Show HN: HypergraphZ – directed hypergraph library in Zig with Python bindings
HypergraphZ is a directed hypergraph library developed in Zig, offering Python bindings for ease of use. It allows for complex relationships involving multiple vertices through hyperedges, making it suitable for various domains like academia, biology, and finance. The library includes a comprehensive algorithm suite and optimizes performance with bulk insertion capabilities.
- ▪HypergraphZ supports directed hyperedges, enabling functionalities like shortest-path queries and topological sorting.
- ▪The library includes a full algorithm suite, including BFS/DFS, PageRank, and centrality measures.
- ▪Pre-built wheels for installation are available across multiple operating systems, including Linux, macOS, and Windows.
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Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/yamafaktory/hypergraphz |
| Publication time | Sun, 17 May 2026 19:08:51 +0000 |
| Retrieval time | 2026-05-17T19:33:20.883Z |
| Last seen | 2026-05-17T19:33:20.883Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | ylhkOt_wfHBP |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
HypergraphZ A fast, directed hypergraph library written in Zig, with Python bindings included. In a regular graph an edge connects exactly two nodes. A hyperedge connects any number of vertices at once — making hypergraphs a natural fit wherever relationships involve more than two parties: Domain Vertices Hyperedges Academia researchers papers (all co-authors at once) Biology proteins complexes, metabolic pathways Chemistry molecules reactions (multiple reactants → products) Finance accounts transactions (split payments, settlements) Software packages commits, dependency sets Networks devices multicast groups, subnets Social people group chats, events, committees Knowledge concepts ontology relations, semantic clusters Logistics locations routes, shared shipments ML / AI features…
Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.