# blaze/odo

Data Migration for the Blaze Project

Repository: https://github.com/blaze/odo
Canonical: https://ross.abutalabs.com/products/odo
Homepage: http://odo.readthedocs.org/
Language: Python
License: BSD-3-Clause
License Family: permissive
Last push: 2022-07-15T21:57:09+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 4285, "days_push": 1510, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1006, forks 131 (observed 2026-08-28T04:03:11.809084+00:00)

## What it is
Odo is a Python library for migrating data between different containers, from in-memory structures like lists and pandas DataFrames to out-of-core stores like SQL databases, HDF5 files, and Spark. It uses a network of small conversion functions and finds the shortest path between source and target types.

## Use cases
- load a csv file into a pandas dataframe
- migrate data from hdf5 into a postgresql table
- convert between python data containers
- load csv into a sql database
- transfer data between different storage formats
- move data from s3 into redshift

## When to choose
- you need to move data between heterogeneous formats like CSV, SQL, HDF5, or Spark
- you want an extensible conversion system where you can register custom type conversions
- you work in the Blaze/pandas ecosystem and need out-of-core data transfers

## When to avoid
- you need a modern, actively maintained ETL tool - the project has not released since 2022 and targets legacy Python ecosystems
- you only need simple one-format parsing that a dedicated library handles better
- you need streaming or real-time data pipelines rather than batch migration

## Facets
- artifact type: library
- maturity: maintenance
- function: etl, serialization, database-driver, data-science
- domain: databases, data-science, big-data
- platform: python, cross-platform
- tags: data-migration, data-conversion, csv, hdf5, sql, blaze-project, out-of-core, data-engineering

## Member repositories
- blaze/odo (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:11.809084+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 2026-08-30T07:12:45.214329+00:00, confidence not recorded.
  - readme: https://github.com/blaze/odo (fetched 2026-08-28T04:03:11.809084+00:00, sha b35cac4a72b9)
  - homepage: http://odo.readthedocs.org/ (fetched 2026-08-29T13:12:58.704462+00:00, sha 263f00edf56a)
  - registry_pypi: https://pypi.org/pypi/odo/json (fetched 2026-08-29T13:12:58.715784+00:00, sha 6d5b5bed19af)
  - site_page: http://odo.pydata.org/en/latest/releases.html (fetched 2026-08-29T13:12:58.713573+00:00, sha 53731062b210)
- Data as of 2026-08-30T08:39:29.467469+00:00.