djprocess 0.0.1

Django process orchestration with paginated logs and async workers

djprocess

Django process orchestration with paginated logs and Celery workers.

Track long-running jobs in the database, stream structured log lines, and dispatch work to Celery workers.

Features

• Abstract BaseProcess and BaseProcessLog models with status lifecycle tracking
• Monotonic, paginated log lines per process
• Per-process timeout (default 20 minutes) enforced by a supervisor-queue watchdog
• Escalating kill: SIGTERM retries, then SIGKILL
• Pluggable worker backend (Celery included)
• Eager-mode Celery for fast tests and local development

Installation

pip install -e ".[dev]"

Quick start

1. Define models

from datetime import timedelta

from django.db import models
from djprocess.models import BaseProcess, BaseProcessLog


class ExportProcess(BaseProcess):
    path = models.CharField(max_length=255)

    def run(self):
        self.log(f"Exporting {self.path}")
        # ... do work ...
        self.log("Export complete")


class ExportProcessLog(BaseProcessLog):
    process = models.ForeignKey(
        ExportProcess,
        on_delete=models.CASCADE,
        related_name="logs",
    )

2. Configure Django and Celery

INSTALLED_APPS = [
    # ...
    "djprocess",
    "djprocess_celery",
]

CELERY_BROKER_URL = "redis://localhost:6379/0"
CELERY_RESULT_BACKEND = "redis://localhost:6379/0"

DJPROCESS_PROCESS_QUEUE = "processes"
DJPROCESS_SUPERVISOR_QUEUE = "supervisor"
DJPROCESS_KILL_TERM_RETRIES = 3
DJPROCESS_KILL_TERM_WAIT_SECONDS = 2

Create myproject/celery.py:

import os
from celery import Celery

os.environ.setdefault("DJANGO_SETTINGS_MODULE", "myproject.settings")

app = Celery("myproject")
app.config_from_object("django.conf:settings", namespace="CELERY")
app.autodiscover_tasks()

3. Run a process

process = ExportProcess.objects.create(path="/tmp/data.csv")
process.timeout = timedelta(minutes=45)  # optional, default is 20 minutes
process.start()  # dispatches process + per-job watchdog

page = process.paginate_logs(page=1, per_page=50)
for entry in page:
    print(entry.sequence, entry.level, entry.message)

Each start() schedules a watchdog on the supervisor queue with countdown=process.timeout_seconds(). Different processes can have different timeouts on the same worker pool.

4. Start workers

Use the prefork pool so Celery can terminate individual child processes:

celery -A myproject worker -Q processes -c 4 -P prefork -l info
celery -A myproject worker -Q supervisor -c 2 -P prefork -l info

Do not use worker-level --time-limit; timeouts are per process, not per worker.

Process lifecycle

Status	Meaning
pending	Created, not yet started
running	Worker is executing run()
succeeded	Finished without error
failed	Raised an exception
cancelled	Revoked before or during run
timed_out	Exceeded timeout and was killed

When the watchdog fires on a still-running process, it sends SIGTERM up to DJPROCESS_KILL_TERM_RETRIES times (waiting DJPROCESS_KILL_TERM_WAIT_SECONDS between checks), then SIGKILL. The supervisor task retries immediately if the control command itself fails.

Call process.start() to dispatch, process.cancel() to kill the process task and revoke the watchdog, and process.execute() directly when running synchronously in tests.

Worker backend

The default backend is djprocess_celery.backend.CeleryWorkerBackend. Override with:

DJPROCESS_WORKER_BACKEND = "myapp.backends.CustomWorkerBackend"

Your backend must implement:

• dispatch(process) -> (process_task_id, watchdog_task_id)
• kill(task_id) — escalating SIGTERM → SIGKILL
• revoke_scheduled(task_id) — cancel a not-yet-run watchdog

Development

python manage.py makemigrations
python manage.py migrate
pytest

Example app

This repository includes djprocess_example with ExampleProcess and test settings configured for in-memory Celery (CELERY_TASK_ALWAYS_EAGER = True).

License

MIT