Datasets:

TheFinAI
/

ibm-project-codenet

dataset_info:
  features:
    - name: Source
      dtype: string
    - name: Date
      dtype: int64
    - name: Text
      dtype: string
    - name: Token_count
      dtype: int64
  splits:
    - name: train
      num_bytes: 8122744210
      num_examples: 6366648
  download_size: 3707767805
  dataset_size: 8122744210
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
pretty_name: Project_CodeNet
size_categories:
  - 1M<n<10M
task_categories:
  - text-generation
language:
  - code
license: other

Project_CodeNet

Overview

This dataset is constructed from the Project CodeNet corpus, consisting of competitive programming submissions collected from online judges.

We extract a large-scale code corpus designed for pretraining language models, with a focus on:

clean executable code
temporal metadata (submission time)
minimal preprocessing to preserve the original distribution

Dataset Statistics

Total samples: ~6.37M
Total tokens: ~3.06B
Average tokens per sample: 480.44

Token Length Distribution

P50: 162 tokens
P90: 679 tokens
P95: 1035 tokens
P99: 2702 tokens

Construction

Source

Project CodeNet https://github.com/IBM/Project_CodeNet

Filtering Rules

We apply the following steps:

Keep only Accepted submissions
- Removes incorrect or incomplete code.
Deduplication at metadata level
- For each (problem_id, user_id, language), keep the last accepted submission
- This approximates the user's final solution
No content-based deduplication
- Similar solutions across users are preserved
- Reflects real-world submission distribution
No balancing
- Language and temporal distributions are kept as-is

Fields

Each sample contains:

Field	Description
`Source`	Dataset name (`Project_CodeNet`)
`Date`	Submission year
`Text`	Source code
`Token_count`	Token count computed using `tiktoken`

Tokenization

Tokenizer: tiktoken
Encoding: cl100k_base

Distribution Characteristics

Language Distribution

The dataset is highly skewed toward C++:

C++ dominates (~60%)
Python is the second largest (~23%)
Other languages form a long tail

Temporal Distribution

The dataset is heavily concentrated in recent years:

Majority of samples from 2019–2020
Reflects real submission activity in CodeNet

Important Notes

This dataset preserves the original submission distribution of CodeNet.
It is not balanced across languages or time.
It is primarily composed of competitive programming code, which may differ from production software code.
Some level of near-duplicate solutions exists due to similar problem-solving strategies.

Intended Use

Pretraining code language models
Studying temporal evolution of programming patterns
Benchmarking under real-world distribution settings

Limitations

Not representative of general software engineering code
Strong bias toward:
- competitive programming tasks
- algorithmic problem solving
Language and temporal imbalance

License

Please refer to the original Project CodeNet dataset for licensing details.

Citation

If you use this dataset, please cite Project CodeNet:

@article{puri2021project, title={Project CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks}, author={Puri, Ruchir and others}, year={2021} }