What is z4j?

z4j is a control plane for Python task infrastructure. It gives Django, Flask, FastAPI, and bare-Python applications a modern dashboard for Celery, RQ, Dramatiq, Huey, arq, and taskiq - with persistent history, unified actions (retry / cancel / bulk-retry / restart), schedule CRUD, HMAC-chained audit logging, and secure-by-default redaction - without touching your existing task code.

It is not a new task queue

z4j integrates with the queue you already run. If you’re on Celery today, stay on Celery. Install one pip package. The dashboard populates within seconds.

It is not a pitch to replace Flower

Flower is a Celery viewer. z4j is a control plane:

Observation - task events, worker state, schedule runs, error rates.
Action - retry, cancel, bulk-retry, restart, purge - on every engine.
Schedule CRUD - create/update/delete periodic tasks from the UI (on supported schedulers).
Persistent history - PostgreSQL-backed audit trail, survives broker restarts.
Multi-engine - run Celery + RQ in the same org without switching tools.

Mental model

┌──────────────────────────────┐
│          z4j-brain           │   FastAPI + React dashboard
│  (Postgres persistence +     │   + WebSocket server for agents
│   unified action surface)    │   AGPL v3
└──────────────▲───────────────┘
               │ WebSocket (outbound from your app)
               │
┌──────────────┴───────────────┐
│        z4j-<framework>       │   thin pip package you install in
│   + z4j-<engine> adapters    │   your app (Django/Flask/FastAPI/bare)
│                              │   Apache 2.0
└──────────────────────────────┘
               │
               ▼
   Celery / RQ / Dramatiq / …    your existing task code, unchanged

One sentence per feature

Feature	What it does
Task list	Every enqueue/start/success/retry/fail event across every engine, one timeline
Unified actions	Retry/cancel/bulk-retry behave the same on every engine - brain polyfills what the native API lacks
Schedule CRUD	Create, update, pause, delete periodic tasks (supported schedulers)
Audit log	HMAC-chained, tamper-evident. Every admin action, every auth event
RBAC	Project-scoped roles (owner / admin / operator / viewer) + multi-user invitations
Rate limits	Per-endpoint on every unauthenticated path
Reconciliation	Background worker reconciles “running forever” tasks against real engine state
Redaction	Secrets never leak to events - pattern-based + field-name heuristics

How do I install it?

Three paths, three audiences. Pick the one that matches what you are doing:

If you are…	Run
Evaluating (one-venv demo)	`pip install z4j` — gets brain + core in one command. AGPL-3.0.
Instrumenting a production app	`pip install z4j-<framework> z4j-<engine>` — agents only, Apache 2.0.
Running the brain in production	`docker run z4jdev/z4j` for the brain; agents via pip in the app.

See the install guide for the full breakdown of each path and their licence implications.