PyGraphDB Documentation

PyGraphDB is a pure Python graph database toolkit for attributed graphs. It stores nodes, edges, adjacency lists, and typed adjacency indexes on key-value backends such as LMDB and LevelDB.

The documentation focuses on practical examples: creating graphs, choosing a backend, serializing properties, traversing typed edges, and sampling subgraphs.

User Guide

• Installation
  • Python Version
  • Install With uv
  • Install With pip
  • Install From GitHub
  • Notebook Kernel Example
  • Optional Dependencies
  • Pre-Release Installs
• Quickstart
  • Create a Graph
  • Bulk Insert Edges
  • Fetch Nodes in Bulk
  • Labels and Exact-Match Indexes
  • Columnar Ingestion
  • Traverse With BFS
  • Query With Cypher
  • Use Stable IDs
• Storage Backends
  • LMDB Backend
  • LevelDB Backend
  • RocksDB Backend
  • Sorted Indexes
  • Backend Selection Pattern
  • Cleanup
• Serializers
  • Pickle Serializer
  • JSON Serializer
  • MessagePack Serializer
  • Protobuf Serializer
  • Using a Serializer With GraphDB
• Typed Traversal and Sampling
  • Create a Typed Graph
  • Query Typed Neighbors
  • Query Typed Edges
  • Sample Neighbors
  • Object-Based Sampling Patterns
  • Dictionary-Based Sampling Patterns
  • Cypher Sampling Procedure
  • Sample a Materialized Subgraph
  • Rebuild Typed Adjacency
• Cypher Queries
  • Supported Feature Matrix
  • Indexed Label Scans
  • Indexed Label and Property Lookup
  • Property Projections and Limits
  • Anchored One-Hop Traversal
  • Relationship Variables
  • Anchored Multi-Hop Traversal
  • Reverse and Undirected Traversal
  • Sampling Procedure
  • Current Cypher Limitations
• Performance and RocksDB Tuning
  • Install Optional Dependencies
  • Run Backend Benchmarks
  • Tune RocksDB
  • Benchmarks
  • Columnar Ingestion Benchmark
  • Initial Local Findings
  • RocksDB Knobs Exposed by PyRexStore
• ArcadeDB vs PyGraphDB Benchmarks
  • Benchmark Setup
  • Overall Results
  • Ingestion Results
  • Query Results
  • Interpretation
  • Important Caveats
• Notebook Usage
  • Choose the Correct Kernel
  • Minimal Notebook Cell
  • Close Stores Between Runs
  • Troubleshooting plyvel

API Reference

• API Reference
  • Graph Models and Database
  • Sampling Configuration
  • Columnar Ingestion
  • Cypher Queries
  • Key-Value Stores
  • Serializers

Quick Example

from pygraphdb.graphdb import Edge, GraphDB, Node
from pygraphdb.kvstores import LMDBStore
from pygraphdb.serializers import PickleSerializer

graph_db = GraphDB(LMDBStore(path="graph_lmdb_example"), PickleSerializer())

alice = Node(node_id="alice", properties={"kind": "person"})
bob = Node(node_id="bob", properties={"kind": "person"})
graph_db.put_node(alice)
graph_db.put_node(bob)

graph_db.put_edge(Edge(
    edge_id="alice-knows-bob",
    source="alice",
    target="bob",
    properties={"type": "knows", "since": 2024},
))

print(graph_db.get_node(b"alice").properties)
print(graph_db.neighbors_by_edge_type("alice", "knows", direction="out"))

graph_db.close()