aioskd is a powerful Python library designed to handle the execution of background tasks asynchronously and at scheduled intervals. It provides an efficient and flexible scheduler, making it effortless to integrate asynchronous background processing into your Python projects.
As applications grow more complex, certain tasks need to be executed in the background without affecting the responsiveness of the main application. AIOSKD is the perfect solution for such scenarios, as it allows you to offload these tasks to asynchronous workers, ensuring smooth execution and a better user experience.
- Asynchronous execution of background tasks
- Customizable scheduling of tasks at specified intervals
- Easy-to-use API for integrating with your Python projects
- Lightweight and efficient
You can install aioskd
using pip:
pip install aioskd
To get started, import the necessary modules and create an instance of the Scheduler
class:
from aioskd import Scheduler
skd = Scheduler()
You can schedule tasks using the schedule decorator as shown below:
import datetime
import asyncio
@skd.schedule(interval=datetime.timedelta(seconds=1))
async def task_one():
print("Task One - Hello world!")
await asyncio.sleep(2) # Simulate some async work taking 2 seconds
@skd.schedule(interval=datetime.timedelta(seconds=5))
async def task_two():
print("Task Two - I'm running every 5 seconds!")
await asyncio.sleep(1) # Simulate some async work taking 1 second
Alternatively, you can also register tasks without using decorators. Here's how you can do it:
import datetime
import asyncio
from aioskd import Scheduler
skd = Scheduler()
async def test_task(name: str, age: int = 25):
print(f"Hello {name} with age {age}")
skd.register_task(test_task, "John", age=30).schedule(interval=datetime.timedelta(seconds=5))
skd.register_task(test_task, "Alice", age=28).schedule(interval=datetime.timedelta(seconds=2))
In this example, the test_task function is registered with the scheduler using the register_task method. You can pass the function along with its arguments to register_task, and then schedule it with the desired interval using the schedule method.
To start the scheduler and run the scheduled tasks, you can use the run()
method:
skd.run()
If you want to run the scheduled tasks from the command line, you can use the following command:
skd path/to/file/with/tasks:obj_of_skd
import datetime
import asyncio
import aiohttp
from aioskd import Scheduler
skd = Scheduler()
@skd.schedule(interval=datetime.timedelta(minutes=30))
async def fetch_data():
url = "https://api.example.com/data"
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
if response.status == 200:
data = await response.json()
# Process and store the data as needed
print("Data fetched successfully!")
else:
print("Failed to fetch data. Status code:", response.status)
if __name__ == "__main__":
skd.run()
In this example, the fetch_data
task is scheduled to run every 30 minutes. It sends a request to an API to fetch data and then processes the response accordingly.
import datetime
import asyncio
import aiosmtplib
from email.message import EmailMessage
from aioskd import Scheduler
skd = Scheduler()
@skd.schedule(interval=datetime.timedelta(hours=24))
async def send_reminder_email():
email_content = "Hello! Just a friendly reminder that your appointment is tomorrow."
msg = EmailMessage()
msg.set_content(email_content)
msg["Subject"] = "Appointment Reminder"
msg["From"] = "[email protected]"
msg["To"] = "[email protected]"
async with aiosmtplib.SMTP("smtp.example.com", 587) as server:
await server.starttls()
await server.login("[email protected]", "your_email_password")
await server.send_message(msg)
if __name__ == "__main__":
skd.run()
This example schedules the send_reminder_email task to run once every 24 hours, sending a reminder email to a specified recipient about an upcoming appointment.
import datetime
import asyncio
import aiohttp
import aiosmtplib
from email.message import EmailMessage
from aioskd import Scheduler
skd = Scheduler()
async def get_weather_data(city: str) -> dict:
url = f"https://api.openweathermap.org/data/2.5/weather?q={city}&appid=YOUR_OPENWEATHERMAP_API_KEY"
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
data = await response.json()
return data
async def send_weather_email(city: str, recipient: str):
data = await get_weather_data(city)
temperature = data["main"]["temp"]
description = data["weather"][0]["description"]
email_content = f"Weather Update for {city}:\n\nTemperature: {temperature} °C\nDescription: {description}"
msg = EmailMessage()
msg.set_content(email_content)
msg["Subject"] = f"Weather Update for {city}"
msg["From"] = "[email protected]"
msg["To"] = recipient
async with aiosmtplib.SMTP("smtp.example.com", 587) as server:
await server.starttls()
await server.login("[email protected]", "your_email_password")
await server.send_message(msg)
print(f"Weather update email sent to {recipient}")
# Register tasks with different cities and recipients
task1 = skd.register_task(send_weather_email, "London", recipient="[email protected]")
task1.schedule(interval=datetime.timedelta(hours=1))
task2 = skd.register_task(send_weather_email, "New York", recipient="[email protected]")
task2.schedule(interval=datetime.timedelta(hours=2))
if __name__ == "__main__":
skd.run()
This code demonstrates the use of AIOSKD to send weather updates via email.
- interval:
datetime.timedelta
- The interval between which the asynchronous function should be executed.
- repeat:
bool
- A flag that indicates whether the asynchronous function should be repeated or executed only once. - If set to
True
, the function will be scheduled to run repeatedly at the specified interval. - If set toFalse
, the function will be executed only once.
- A flag that indicates whether the asynchronous function should be repeated or executed only once. - If set to
- immediate:
bool
- A flag that controls the first execution of the scheduled function. - If set to
True
, the scheduler will execute the function immediately when starting the task for the FIRST TIME, and subsequent executions will be based on the interval. - If set toFalse
, the first execution will wait for the interval before running.
- A flag that controls the first execution of the scheduled function. - If set to
- iter_count (optional):
int
- The necessary number of repeats. This parameter is applicable only when
repeat
isTrue
. - It specifies the maximum number of times the function should be repeated. - If not provided, the function will continue to be repeated indefinitely until the scheduler is stopped or the coroutine is cancelled.
- The necessary number of repeats. This parameter is applicable only when
If you'd like to contribute to this project, follow these steps:
- Fork the repository and create a new branch.
- Make your changes and test them thoroughly.
- Submit a pull request, explaining the changes you've made.