Redis integration for taskiq
Project description
TaskIQ-Redis
Taskiq-redis is a plugin for taskiq that adds a new broker and result backend based on redis.
Installation
To use this project you must have installed core taskiq library:
pip install taskiq
This project can be installed using pip:
pip install taskiq-redis
Usage
Let's see the example with the redis broker and redis async result:
# broker.py
import asyncio
from taskiq_redis import RedisAsyncResultBackend, RedisStreamBroker
result_backend = RedisAsyncResultBackend(
redis_url="redis://localhost:6379",
)
# Or you can use PubSubBroker if you need broadcasting
# Or ListQueueBroker if you don't want acknowledges
broker = RedisStreamBroker(
url="redis://localhost:6379",
).with_result_backend(result_backend)
@broker.task
async def best_task_ever() -> None:
"""Solve all problems in the world."""
await asyncio.sleep(5.5)
print("All problems are solved!")
async def main():
task = await best_task_ever.kiq()
print(await task.wait_result())
if __name__ == "__main__":
asyncio.run(main())
Launch the workers:
taskiq worker broker:broker
Then run the main code:
python3 broker.py
Brokers
This package contains 6 broker implementations. 3 broker types:
- PubSub broker
- ListQueue broker
- Stream broker
Each of type is implemented for each redis architecture:
- Single node
- Cluster
- Sentinel
Here's a small breakdown of how they differ from eachother.
PubSub
By default on old redis versions PUBSUB was the way of making redis into a queue. But using PUBSUB means that all messages delivered to all subscribed consumers.
[!WARNING] This broker doesn't support acknowledgements. If during message processing Worker was suddenly killed the message is going to be lost.
ListQueue
This broker creates a list of messages at some key. Adding new tasks will be done
by appending them from the left side using lpush
, and taking them from the right side using brpop
.
[!WARNING] This broker doesn't support acknowledgements. If during message processing Worker was suddenly killed the message is going to be lost.
Stream
Stream brokers use redis stream type to store and fetch messages.
[!TIP] This broker supports acknowledgements and therefore is fine to use in cases when data durability is required.
RedisAsyncResultBackend configuration
RedisAsyncResultBackend parameters:
redis_url
- url to redis.keep_results
- flag to not remove results from Redis after reading.result_ex_time
- expire time in seconds (by default - not specified)result_px_time
- expire time in milliseconds (by default - not specified)- Any other keyword arguments are passed to
redis.asyncio.BlockingConnectionPool
. Notably, you can usetimeout
to set custom timeout in seconds for reconnects (or set it toNone
to try reconnects indefinitely).
[!WARNING] It is highly recommended to use expire time in RedisAsyncResultBackend If you want to add expiration, either
result_ex_time
orresult_px_time
must be set.# First variant redis_async_result = RedisAsyncResultBackend( redis_url="redis://localhost:6379", result_ex_time=1000, ) # Second variant redis_async_result = RedisAsyncResultBackend( redis_url="redis://localhost:6379", result_px_time=1000000, )
Schedule sources
You can use this package to add dynamic schedule sources. They are used to store schedules for taskiq scheduler.
The advantage of using schedule sources from this package over default LabelBased
source is that you can
dynamically add schedules in it.
We have two types of schedules:
RedisScheduleSource
ListRedisScheduleSource
RedisScheduleSource
This source is super simple. It stores all schedules by key {prefix}:{schedule_id}
. When scheduler requests
schedules, it retrieves all values from redis that start with a given prefix
.
This is very ineficent and should not be used for high-volume schedules. Because if you have 1000
schedules, this scheduler will make at least 20
requests to retrieve them (we use scan
and mget
to minimize number of calls).
ListRedisScheduleSource
This source holds values in lists.
- For cron tasks it uses key
{prefix}:cron
. - For timed schedules it uses key
{prefix}:time:{time}
where{time}
is actually time where schedules should run.
The main advantage of this approach is that we only fetch tasks we need to run at a given time and do not perform any excesive calls to redis.
Migration from one source to another
To migrate from RedisScheduleSource
to ListRedisScheduleSource
you can define the latter as this:
# broker.py
import asyncio
import datetime
from taskiq import TaskiqScheduler
from taskiq_redis import ListRedisScheduleSource, RedisStreamBroker
from taskiq_redis.schedule_source import RedisScheduleSource
broker = RedisStreamBroker(url="redis://localhost:6379")
old_source = RedisScheduleSource("redis://localhost/1", prefix="prefix1")
array_source = ListRedisScheduleSource(
"redis://localhost/1",
prefix="prefix2",
# To migrate schedules from an old source.
).with_migrate_from(
old_source,
# To delete schedules from an old source.
delete_schedules=True,
)
scheduler = TaskiqScheduler(broker, [array_source])
During startup the scheduler will try to migrate schedules from an old source to a new one. Please be sure to specify different prefixe just to avoid any kind of collision between these two.
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