--- language: - en license: apache-2.0 size_categories: - 100K=3.8`) | | `requires` | list[string] | Runtime dependencies | | `project_urls` | list[string] | Additional URLs (source, docs, tracker, etc.) | | `upload_time` | timestamp | UTC timestamp of when this release was uploaded | | `size` | int64 | Size of the distribution file in bytes | | `packagetype` | string | Distribution type: `sdist`, `bdist_wheel`, etc. | | `metadata_version` | string | Metadata specification version | | `recent_7d_downloads` | int64 | Total downloads in the most recent 7-day window | ## Usage ```python from datasets import load_dataset ds = load_dataset("semvec/pypi-packages") df = ds["train"].to_pandas() # Top 10 most downloaded packages df.sort_values("recent_7d_downloads", ascending=False).head(10)[["name", "summary", "recent_7d_downloads"]] ``` ## Example Use Cases - **Trend Analysis** — Track adoption of ecosystems (AI/ML, web frameworks, DevOps tooling) by filtering classifiers and plotting `upload_time` vs. cumulative package count. - **Package Classification / NLP** — Use `summary` and `description` to train text classifiers or summarization models that categorize packages by domain. - **Dependency Graph Research** — Parse `requires` to construct a directed dependency graph of the entire Python ecosystem. - **Popularity Modeling** — Predict `recent_7d_downloads` from metadata features like `requires_python`, `classifiers`, description length, and age. - **License Compliance** — Audit license diversity across the ecosystem and identify packages with missing or ambiguous license declarations. - **Author & Maintainer Analysis** — Study open-source contribution patterns, prolific authors, and package maintainer turnover over time. ## Data Collection Metadata was fetched from the [PyPI JSON API](https://pypi.org/pypi/{package}/json) for every package listed in the PyPI simple index. Download counts were sourced from the [PyPI public BigQuery dataset](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=pypi&page=dataset) (`bigquery-public-data.pypi.file_downloads`), aggregated over the 7 days preceding the collection date (February 2026). ## Citation If you use this dataset in your research, please cite it as: ``` @dataset{pypi_packages_2026, title = {PyPI Download and Package Analysis}, author = {semvec}, year = {2026}, url = {https://huggingface.co/datasets/semvec/pypi-packages}, license = {Apache-2.0} } ```