absurd-sdk
Python SDK for Absurd - PostgreSQL-based durable task execution
What it is and what it does
Absurd SDK provides a Python interface to Absurd, a durable execution system built entirely on PostgreSQL. It lets you define long-running workflows as task functions that survive crashes, restarts, and network failures by decomposing work into recorded steps. Each step's result is persisted, so if a worker crashes mid-execution, the system can resume from the last completed step without duplicating work.
The SDK offers both synchronous and asynchronous APIs. You register tasks as decorated functions, define steps within them using either decorators (sync) or async/await patterns (async), and optionally wait for external events before proceeding. The system handles scheduling, retries, and state management automatically, requiring only a Postgres connection—no additional services, brokers, or infrastructure.
Use it for:
- Order fulfillment workflows that process payments, reserve inventory, await shipment events, and send notifications across multiple steps.
- Multi-step data pipelines where intermediate results must survive worker restarts and be resumable from the last completed stage.
- Scheduled background jobs with built-in retry logic and durability, replacing simpler queue systems when crash-safety is required.
- Event-driven workflows that pause execution to await external events (e.g., webhook callbacks) before resuming downstream steps.
- Parent-child task hierarchies where one task spawns and durably waits for results from child tasks without losing state.
Worth the install?
AI-flagged interpretation of the facts on this page — verify before relying
Python SDK for Absurd, a PostgreSQL-based durable task execution system that handles scheduling, retries, and long-lived workflows without requiring additional services beyond Postgres.
Yes. The package is actively maintained, has low install friction, carries no known vulnerabilities, and solves a real problem—durable task execution without external infrastructure—in a way that's genuinely simpler than multi-service alternatives if you already run Postgres. The alpha status reflects early maturity, but the recent release cadence and community interest (2335 stars) suggest it's production-ready for teams comfortable with that trade-off.
Install
absurd-sdk on PyPI
pip
pip install absurd-sdkuv
uv add absurd-sdkpoetry
poetry add absurd-sdkInstalling absurd-sdk
Before you install
Low install friction with a single runtime dependency (psycopg). Active maintenance with a recent release (10 days ago) and 2335 repository stars indicate ongoing development and community interest.
License in practice
Licensed under Apache-2.0 (permissive), allowing use in commercial and private projects with minimal restrictions.
Quickstart
pip install absurd-sdk
from absurd_sdk import Absurd
app = Absurd("postgresql://localhost/absurd")
@app.register_task(name="my-task")
def my_task(params, ctx):
@ctx.run_step("step-name")
def step_work():
return {"result": 42}
return step_work
app.start_worker()
Requires a running PostgreSQL database; connection URL can be set via ABSURD_DATABASE_URL, PGDATABASE environment variables, or passed explicitly.
Verify before relying
- Whether Postgres schema is automatically initialized on first connection or requires manual setup
- Performance characteristics and scalability limits for high-volume task workloads
- Retry policy configuration options and backoff strategies
- Support for task priorities or custom scheduling logic
Package facts
| License | Apache-2.0 (permissive) |
| Python support | supports the current Python release (>=3.9) |
| Install friction | low — pure-Python wheel |
| Runtime dependencies | 1 — psycopg |
| Maintenance | actively maintained — 10 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 157,058/month — #10,768 on PyPI (30-day window, as of 2026-08-14) |
| Known vulnerabilities | none known (OSV.dev, checked 2026-08-14) |
Evidence: absurd_sdk-0.5.0-py3-none-any.whl
Keywords: absurd, postgresql, queue, task, durable, workflow
Tags
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