FastAPI taskiq Dashboard
Run taskiq inside a FastAPI app and you have working background jobs. Run taskiq with z4j and you also have a dashboard, persistent history, the task controls this adapter can execute safely, scheduler integration, RBAC with invitations, and a tamper-evident audit log. z4j is one container or one Python process; the agent is one pip extra in your existing FastAPI venv.
FastAPI + taskiq is the most native pairing in the Python async ecosystem. taskiq mirrors FastAPI's dependency-injection style, the lifespan hooks line up naturally, and the z4j-taskiq adapter captures broker, worker, and result events without altering your task definitions.
Install z4j alongside FastAPI + taskiq
1. Install the brain
pip install z4j && z4j serveFirst boot prints a setup URL to stderr. Open it, create the first admin, and mint a token + HMAC secret for this agent.
2. Add the agent to your FastAPI venv
pip install z4j-fastapi[taskiq]3. Wire it into FastAPI
from fastapi import FastAPI
from z4j_fastapi import z4j_lifespan
app = FastAPI(lifespan=z4j_lifespan())What you get
- Persistent taskiq task history in Postgres or SQLite
- Adapter-advertised controls: submit_task
- Scheduler integration via taskiq scheduler; available controls depend on that scheduler adapter
- RBAC with invitations and password reset
- HMAC-chained tamper-evident audit log
- Notifications: email, Slack, Telegram, webhook
z4j-fastapi and z4j-taskiq are Apache 2.0. Importing them into your FastAPI app does not affect your application's licensing. z4j is AGPL-3.0-or-later, isolated in its own process.
What the dashboard can actually do
Native actions
-
submit_task
Event capture
Z4JTaskiqMiddleware: pre_send / pre_execute / post_execute / on_error.
Reconciliation
result_backend.is_result_ready() + get_result(). Works across every backend taskiq ships.
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Start using FastAPI taskiq Dashboard
Self-hosted, open source, no SaaS, no telemetry. z4j runs anywhere Python or Docker runs.