Task queue, Long lived workers for work based parallelization, with processes and Redis as back-end. For distributed computing.
Task queue, Long lived workers process parallelization, with Redis as backend.
The project is used in production by three different companies.
There are Meesee instances that have been running without maintenance or restarts for more than one year.
Since the scope of the project is laser focussed on providing the following usecases.
There are no outstanding feature requests, the project is stable and no code are needed at the moment.
For feature request or additional information, an issue could be raised.
For examples on how to use Meesee there are examples available.
Create my_func that will
Let’s start 10 of those.
import time
from meesee import startapp
def my_func(item, worker_id):
print("hello, look at me")
time.sleep(1)
print('finished item', locals())
startapp(my_func, workers=10)
Open another terminal, Let’s produce some tasks
from meesee import RedisQueue, config
def produce(items):
r = RedisQueue(**config)
for i in range(items):
r.send(i)
produce(10)
Great, the placement of both scripts can be on any machine with connectivity to the redis instance.
Create a virtualenv for your project.
Install meesee:
$ . /path/to/virtualenv/bin/activate
$ pip install meesee
For Docker
$ docker run --name some-redis -d redis
For Debian, Ubuntu
$ sudo apt-get install redis-server
For Centos, Red Hat
$ sudo yum install redis
This project is licensed under the MIT License - see the LICENSE file for details