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Odoo payroll multiprocessing to speed it up

payroll multiprocess odoo

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AteneoLab

Hi every one, I need to execute a payroll for more than 6K employees. This takes about 4 hours to complete.

I want to parallelize the method that compute and confirms the payroll but it throws this error message:

Traceback (most recent call last):

File "/home/matos/PycharmProjects/Odoo12/odoo/odoo/http.py", line 654, in _handle_exception

return super(JsonRequest, self)._handle_exception(exception)

File "/home/matos/PycharmProjects/Odoo12/odoo/odoo/http.py", line 312, in _handle_exception

raise pycompat.reraise(type(exception), exception, sys.exc_info()[2])

File "/home/matos/PycharmProjects/Odoo12/odoo/odoo/tools/pycompat.py", line 87, in reraise

raise value

File "/home/matos/PycharmProjects/Odoo12/odoo/odoo/http.py", line 696, in dispatch

result = self._call_function(**self.params)

File "/home/matos/PycharmProjects/Odoo12/odoo/odoo/http.py", line 344, in _call_function

return checked_call(self.db, *args, **kwargs)

File "/home/matos/PycharmProjects/Odoo12/odoo/odoo/service/model.py", line 97, in wrapper

return f(dbname, *args, **kwargs)

File "/home/matos/PycharmProjects/Odoo12/odoo/odoo/http.py", line 337, in checked_call

result = self.endpoint(*a, **kw)

File "/home/matos/PycharmProjects/Odoo12/odoo/odoo/http.py", line 939, in __call__

return self.method(*args, **kw)

File "/home/matos/PycharmProjects/Odoo12/odoo/odoo/http.py", line 517, in response_wrap

response = f(*args, **kw)

File "/home/matos/PycharmProjects/Odoo12/odoo/addons/web/controllers/main.py", line 966, in call_button

action = self._call_kw(model, method, args, {})

File "/home/matos/PycharmProjects/Odoo12/odoo/addons/web/controllers/main.py", line 954, in _call_kw

return call_kw(request.env[model], method, args, kwargs)

File "/home/matos/PycharmProjects/Odoo12/odoo/odoo/api.py", line 749, in call_kw

return _call_kw_multi(method, model, args, kwargs)

File "/home/matos/PycharmProjects/Odoo12/odoo/odoo/api.py", line 736, in _call_kw_multi

result = method(recs, *args, **kwargs)

File "/home/matos/PycharmProjects/Odoo12/payroll/payroll_masive/models/payslip_run.py", line 70, in compute_and_confirm_sheet_massive

pool.map(self.excec, [slip for slip in slip_list_par])

File "/usr/lib/python3.6/multiprocessing/pool.py", line 288, in map

return self._map_async(func, iterable, mapstar, chunksize).get()

File "/usr/lib/python3.6/multiprocessing/pool.py", line 670, in get

raise self._value

File "/usr/lib/python3.6/multiprocessing/pool.py", line 450, in _handle_tasks

put(task)

File "/usr/lib/python3.6/multiprocessing/connection.py", line 206, in send

self._send_bytes(_ForkingPickler.dumps(obj))

File "/usr/lib/python3.6/multiprocessing/reduction.py", line 51, in dumps

cls(buf, protocol).dump(obj)

_pickle.PicklingError: Can't pickle <class 'odoo.api.hr.payslip.run'>: attribute lookup hr.payslip.run on odoo.api failed

Does anyone of you have any idea of why is this and how to solve it?

Thank you very much.

djking7

you can't pickle odoo methods, you need to send table of ids to the function declared outside of the class;

Example:

def multi_compute(ids)

kwargs = {'uid': request.uid, 'db': request.db}
with openerp.api.Environment.manage():
    with openerp.registry(kwargs.get('db')).cursor() as new_cr:
        env = openerp.api.Environment(new_cr, kwargs.get('uid'), {})

      playslip_obj = env['hr.payslip']

      payslip_ids = payslip_obj.browse(ids).compute_sheet()

the call of the method with multiprocessing library should be like this:

list = list(split([slip for slip in slip_list_par], multiprocessing.cpu_count()))

try:
    pool = multiprocessing.Pool(multiprocessing.cpu_count())
    pool.map(multi_compute, list)
except KeyboardInterrupt, e:
    pool.terminate()
    raise e

if you get any connection problem add try and except to 'multi_compute' function

and in the exception recall the method again ('multi_compute(ids)') cause sometimes it's blocked by postgress

cause another process is blocking you process, so you need to recall it after a time

I hope this helps

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