A web-based tool for exploring IPLD data structures and the Merkle Forest directly from your browser.
IPLD Explorer is a browser-based application that enables users to navigate and visualize IPLD (InterPlanetary Linked Data) structures, often referred to as the Merkle Forest. It provides an intuitive interface for interacting with content-addressed data on the IPFS network and understanding linked data relationships directly in a web browser without requiring local software installation.
Developers, researchers, and users working with IPFS and IPLD who need to explore, visualize, and understand content-addressed data structures and their relationships in a decentralized ecosystem.
Developers choose IPLD Explorer for its intuitive visual interface that simplifies navigating complex Merkle structures, its ability to query both local IPFS nodes and the broader network via Helia HTTP client, and its browser-based accessibility without installation requirements.
Explore the Merkle Forest from the comfort of your browser
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Fully browser-based, enabling users to explore IPLD structures without any local software installation, as highlighted in the key features for easy access.
Provides an intuitive visual interface that simplifies understanding complex Merkle structures and linked data relationships, making exploration accessible and user-friendly.
Features automatic language detection and a fallback translation system, seamlessly handled during the build process with Vite, as described in the translations section.
Uses the Helia HTTP client to query both local IPFS nodes and the broader IPFS network, offering flexible data access without requiring deep configuration.
Relies on UI components from the separate ipld-explorer-components repository, which can complicate updates, maintenance, and synchronization of changes.
Running the dev environment requires multiple shell sessions for the dev server, tests, and storybook, which may be inefficient and cumbersome for developers.
Depends on network queries via the Helia HTTP client, making it unsuitable for offline scenarios or slow with large datasets that require extensive loading.