# IBM/Project_CodeNet

This repository is to support contributions for tools for the Project CodeNet dataset hosted in DAX

Repository: https://github.com/IBM/Project_CodeNet
Canonical: https://ross.abutalabs.com/products/project_codenet
Language: Python
License: Apache-2.0
License Family: permissive
Last push: 2025-12-21T15:39:13+00:00

## Health v2 (maintenance only)
Score: 49/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 58, release rhythm 8, longevity 100
- inputs: {"age_days": 1948, "days_push": 255, "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 1689, forks 203 (observed 2026-08-28T04:05:22.459213+00:00)

## What it is
Project CodeNet is a large-scale curated dataset of ~14 million code submissions across 50+ programming languages, built to support AI-for-Code research such as code search, summarization, completion, and code-to-code translation. This repository hosts tools and utilities in Python for accessing, selecting, and pre-processing the dataset, which is hosted on DAX.

## Use cases
- train machine learning models on source code
- build code-to-code translation models
- research code summarization and completion
- benchmark AI models for code understanding
- filter and preprocess large code corpora by language or problem
- study competitive programming submissions for AI research

## When to choose
- you need a large, diverse, curated dataset of code with metadata for AI-for-Code research
- you want benchmark problems with solutions in many programming languages
- you need Python tooling to access and preprocess code datasets

## When to avoid
- you need a production code analysis tool rather than a research dataset
- you want a small, clean dataset for quick experiments
- you need real-world production code rather than competitive programming submissions

## Facets
- artifact type: dataset
- maturity: stable
- function: machine-learning, nlp, data-science, parser
- domain: artificial-intelligence, machine-learning, programming-languages, education, developer-tools
- platform: python, cross-platform
- tags: ai-for-code, code-dataset, code-generation, code-translation, benchmark, competitive-programming

## Member repositories
- IBM/Project_CodeNet (main) score 49

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:22.459213+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 2026-08-30T03:38:39.851032+00:00, confidence not recorded.
  - readme: https://github.com/IBM/Project_CodeNet (fetched 2026-08-28T04:05:22.459213+00:00, sha 02e05f1da04d)
- Data as of 2026-08-30T08:39:29.467469+00:00.