apscheduler by aiskillstore
Advanced Python Scheduler - Task scheduling and job queue system
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Updated Jan 19, 2026, 04:39 AM
Why Use This
This skill provides specialized capabilities for aiskillstore's codebase.
Use Cases
- Developing new features in the aiskillstore repository
- Refactoring existing code to follow aiskillstore standards
- Understanding and working with aiskillstore's codebase structure
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---
name: apscheduler
description: Advanced Python Scheduler - Task scheduling and job queue system
when_to_use: "Background task execution, periodic jobs, cron scheduling, distributed task processing"
tags: [scheduling, background-jobs, cron, async, task-queue]
---
# APScheduler
APScheduler is a flexible task scheduling and job queue system for Python applications. It supports both synchronous and asynchronous execution with multiple scheduling mechanisms including cron-style, interval-based, and one-off scheduling.
## Quick Start
### Basic Synchronous Scheduler
```python
from datetime import datetime
from apscheduler import Scheduler
from apscheduler.triggers.interval import IntervalTrigger
def tick():
print(f"Tick: {datetime.now()}")
# Create and start scheduler with memory datastore
with Scheduler() as scheduler:
scheduler.add_schedule(tick, IntervalTrigger(seconds=1))
scheduler.run_until_stopped()
```
### Async Scheduler with FastAPI
```python
from contextlib import asynccontextmanager
from fastapi import FastAPI
from apscheduler import AsyncScheduler
from apscheduler.triggers.interval import IntervalTrigger
def cleanup_task():
print("Running cleanup task...")
@asynccontextmanager
async def lifespan(app: FastAPI):
scheduler = AsyncScheduler()
async with scheduler:
await scheduler.add_schedule(
cleanup_task,
IntervalTrigger(hours=1),
id="cleanup"
)
await scheduler.start_in_background()
yield
app = FastAPI(lifespan=lifespan)
```
## Common Patterns
### Schedulers
**In-memory scheduler (development):**
```python
from apscheduler import AsyncScheduler
async def main():
async with AsyncScheduler() as scheduler:
# Jobs lost on restart
await scheduler.add_schedule(my_task, trigger)
await scheduler.run_until_stopped()
```
**Persistent scheduler (production):**
```python
from sqlalchemy.ext.asyncio import create_async_engine
from apscheduler import AsyncScheduler
from apscheduler.datastores.sqlalchemy import SQLAlchemyDataStore
async def main():
engine = create_async_engine("postgresql+asyncpg://user:pass@localhost/db")
data_store = SQLAlchemyDataStore(engine)
async with AsyncScheduler(data_store) as scheduler:
# Jobs survive restarts
await scheduler.add_schedule(my_task, trigger)
await scheduler.run_until_stopped()
```
**Distributed scheduler:**
```python
from apscheduler import AsyncScheduler, SchedulerRole
from apscheduler.datastores.sqlalchemy import SQLAlchemyDataStore
from apscheduler.eventbrokers.asyncpg import AsyncpgEventBroker
# Scheduler node - creates jobs from schedules
async def scheduler_node():
async with AsyncScheduler(
data_store,
event_broker,
role=SchedulerRole.scheduler
) as scheduler:
await scheduler.add_schedule(task, trigger)
await scheduler.run_until_stopped()
# Worker node - executes jobs only
async def worker_node():
async with AsyncScheduler(
data_store,
event_broker,
role=SchedulerRole.worker
) as scheduler:
await scheduler.run_until_stopped()
```
### Jobs
**Simple function jobs:**
```python
def send_daily_report():
generate_report()
email_report("[email protected]")
scheduler.add_schedule(
send_daily_report,
CronTrigger(hour=9, minute=0) # 9 AM daily
)
```
**Jobs with arguments:**
```python
def process_data(source: str, destination: str, batch_size: int):
# Data processing logic
pass
scheduler.add_schedule(
process_data,
IntervalTrigger(hours=1),
kwargs={
'source': 's3://incoming',
'destination': 's3://processed',
'batch_size': 1000
}
)
```
**Async jobs:**
```python
async def fetch_external_api():
async with aiohttp.ClientSession() as session:
async with session.get('https://api.example.com/data') as resp:
data = await resp.json()
await save_to_database(data)
scheduler.add_schedule(
fetch_external_api,
IntervalTrigger(minutes=5)
)
```
### Triggers
**Interval trigger:**
```python
from apscheduler.triggers.interval import IntervalTrigger
# Every 30 seconds
IntervalTrigger(seconds=30)
# Every 2 hours and 15 minutes
IntervalTrigger(hours=2, minutes=15)
# Every 3 days
IntervalTrigger(days=3)
```
**Cron trigger:**
```python
from apscheduler.triggers.cron import CronTrigger
# 9:00 AM Monday-Friday
CronTrigger(hour=9, minute=0, day_of_week='mon-fri')
# Every 15 minutes
CronTrigger(minute='*/15')
# Last day of month at midnight
CronTrigger(day='last', hour=0, minute=0)
# Using crontab syntax
CronTrigger.from_crontab('0 9 * * 1-5') # 9 AM weekdays
```
**Date trigger (one-time):**
```python
from datetime import datetime, timedelta
from apscheduler.triggers.date import DateTrigger
# 5 minutes from now
run_time = datetime.now() + timedelta(minutes=5)
DateTrigger(run_time=run_time)
# Specific datetime
DateTrigger(run_time=datetime(2024, 12, 31, 23, 59, 59))
```
**Calendar interval:**
```python
from apscheduler.triggers.calendarinterval import CalendarIntervalTrigger
# First day of every month at 9 AM
CalendarIntervalTrigger(months=1, hour=9, minute=0)
# Every Monday at 10 AM
CalendarIntervalTrigger(weeks=1, day_of_week='mon', hour=10, minute=0)
```
### Persistence
**SQLite:**
```python
engine = create_async_engine("sqlite+aiosqlite:///scheduler.db")
data_store = SQLAlchemyDataStore(engine)
```
**PostgreSQL:**
```python
engine = create_async_engine("postgresql+asyncpg://user:pass@localhost/db")
data_store = SQLAlchemyDataStore(engine)
event_broker = AsyncpgEventBroker.from_async_sqla_engine(engine)
```
**Redis (event broker):**
```python
from apscheduler.eventbrokers.redis import RedisEventBroker
event_broker = RedisEventBroker.from_url("redis://localhost:6379")
```
### Job Management
**Get job results:**
```python
async def main():
async with AsyncScheduler() as scheduler:
await scheduler.start_in_background()
# Add job with result retention
job_id = await scheduler.add_job(
calculate_result,
args=(10, 20),
result_expiration_time=timedelta(hours=1)
)
# Wait for result
result = await scheduler.get_job_result(job_id, wait=True)
print(f"Result: {result.return_value}")
```
**Schedule management:**
```python
# Pause schedule
await scheduler.pause_schedule("my_schedule")
# Resume schedule
await scheduler.unpause_schedule("my_schedule")
# Remove schedule
await scheduler.remove_schedule("my_schedule")
# Get schedule info
schedule = await scheduler.get_schedule("my_schedule")
print(f"Next run: {schedule.next_fire_time}")
```
**Event handling:**
```python
from apscheduler import JobAdded, JobReleased
def on_job_completed(event: JobReleased):
if event.outcome == Outcome.success:
print(f"Job {event.job_id} completed successfully")
else:
print(f"Job {event.job_id} failed: {event.exception}")
scheduler.subscribe(on_job_completed, JobReleased)
```
## Configuration
**Task defaults:**
```python
from apscheduler import TaskDefaults
task_defaults = TaskDefaults(
job_executor='threadpool',
max_running_jobs=3,
misfire_grace_time=timedelta(minutes=5)
)
scheduler = AsyncScheduler(task_defaults=task_defaults)
```
**Job execution options:**
```python
# Configure task behavior
await scheduler.configure_task(
my_function,
job_executor='processpool',
max_running_jobs=5,
misfire_grace_time=timedelta(minutes=10)
)
# Override per schedule
await scheduler.add_schedule(
my_function,
trigger,
job_executor='threadpool', # Override default
coalesce=CoalescePolicy.latest
)
```
## Requirements
```bash
# Core package
uv add apscheduler
# Database backends
uv add "apscheduler[postgresql]" # PostgreSQL
uv add "apscheduler[mongodb]" # MongoDB
uv add "apscheduler[sqlite]" # SQLite
# Event brokers
uv add "apscheduler[redis]" # Redis
uv add "apscheduler[mqtt]" # MQTT
```
**Dependencies by use case:**
- **Basic scheduling**: `apscheduler`
- **PostgreSQL persistence**: `asyncpg`, `sqlalchemy`
- **Redis distributed**: `redis`
- **MongoDB**: `motor`
- **SQLite**: `aiosqlite`
## Best Practices
1. **Use persistent storage** for production to survive restarts
2. **Set appropriate misfire_grace_time** to handle system delays
3. **Use conflict policies** when updating schedules
4. **Subscribe to events** for monitoring and debugging
5. **Choose appropriate executors** (threadpool for I/O, processpool for CPU)
6. **Implement error handling** in job functions
7. **Use unique schedule IDs** for management operations
8. **Set result expiration** to prevent memory leaks
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