Metadata-Version: 2.1
Name: grand-graph
Version: 0.1.0
Summary: Graph database wrapper for non-graph datastores
Home-page: https://github.com/aplbrain/grand
Author: Jordan Matelsky
Author-email: opensource@matelsky.com
License: UNKNOWN
Description: <div align=center><img src="docs/grand.png" width=400 /></div>
        
        _Grand_ is a Rosetta Stone of graph technologies.
        
        ## Example use-cases
        
        -   True-serverless graph databases using DynamoDB\*
        -   Query a host graph in SQL for subgraph isomorphisms with DotMotif
        
        > \* [Neptune is not true-serverless.](docs/What-About-Neptune.md)
        
        ## Why it's a big deal
        
        _Grand_ is a Rosetta Stone of graph technologies. In short, a _Grand_ graph has a "Backend," which handles the nitty-gritty of talking to data on disk (or in the cloud), and an "Dialect", which is your preferred way of talking to a graph.
        
        For example, here's how you make a graph that is persisted in DynamoDB (the "Backend") but that you can talk to as though it's a `networkx.DiGraph` (the "Dialect"):
        
        ```python
        import grand
        
        G = grand.Graph(backend=grand.DynamoDBBackend())
        
        G.nx.add_node("Jordan", type="Person")
        G.nx.add_node("DotMotif", type="Project")
        
        G.nx.add_edge("Jordan", "DotMotif", type="Created")
        
        assert len(G.nx.edges()) == 1
        assert len(G.nx.nodes()) == 2
        ```
        
        It doesn't stop there. If you like the way IGraph handles anonymous node insertion (ugh) but you want to handle the graph using regular NetworkX syntax, use a `IGraphDialect` and then switch to a `NetworkXDialect` halfway through:
        
        ```python
        import grand
        
        G = grand.Graph()
        
        # Start in igraph:
        G.igraph.add_vertices(5)
        
        # A little bit of networkit:
        G.networkit.addNode()
        
        # And switch to networkx:
        assert len(G.nx.nodes()) == 6
        
        # And back to igraph!
        assert len(G.igraph.vs) == 6
        ```
        
        You should be able to use the "dialect" objects the same way you'd use a real graph from the constituent libraries. For example, here is a NetworkX algorithm running on NetworkX graphs alongside Grand graphs:
        
        ```python
        import networkx as nx
        
        nx.algorithms.isomorphism.GraphMatcher(networkxGraph, grandGraph.nx)
        ```
        
        ## Current Support
        
        <table><tr>
        <th>✅ = Fully Implemented</th>
        <th>🤔 = In Progress</th>
        <th>🔴 = Unsupported</th>
        </tr></table>
        
        | Dialect           | Description & Notes                            | Status |
        | ----------------- | ---------------------------------------------- | ------ |
        | `CypherDialect`   | Cypher syntax queries                          | 🔴     |
        | `DotMotifDialect` | DotMotif subgraph isomorphisms                 | 🤔     |
        | `IGraphDialect`   | Python-IGraph interface (no metadata)          | 🤔     |
        | `NetworkXDialect` | NetworkX-like interface for graph manipulation | ✅     |
        | `NetworkitDialect` | Networkit-like interface (no metadata)        | ✅     |
        
        | Backend           | Description & Notes                                 | Status |
        | ----------------- | --------------------------------------------------- | ------ |
        | `DynamoDBBackend` | A graph stored in two sister tables in AWS DynamoDB | ✅     |
        | `NetworkXBackend` | A NetworkX graph, in memory                         | ✅     |
        | `SQLBackend`      | A graph stored in two SQL-queryable sister tables   | ✅     |
        
        You can read more about usage and learn about backends and dialects in [the wiki](https://github.com/aplbrain/grand/wiki).
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
