metadata
language:
- en
license: apache-2.0
size_categories:
- 100K<n<1M
task_categories:
- tabular-classification
- text-classification
tags:
- pypi
- python
- software-engineering
- metadata
pretty_name: PyPI Download and Package Analysis
configs:
- config_name: default
data_files:
- split: train
path: packages_data/*.parquet
dataset_info:
features:
- name: metadata_version
dtype: string
- name: name
dtype: string
- name: version
dtype: string
- name: summary
dtype: string
- name: description
dtype: string
- name: description_content_type
dtype: string
- name: author
dtype: string
- name: author_email
dtype: string
- name: maintainer
dtype: string
- name: maintainer_email
dtype: string
- name: license
dtype: string
- name: keywords
dtype: string
- name: classifiers
sequence: string
- name: platform
sequence: string
- name: home_page
dtype: string
- name: download_url
dtype: string
- name: requires_python
dtype: string
- name: requires
sequence: string
- name: provides
sequence: string
- name: obsoletes
sequence: string
- name: requires_dist
sequence: string
- name: provides_dist
sequence: string
- name: obsoletes_dist
sequence: string
- name: requires_external
sequence: string
- name: project_urls
sequence: string
- name: uploaded_via
dtype: string
- name: upload_time
dtype: timestamp[us]
- name: filename
dtype: string
- name: size
dtype: int64
- name: path
dtype: string
- name: python_version
dtype: string
- name: packagetype
dtype: string
- name: comment_text
dtype: string
- name: has_signature
dtype: bool
- name: md5_digest
dtype: string
- name: sha256_digest
dtype: string
- name: blake2_256_digest
dtype: string
- name: license_expression
dtype: string
- name: license_files
sequence: string
- name: recent_7d_downloads
dtype: int64
PyPI Download and Package Analysis
A comprehensive snapshot of the Python Package Index (PyPI), covering 690,775 packages published from April 2005 through February 2026. Each row represents a published package release, enriched with full metadata from the PyPI API and recent download statistics from the PyPI BigQuery public dataset.
Dataset at a Glance
| Stat | Value |
|---|---|
| Total packages | 690,775 |
| Date range | April 2005 – February 2026 |
| Total 7-day downloads | ~13.3 Billion |
| Format | Parquet (15 shards) |
| License | Apache-2.0 |
Data Fields
| Field | Type | Description |
|---|---|---|
name |
string | Package name on PyPI (unique identifier) |
version |
string | Release version string (PEP 440) |
summary |
string | One-line description of the package |
description |
string | Full project description / README text |
description_content_type |
string | MIME type of the description (e.g. text/markdown) |
author |
string | Primary author name |
author_email |
string | Primary author email |
maintainer |
string | Maintainer name (if different from author) |
maintainer_email |
string | Maintainer email |
license |
string | License string as declared by the author |
keywords |
string | Space- or comma-separated keywords |
classifiers |
list[string] | PyPI trove classifiers (e.g. Programming Language :: Python :: 3) |
platform |
list[string] | Target platforms declared by the author |
home_page |
string | Project homepage URL |
download_url |
string | Direct download URL (if provided) |
requires_python |
string | Python version constraint (e.g. >=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
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_timevs. cumulative package count. - Package Classification / NLP — Use
summaryanddescriptionto train text classifiers or summarization models that categorize packages by domain. - Dependency Graph Research — Parse
requiresto construct a directed dependency graph of the entire Python ecosystem. - Popularity Modeling — Predict
recent_7d_downloadsfrom metadata features likerequires_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 for every package listed in the PyPI simple index. Download counts were sourced from the PyPI public BigQuery 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}
}