docs/data-science/ocean.py

description
Python library to privately & securely publish, exchange, and consume data.

Ocean.py

Ocean.py helps data scientists earn $ from their AI models, track provenance of data & compute, and get more data. (More details here.)

Ocean.py makes these tasks easy:

• Publish data services: data feeds, REST APIs, downloadable files or compute-to-data. Create an ERC721 data NFT for each service, and ERC20 datatoken for access (1.0 datatokens to access).
• Sell datatokens via for a fixed price. Sell data NFTs.
• Transfer data NFTs & datatokens to another owner, and all other ERC721 & ERC20 actions using web3.

As a Python library, Ocean.py is built for the key environment of data scientists. It that can simply be imported alongside other Python data science tools like numpy, matplotlib, scikit-learn and tensorflow.

Quickstart 🚀

Follow these steps in sequence to ramp into Ocean.

1. Install Ocean 📥
2. Setup 🛠️
   • Remote (Win, MacOS, Linux)
   • or Local (Linux only)
3. Publish asset, post for free / for sale, dispense it / buy it, and consume it
4. Run algorithms through Compute-to-Data flow using Ocean environment.

After these quickstart steps, the main README points to several other use cases, such as Volume Data Farming, on-chain key-value stores (public or private), and other types of data assets (REST API, GraphQL, on-chain).