petl-developers/petl
Python Extract Transform and Load Tables of Data observed · 2026-08-28
Health v2 · maintenance only
98/100
- Activity 98
- Release rhythm 98
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 10.5
- age_days: 5493
- days_rel: 14
- days_push: 14
- n_releases_24m: 9
Adoption not part of the score
1316 stars · 207 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
petl is a general-purpose Python package for extracting, transforming and loading tables of data. It provides a lightweight, pure-Python toolkit for reading, converting, and writing tabular data across formats like CSV, JSON, XML, and SQL databases.
Use cases
- convert csv files to
- clean and transform tabular data in python
- load data from csv into a sql database
- filter and sort rows in a large table
- join and merge datasets from different files
- extract transform load without pandas
- deduplicate records in a data file
When to choose
- you need lightweight pure-Python ETL without heavy dependencies
- you work with tabular data in many formats (csv, , xml, sql)
- you want lazy evaluation pipelines that handle large files
- you need simple data cleaning, sorting, joining, and conversion
When to avoid
- you need distributed or parallel processing at scale (use Spark/Dask)
- you want dataframe-style numeric analysis (use pandas)
- you need a full orchestration or scheduling ETL platform
Facets
library · maturity stable
etl csv data-science data-science files python cross-platform etl tables data-pipelines tabular-data data-engineering
2 sources
- readme: https://github.com/petl-developers/petl · fetched 2026-08-28 · 0ab0f63f9454
- registry_pypi: https://pypi.org/pypi/petl/json · fetched 2026-08-29 · cb9d9bdeb0d2
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| petl-developers/petl | main | 98 |
For agents
markdown · JSON · MCP: product_card(name="petl-developers/petl")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem