs instead of opaque guesses and giving you an explorer to inspect and review the results.

Quickstart

Installation

pip install smartjoin-py

Run

smartjoin run <path> <out_dir>

This analyzes the structured datasets in <path> and writes results to <out_dir>.

Generate test datasets

To explore how smartjoin works, you can generate synthethic test datasets:

smartjoin generate-test-datasets --output-dir <output-dir>

Explorer

In addition to the output files, smartjoin generates an interactive HTML-based explorer that helps you inspect detected relationships visually.

Limitations

smartjoin identifies candidate relationships across structured datasets. It does not guarantee semantic correctness.

Please keep in mind:

• inferred relationships should be reviewed before being relied on downstream
• domain-specific meaning may still require human interpretation
• output quality depends on the quality, consistency, and structure of the input data
• the tool is intended for structured dataset analysis, not as a general-purpose data processing platform

Currently supported input formats include: .csv, .xlsx, .json, .parquet.

Roadmap

Future development may include:

• stronger semantic matching across columns and tables
• optional AI-assisted reasoning and scoring
• improved explorer and debugging capabilities
• broader support for real-world edge cases and heterogeneous datasets

Contributing

See CONTRIBUTING.md.

License

Licensed under the MIT License