# pudo/dataset

Easy-to-use data handling for SQL data stores with support for implicit table creation, bulk loading, and transactions.

Repository: https://github.com/pudo/dataset
Canonical: https://ross.abutalabs.com/products/dataset
Homepage: https://dataset.readthedocs.org/
Language: Python
License: MIT
License Family: permissive
Topics: sql, database, python
Last push: 2026-07-22T12:53:43+00:00

## Health v2 (maintenance only)
Score: 78/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 93, release rhythm 47, longevity 100
- inputs: {"age_days": 4902, "days_push": 42, "days_rel": 143, "gap_med": null, "n_releases_24m": 1}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4871, forks 298 (observed 2026-08-28T04:09:01.656731+00:00)

## What it is
dataset is a Python library that makes reading and writing data in SQL databases as simple as working with JSON files. It provides implicit table creation, bulk loading, and transaction support on top of SQLAlchemy.

## Use cases
- store python dicts in a sql database without writing schema
- quickly persist scraped data to sqlite
- bulk load rows into a database table
- use a database as a simple key-value or document store
- prototype data pipelines without writing sql

## When to choose
- you want dead-simple database access in Python scripts
- you need implicit table creation and schema-free inserts
- you're building small ETL or data-loading utilities
- you want SQLAlchemy power without writing ORM models

## When to avoid
- you need fine-grained control over migrations and schema
- you're building a large application needing a full ORM
- you need high-performance bulk operations at massive scale
- you need NoSQL databases rather than SQL stores

## Facets
- artifact type: library
- maturity: stable
- function: database, orm, etl, serialization
- domain: databases, developer-tools
- platform: python, cross-platform
- tags: sqlalchemy, sql, lazy-database-access, bulk-loading, transactions, data-engineering

## Member repositories
- pudo/dataset (main) score 78

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:01.656731+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:18:19.092294+00:00, confidence not recorded.
  - readme: https://github.com/pudo/dataset (fetched 2026-08-28T04:09:01.656731+00:00, sha 393907d17ea1)
  - registry_pypi: https://pypi.org/pypi/dataset/json (fetched 2026-08-29T09:01:16.049092+00:00, sha 412072549306)
- Data as of 2026-08-30T08:39:29.467469+00:00.