offchain 0.2.2

Open source metadata processing framework

offchain

Documentation | Zora API

---

offchain is a library for parsing NFT metadata. It's used by Zora's indexer & API. It can handle metadata of many standards (OpenSea, ZORA, Nouns), hosted in many places (ipfs, http, dataURIs), and normalize them into a consistent format.

Our goal with this project is to democratize access to NFT metadata.

pip install offchain

from offchain import MetadataPipeline, Token

pipeline = MetadataPipeline()
token = Token(
    collection_address="0x5180db8f5c931aae63c74266b211f580155ecac8",
    token_id=9559
)
metadata = pipeline.run([token])[0]

metadata.name               # -> 'antares the improbable'
metadata.description        # -> 'You are a WITCH who bathes in the tears of...'
metadata.standard           # -> OPENSEA_STANDARD
metadata.attributes         # -> [Attribute(trait_type='Skin Tone', ...]
metadata.image              # -> MediaDetails(size=2139693, sha256=None, uri='https://cryptocoven.s3.amazonaws.com/2048b255aa1d02045eef13cdd7100479.png', mime_type='image/png')
metadata.additional_fields  # -> [MetadataField(...), ...]

See documentation for more examples and tutorials.

Contributing

We welcome contributions that add support for new metadata standards, new ways of retreiving metadata, and ways of normalizing them to a consistent form. We are commited to integrating contributions to our indexer and making the results available in our API.

You should be able to contribute a new standard for metadata, and have NFTs that adhere to that metadata standard be returned correctly from queries to api.zora.co. We hope this helps to foster innovation in how NFTs are represented, where metadata is stored, and what is expressed in that metadata.

Features

• Multiple metadata standards: represent metadata any way you wish
• Multiple transport protocols: store metadata where you want
• Composible for custom applications: only parse the standards you care about
• Future proof: extensible to new formats, locations, etc. The more gigabrain the better.

Development

This project is developed using Python 3.9. Here's a recommended setup:

Poetry

This project uses poetry for dependency management and packaging. Install poetry:

curl -sSL https://install.python-poetry.org | python3 -

Setup

poetry install

Pre-commit

Pre-commit runs checks to enforce coding standards on every commit

pip install pre-commit  # into global python path
pre-commit install

Testing

poetry run python -m pytest tests/

Documentation

This project uses mkdocs and mkdocs-material for documentation.

poetry run mkdocs serve