# Networkxternal 0 3 0

> NetworkX-compatible interface for external memory MultiDiGraphs persisted in databases (SQLite, PostgreSQL, MySQL, MongoDB, Neo4J). Use when working with Terabyte-Petabyte graphs that won't fit into RAM, needing multi-edge support with key/label-based edge identity, or building graph applications requiring database-backed storage without changing application code.

- Skill: `tangledgroup/networkxternal-0-3-0` (Agent Skill, multi-file: 6 files)
- Install (CLI): `npx skillmds@latest add tangledgroup/networkxternal-0-3-0`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tangledgroup/networkxternal-0-3-0/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- License: MIT
- Author: tangledgroup (https://skillmd.com/u/tangledgroup)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tangledgroup/networkxternal-0-3-0

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# NetworkXternal 0.3.0

## Overview

NetworkXternal provides a NetworkX-like API for graphs persisted in external databases, enabling you to scale from megabyte-sized in-memory graphs to terabyte-petabyte graphs that exceed available RAM — without changing application code. It wraps five database backends (SQLite, PostgreSQL, MySQL, MongoDB, Neo4J) behind a unified `BaseAPI` abstract class partially compatible with NetworkX's `MultiDiGraph`.

The library is written in Python (98.6%), uses SQLAlchemy for ORM-based SQL backends, PyMongo for MongoDB, and the official Neo4J Bolt driver for Neo4J. It comes with a performance penalty compared to pure in-memory NetworkX, but provides a practical starting point for database-backed graph applications.

## When to Use

- Graphs too large to fit in RAM (terabyte to petabyte scale)
- Persistent graph storage across application restarts
- Multi-edge graphs where edges carry unique identity via key/label
- Migrating from in-memory NetworkX to database-backed storage with minimal code changes
- Applications needing concurrent read access to graph data (`__is_concurrent__ = True` on SQL, MongoDB, Neo4J backends)

## Core Concepts

**BaseAPI**: Abstract base class defining the graph interface. All backends inherit from it. Designed for directed weighted multigraphs by default. Supports multi-edges (multiple edges between same node pair). Edge IDs can be auto-generated by hashing connected node IDs using the Cantor pairing function.

**Node**: Dataclass with `_id: int`, `weight: float`, `label: int`, and `payload: dict`. Non-integer node names are hashed into integer IDs automatically.

**Edge**: Dataclass with `_id: int`, `first: int`, `second: int`, `weight: float`, `label: int`, `is_directed: bool`, and `payload: dict`. Supports tuple-like indexing (`edge[0]` returns `first`, `edge[1]` returns `second`) for NetworkX compatibility. Edge identity is deterministic via `Edge.identify_by_members(first, second)` using a modular Cantor pairing function.

**GraphDegree**: Simple dataclass holding `count: int` and `weight: float`, returned by reduction operations.

## Architecture

The library uses a two-tier architecture:

1. **BaseAPI** — abstract class defining all graph operations (metadata, bulk reads, random reads/writes, bulk operations)
2. **Backend implementations** — concrete classes for each database:
   - `BaseSQL` → `SQLite`, `SQLiteMem`, `PostgreSQL`, `MySQL` (SQLAlchemy-based)
   - `MongoDB` (PyMongo-based)
   - `Neo4J` (Bolt driver + Cypher-based)

SQL backends share a common `BaseSQL` parent that handles SQLAlchemy session management, ORM mapping (`NodeSQL`, `EdgeSQL`), and SQL query generation. MongoDB and Neo4J implement `BaseAPI` directly with database-specific query languages.

## Advanced Topics

**Core API Reference**: BaseAPI methods, Node/Edge dataclasses, GraphDegree → [Core API Reference](reference/01-core-api-reference.md)
**SQL Backends**: SQLAlchemy ORM mapping, SQLite pragmas, PostgreSQL optimizations, MySQL tuning → [SQL Backends](reference/02-sql-backends.md)
**MongoDB Backend**: PyMongo integration, aggregation pipelines, bulk operations → [MongoDB Backend](reference/03-mongodb-backend.md)
**Neo4J Backend**: Cypher queries, Bolt protocol, labels and constraints, CSV import → [Neo4J Backend](reference/04-neo4j-backend.md)
**Usage Examples**: Common patterns for each backend, data loading, querying → [Usage Examples](reference/05-usage-examples.md)