Metadata-Version: 2.4
Name: vbase
Version: 1.0.0
Summary: vBase Python Software Development Kit (SDK)
Author-email: vBase <tech@vbase.com>
License-Expression: Apache-2.0
Project-URL: Homepage, https://github.com/validityBase/vbase-py
Project-URL: Documentation, https://docs.vbase.com/
Project-URL: Issues, https://github.com/validityBase/vbase-py/issues
Keywords: vbase,blockchain,provenance,web3,sdk
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE.txt
License-File: NOTICE.txt
Requires-Dist: hexbytes>=0.3.1
Requires-Dist: numpy>=1.24.0
Requires-Dist: pandas>=2.0.0
Requires-Dist: python-dotenv>=1.0.0
Requires-Dist: requests>=2.31.0
Requires-Dist: web3==7.15.0
Requires-Dist: sqlmodel>=0.0.24
Requires-Dist: imageio
Requires-Dist: retry>=0.9.2
Dynamic: license-file

# vbase-py

vBase Python Software Development Kit (SDK)

- Python 3.8+ support

---

## License

This project is licensed under the Apache 2.0 License - see the [LICENSE.txt](LICENSE.txt) file for details.

## Introduction

vBase creates a global auditable record of when data was created, by whom, and how it has changed (collectively, “data provenance”). Data producers can prove the provenance of their data to any external party, increasing its value and marketability. Data consumers can ensure the integrity of historical data and any derivative calculations. The result is trustworthy information that can be put into production quickly without expensive and time-consuming trials.

Verifiable provenance establishes the credibility of data and calculations. For example, if you wish to prove investment skill, the recipient must be sure they are receiving a complete and accurate record of your timestamped trades or portfolios.

vBase resolves several expensive market failures common to financial data. Some of the areas that benefit include:
- Provably point-in-time datasets
- Auditable investing track records
- Sound backtests, historical simulations, and time-series modeling

vBase services do not require access to the data itself, assuring privacy. They also do not rely on centralized intermediaries, eliminating the technical, operating, and business risks of a trusted party controlling your data and its validation. vBase ensures data security and interoperability that is unattainable with legacy centralized systems. It does so by storing digital fingerprints of data, metadata, and revisions on secure public blockchains.

With vBase, creating and consuming provably correct data is as easy as pressing a button.

![Demo](https://github.com/validityBase/vbase-py/assets/153264511/4c658cdf-7287-4909-b2b2-94f2079d2d5a)

## Installation

Install the package from PyPI:

```bash
pip install vbase
```

See the [local installation](https://docs.vbase.com/getting-started/python-quickstart/local-installation) and the [cloud notebooks](https://docs.vbase.com/getting-started/python-quickstart/cloud-notebooks) guides to get started using vBase from Python.

## Development

Development and CI installs use generated requirements locks with pip
hash-checking mode:

```bash
python -m pip install --require-hashes -r requirements-dev.txt
python -m pip install --no-deps --no-build-isolation -e .
```

To update dependencies, edit the relevant `.in` file and regenerate the lock
file with `pip-compile --generate-hashes`. See
[internal/specs/python-dependency-hashes.md](internal/specs/python-dependency-hashes.md).
