Prefect — Python Workflow Orchestration

What it is

Prefect is a Python workflow orchestration platform that lets you turn any Python function into a resilient, observable pipeline. Use @flow and @task decorators to add retries, caching, logging, and scheduling to existing code without rewriting it. Prefect provides a UI dashboard for monitoring runs, viewing logs, and managing schedules.

Data engineers, ML engineers, and backend developers who need reliable Python pipelines with observability use Prefect. It replaces cron jobs and manual scripts with structured orchestration.

How it saves time or tokens

Prefect adds orchestration features through decorators, so you keep your existing Python code and add resilience on top. The estimated token cost for this workflow is about 298 tokens. Automatic retries on failure, result caching across runs, and built-in scheduling replace custom retry logic, cache layers, and cron configuration.

How to use

1. Install Prefect:

pip install -U prefect

1. Define a flow:

from prefect import flow, task

@task(retries=3, retry_delay_seconds=10)
def extract_data(url: str) -> dict:
    import httpx
    return httpx.get(url).json()

@flow(log_prints=True)
def pipeline():
    data = extract_data('https://api.example.com/data')
    print(f'Got {len(data)} records')

pipeline()

1. Start the UI dashboard:

prefect server start
# Open http://localhost:4200

Example

from prefect import flow, task
from prefect.tasks import task_input_hash
from datetime import timedelta

@task(cache_key_fn=task_input_hash, cache_expiration=timedelta(hours=1))
def fetch_prices(symbol: str) -> list:
    import httpx
    resp = httpx.get(f'https://api.example.com/prices/{symbol}')
    return resp.json()

@task
def compute_average(prices: list) -> float:
    return sum(p['close'] for p in prices) / len(prices)

@flow
def price_analysis(symbol: str = 'AAPL'):
    prices = fetch_prices(symbol)
    avg = compute_average(prices)
    print(f'{symbol} average: {avg:.2f}')

price_analysis()

Related on TokRepo

• AI tools for automation — Workflow automation tools
• AI tools for coding — Developer tools and frameworks

Common pitfalls

• Using Prefect for real-time streaming. Prefect is designed for batch orchestration. For streaming, use tools like Apache Kafka or Flink.
• Not setting up a Prefect server for production. Running flows without a server loses observability. Always run prefect server start or use Prefect Cloud for production pipelines.
• Over-decorating functions with @task. Not every helper function needs to be a task. Use tasks for steps that benefit from retries, caching, or independent monitoring.