kagglehub
Access Kaggle resources anywhere
Decision gist · record as of 2026-08-14
Yes. kagglehub is actively maintained, has low install friction, carries a permissive Apache 2.0 license, and no known vulnerabilities. Install it if you regularly work with Kaggle datasets or models and want to automate downloads in Python code. The native Kaggle notebook integration and multi-format dataset loading (pandas, Polars, Hugging Face) make it a natural choice for data science workflows.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Authentication requires a Kaggle account and API token (generated at https://www.kaggle.com/settings/api).
- Low friction installation with five runtime dependencies (kagglesdk, packaging, pyyaml, requests, tqdm).
License · maintenance · safety
permissive license (permissive) — Licensed under Apache License 2.0 (permissive). You can use, modify, and distribute the package freely in commercial and private projects, provided you include the license notice and document any changes.
last release 2026-06-09 (66 days) · last repo commit 2026-08-05 · 515 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 2,536,225 downloads/mo, #3,014 on PyPI
Alternatives
Verify before relying
pip install kagglehub
import kagglehub
# Authenticate (required for private/consent resources)
kagglehub.login()
# Download a model
kagglehub.model_download('google/bert/tensorFlow2/answer-equivalence-bem')
# Download a dataset
kagglehub.dataset_download('dataset-owner/dataset-name')- Whether optional dependencies (pandas, hugging-face, polars) are needed for specific use cases or if core functionality works without them
- Performance characteristics when downloading large models or datasets outside the Kaggle notebook environment
- Caching behavior and storage requirements for repeated downloads
What it is and what it does
kagglehub is a Python client library that simplifies downloading and uploading Kaggle resources—datasets, models, and notebook outputs—directly from your code. It wraps the Kaggle API and provides a straightforward interface for authentication and resource management.
The library behaves differently depending on where it runs: inside a Kaggle notebook, resources are automatically attached and served from Kaggle's shared cache; outside a notebook, files are downloaded to a local cache folder. It supports multiple authentication methods (API token, environment variable, config file, Google Colab secrets) and can load datasets directly into pandas, Hugging Face, or Polars objects via optional adapters. It also handles model uploads with versioning, licensing, and file-ignore patterns.
Use it for
- Download pre-trained models from Kaggle to use in local ML projects without manual browser downloads
- Load Kaggle competition datasets directly into pandas DataFrames or Polars for analysis in Jupyter notebooks
- Automate dataset and model retrieval in CI/CD pipelines or scheduled data processing workflows
- Upload trained models to Kaggle with version notes and licensing information for sharing with the community
- Access private or consent-gated Kaggle resources programmatically after authentication
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
kagglehub is actively maintained, has low install friction, carries a permissive Apache 2.0 license, and no known vulnerabilities. Install it if you regularly work with Kaggle datasets or models and want to automate downloads in Python code. The native Kaggle notebook integration and multi-format dataset loading (pandas, Polars, Hugging Face) make it a natural choice for data science workflows.
Install
kagglehub on PyPI
Before you install
Low friction installation with five runtime dependencies (kagglesdk, packaging, pyyaml, requests, tqdm). Repository is actively maintained with recent commits and moderate GitHub presence (515 stars). Requires Python 3.10 or later.
Requires Python 3.10 or later. Authentication requires a Kaggle account and API token (generated at https://www.kaggle.com/settings/api).
License in practice
Licensed under Apache License 2.0 (permissive). You can use, modify, and distribute the package freely in commercial and private projects, provided you include the license notice and document any changes.
Quickstart
pip install kagglehub
import kagglehub
# Authenticate (required for private/consent resources)
kagglehub.login()
# Download a model
kagglehub.model_download('google/bert/tensorFlow2/answer-equivalence-bem')
# Download a dataset
kagglehub.dataset_download('dataset-owner/dataset-name')Verify before relying
- Whether optional dependencies (pandas, hugging-face, polars) are needed for specific use cases or if core functionality works without them
- Performance characteristics when downloading large models or datasets outside the Kaggle notebook environment
- Caching behavior and storage requirements for repeated downloads
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 5 packageskagglesdkpackagingpyyamlrequeststqdm |
| Maintenance | Actively maintained 66 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 2,536,225 / month, #3,014 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3 |
Evidence: kagglehub-1.0.2-py3-none-any.whl
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See also athina-client · kaggle · kagglesdk · huggingface-hub · datasets · keras-hub · hf · spaces · wbdata · kedro-datasets