A background worker is used when you have a task that takes more than a few seconds to execute. Instead of letting the user wait for that task to execute, we send it to a background worker.
There are a few projects which solve this issue (Celery, Dramatiq, RQ etc), but I wanted a solution even easier to use and configure, so I've build one which I called kerground (wor ker + back ground).
Quickstart
Install
pip install kerground
In your app folder create a new package called dependencies
(you can add this in utils
or whatever you consider fit otherwise)
#app/dependencies/kerground.py
from kerground import Kerground
ker = Kerground()
You can set on Kerground
the following params:
-
tasks_path
- path where theevents
will be saved by default in "./.kergroundtasks"; -
pool
- wait in seconds for pending tasks;
Next register
your background workers like:
#some_module_.py
from app.dependencies import ker
@ker.register(ker.MODE.THREAD, max_retries=3)
def convert_files(event: list[str]):
pass # some heavy duty stuff here
# or just go with the defaults
@ker.register
def convert_files_v2(event: list[str]):
pass # some heavy duty stuff here
The event
must be json serializable!
There are 3 mode available:
-
ker.MODE.THREAD
- distribute events withthreading.Thread
if you have urls to wait; -
ker.MODE.PROCESS
- (default) distribute events withmultiprocessing.Process
if you have some CPU intensive tasks; -
ker.MODE.SYNC
- distribute events one by one for the func to process;
By default max_retries
is 0
you can increase this number if you need to get data from some urls and there is a posibility they will fail.
Now you can send an event to background worker (kerground) like:
#some_other_module_possible_route_handler.py
from app.dependencies import ker
def send_files_for_conversion(files: List[UploadFile]):
filepaths = [file.filename for file in files]
msgid = ker.enqueue("convert_files", filepaths)
return f"Files were sent for conversion with id: {msgid}"
Pass to ker.enqueue
the function name you want to call in background along with the json parsable *args and **kwargs. Function ker.enqueue
will return an id which you can later inspect for it's status with ker.check_status(msgid)
.
Prepare the worker.py
file:
# ./worker.py
from app.dependencies import ker
if __name__ == "__main__":
ker.listen()
You can check the example
folder which was used for tests.
Dashboard
Kerground offers a small dashboard in which you can see the functions registered and their status count in a table.
To see the dashboard create a new file worker_dashboard.py
and add the following code:
#./worker_dashboard.py
from app.dependencies import ker
if __name__ == "__main__":
ker.dashboard()
Go to http://localhost:3030/
to see the dashboard.
Check kerground repo here.
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