django-graphify 0.1.1

Zero-LLM knowledge graph for Django projects — models, views, URLs, signals, serializers and more.

django-graphify

Zero-LLM knowledge graph for Django projects.
Inspect models, views, URLs, signals, serializers, admin classes, middleware and settings — all fully offline.

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Features

Feature	Detail
Zero LLM	No API keys, no internet required at runtime
Two-pass extraction	AST (always works) + Django introspection (richer data)
5 output formats	graph.json, graph.html, GRAPH_REPORT.md, graph.cypher, graph.mermaid
Interactive HTML	Force-directed graph, D3 v7 bundled inline — fully offline
All node types	Models, Fields, Views (CBV+FBV), URLs, Signals, Serializers, Admin, Middleware, Settings, Apps
Rich edges	FK, M2M, OneToOne, URL→View, View→Model, View→Serializer, Signal, Admin, App dependency
DRF support	Auto-detected if djangorestframework is installed
Single command	python manage.py graphify

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Installation

pip install django-graphify

Add to INSTALLED_APPS:

INSTALLED_APPS = [
    ...
    "django_graphify",
]

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Quick start

# Full project graph — all formats
python manage.py graphify

# Single app
python manage.py graphify --app orders

# Custom output dir
python manage.py graphify --out ./docs/graph

# Only json + html
python manage.py graphify --format json html

# Cleaner graph — skip field-level nodes
python manage.py graphify --no-fields

# Only EXTRACTED edges (skip inferred queryset links)
python manage.py graphify --skip-inferred

Output lands in ./graphify-out/ by default:

graphify-out/
├── graph.html         ← interactive force-directed graph (open in browser)
├── graph.json         ← queryable node/edge data
├── GRAPH_REPORT.md    ← god nodes, URL chains, signal wiring, orphans
├── graph.cypher       ← Neo4j import
└── graph.mermaid      ← Mermaid flowchart (paste into any renderer)

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Command reference

Option	Default	Description
--app APP_LABEL	all apps	Restrict to one Django app
--out DIR	./graphify-out	Output directory
--format FMT …	all	json html md cypher mermaid
--no-fields	off	Exclude field-level nodes
--skip-inferred	off	Only EXTRACTED edges
--no-offline	off	Use CDN for D3 instead of bundling

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Node types

Type	What it represents	Color
model	models.Model subclass	teal #1D9E75
field	Individual model field	light teal
view	CBV or FBV	purple #534AB7
url	path() / re_path() route	coral #D85A30
signal	Signal sender or receiver	pink #D4537E
serializer	DRF Serializer subclass	amber #BA7517
admin	ModelAdmin class	gray
middleware	Entry in MIDDLEWARE setting	blue #378ADD
app	Entry in INSTALLED_APPS	green #639922
setting	Top-level settings key	dark gray

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Edge types

Relation	Example	Tag
fk	Order.customer → User	EXTRACTED
m2m	Post.tags → Tag	EXTRACTED
one_to_one	Profile.user → User	EXTRACTED
url_to_view	/api/orders/ → OrderListView	EXTRACTED
view_to_model	OrderListView → Order	INFERRED
view_to_serializer	OrderListView → OrderSerializer	EXTRACTED
serializer_to_model	OrderSerializer → Order	EXTRACTED
signal_sender_receiver	post_save → send_welcome_email	EXTRACTED
admin_to_model	UserAdmin → User	EXTRACTED
app_dependency	INSTALLED_APPS order	EXTRACTED
model_has_field	Order → Order.status	EXTRACTED

Every edge is tagged EXTRACTED (found in source), INFERRED (confident guess), or AMBIGUOUS (needs review). INFERRED edges carry a confidence score (0–1).

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Python API

You can also drive extraction programmatically:

from pathlib import Path
from django_graphify.graph import GraphBuilder
from django_graphify.extractors import ModelExtractor, ViewExtractor
from django_graphify.exporters import JsonExporter, HtmlExporter

builder = GraphBuilder(project_name="myproject")
root = Path("/path/to/project")

for ExtractorClass in [ModelExtractor, ViewExtractor]:
    extractor = ExtractorClass(root)
    nodes, edges = extractor.ast_extract()
    builder.add_nodes(nodes)
    builder.add_edges(edges)
    nodes, edges = extractor.introspect()
    builder.add_nodes(nodes)
    builder.add_edges(edges)

JsonExporter(builder).export(Path("./out"))
HtmlExporter(builder).export(Path("./out"))

# Query
node = builder.get_node("orders.Order")
neighbours = builder.get_neighbours("orders.Order")
path = builder.shortest_path("orders.Order", "users.User")
gods = builder.god_nodes(top_n=5)
orphans = builder.orphan_nodes()

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graph.json schema

{
  "meta": {
    "project": "myproject",
    "django_version": "4.2.7",
    "generated_at": "2025-04-29T10:00:00Z",
    "node_count": 142,
    "edge_count": 89
  },
  "nodes": [
    {
      "id": "orders.Order",
      "type": "model",
      "label": "Order",
      "app": "orders",
      "file": "orders/models.py",
      "line": 14,
      "tag": "EXTRACTED",
      "confidence": 1.0,
      "meta": { "db_table": "orders_order", "abstract": false }
    }
  ],
  "edges": [
    {
      "source": "orders.Order",
      "target": "users.User",
      "relation": "fk",
      "tag": "EXTRACTED",
      "confidence": 1.0,
      "meta": { "field": "customer" }
    }
  ]
}

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How it works

Pass 1 — AST (always runs):
Uses Python's ast module to walk every .py file. No Django import required. Extracts class names, base classes, field assignments, decorators. Works even if the project can't be fully imported.

Pass 2 — Django introspection (runs when Django is configured):
Uses django.apps.apps.get_models(), django.conf.settings, and DRF's serializer registry to enrich Pass 1 nodes with concrete field types, FK targets, choices, related_name, middleware ordering, and installed app paths. Gracefully skipped if DJANGO_SETTINGS_MODULE isn't set.

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Requirements

• Python 3.10+
• Django 3.2+
• networkx >= 3.0
• djangorestframework (optional — DRF extraction auto-detected)

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Author

Yogesh Chauhan — AI and Django engineer, India.

GitHub | LinkedIn | Portfolio

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License

MIT — see LICENSE.