"""
The tool to check the availability or syntax of domain, IP or URL.
::
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Provides the base of all multiprocessing jobs.
Author:
Nissar Chababy, @funilrys, contactTATAfunilrysTODTODcom
Special thanks:
https://pyfunceble.github.io/#/special-thanks
Contributors:
https://pyfunceble.github.io/#/contributors
Project link:
https://github.com/funilrys/PyFunceble
Project documentation:
https://pyfunceble.readthedocs.io/en/latest/
Project homepage:
https://pyfunceble.github.io/
License:
::
Copyright 2017, 2018, 2019, 2020, 2022, 2023 Nissar Chababy
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
import functools
import multiprocessing
import os
import queue
from typing import Any, List, Optional
import PyFunceble.facility
from PyFunceble.cli.continuous_integration.base import ContinuousIntegrationBase
from PyFunceble.cli.processes.workers.base import WorkerBase
[docs]class ProcessesManagerBase:
"""
Provides the base of all classes.
"""
CPU_COUNT = os.cpu_count()
if CPU_COUNT > 2:
STD_MAX_WORKER: int = CPU_COUNT - 2
else:
STD_MAX_WORKER: int = 1
WORKER_OBJ: Optional[WorkerBase] = None
input_datasets: Optional[List] = []
"""
Use this variable if you want to differ the addition in the input queue.
"""
output_datasets: Optional[List] = []
"""
Use this variable if you want to differ the addition in the output queue.
"""
input_queue: Optional[queue.Queue] = None
"""
The input queue. Dataset will be given through this.
"""
output_queue: Optional[List[queue.Queue]] = None
"""
The output queue. This is where the result of a worker will be put.
"""
daemon: Optional[bool] = None
manager: Optional[multiprocessing.Manager] = None
global_exit_event: Optional[multiprocessing.Event] = None
continuous_integration: Optional[ContinuousIntegrationBase] = None
_created_workers: Optional[List[WorkerBase]] = None
_running_workers: Optional[List[WorkerBase]] = None
_output_workers_count: Optional[int] = None
_max_worker: Optional[int] = None
def __init__(
self,
manager: Optional[multiprocessing.Manager] = None,
max_worker: Optional[int] = None,
*,
continuous_integration: Optional[ContinuousIntegrationBase] = None,
input_queue: Optional[queue.Queue] = None,
output_queue: Optional[queue.Queue] = None,
daemon: bool = False,
generate_input_queue: bool = True,
generate_output_queue: bool = True,
output_queue_num: int = 1,
output_workers_count: Optional[int] = None,
) -> None:
if manager is not None:
self.manager = manager
else:
self.manager = multiprocessing.Manager()
if input_queue is None:
if generate_input_queue:
self.input_queue = self.manager.Queue()
else:
self.input_queue = None
else:
self.input_queue = input_queue
if output_queue is None:
if generate_output_queue:
self.output_queue = [
self.manager.Queue() for _ in range(output_queue_num)
]
else:
self.output_queue = None
else:
if not isinstance(output_queue, list):
self.output_queue = [output_queue]
else:
self.output_queue = output_queue
if max_worker is not None:
self.max_worker = max_worker
else:
self.max_worker = self.STD_MAX_WORKER
if continuous_integration is not None:
self.continuous_integration = continuous_integration
self.daemon = daemon
self.global_exit_event = multiprocessing.Event()
self._running_workers = []
self._created_workers = []
if output_workers_count is None:
self._output_workers_count = 1
else:
self._output_workers_count = int(output_workers_count)
[docs] def ensure_worker_obj_is_given(func): # pylint: disable=no-self-argument
"""
Ensures that the worker is properly declared before launching the
decorated method.
"""
@functools.wraps(func)
def wrapper(self, *args, **kwargs):
if self.WORKER_OBJ is None:
raise TypeError(f"<self.WORKER_OBJ> should not be {None}!")
return func(self, *args, **kwargs) # pylint: disable=not-callable
return wrapper
[docs] def create_workers_if_missing(func): # pylint: disable=no-self-argument
"""
Creates the workers if they are missing before launching the decorated
method.
"""
@functools.wraps(func)
def wrapper(self, *args, **kwargs):
# pylint: disable=protected-access
if not self._created_workers:
self.create()
return func(self, *args, **kwargs) # pylint: disable=not-callable
return wrapper
[docs] def ignore_if_running(func): # pylint: disable=no-self-argument
"""
Ignore the launching of the decorated method if the workers are
running.
"""
@functools.wraps(func)
def wrapper(self, *args, **kwargs):
if not self.is_running():
return func(self, *args, **kwargs) # pylint: disable=not-callable
return self
return wrapper
@property
def max_worker(self) -> Optional[int]:
"""
Provides the number of maximum worker we are allowed to generate.
"""
return self._max_worker
@max_worker.setter
def max_worker(self, value: int) -> None:
"""
Sets the number of maximum worker we are authorized to generate.
:param value:
The value to set.
:raise TypeError:
When the given :code:`value` is not a :py:class:`int`.
:raise ValueError:
When the given :code:`value` is less than :code:`1`.
"""
if not isinstance(value, int):
raise TypeError(f"<value> should be {int}, {type(value)} given.")
if value < 1:
raise ValueError("<value> should be greater or equal to one.")
self._max_worker = value
[docs] def set_max_worker(self, value: int) -> "ProcessesManagerBase":
"""
Sets the number of maximum worker we are authorized to generate.
:param value:
The value to set.
"""
self.max_worker = value
return self
[docs] def is_running(self) -> bool:
"""
Checks if a worker is running.
"""
if not self._running_workers:
return False
for worker in self._running_workers:
if worker.is_alive():
return True
return False
[docs] def send_stop_signal(
self, *, worker_name: Optional[str] = None
) -> "ProcessesManagerBase":
"""
Sends a stop message to the input queue.
"""
self.add_to_all_input_queues(
"stop", worker_name=worker_name, include_destination=True
)
[docs] def terminate(self) -> "ProcessesManagerBase":
"""
Terminates all workers and send a stop message to the declared output
queues - which are implicitly dependend of this process "pool".
"""
if self._running_workers:
workers = self._running_workers
else:
workers = self._created_workers
if workers[0].global_exit_event:
workers[0].global_exit_event.set()
for worker in workers:
worker.terminate()
worker.join()
# When all worker of the current process are down or finished, send the
# stop message to the depending workers.
self.add_to_all_output_queues("stop")
[docs] def wait(self) -> "ProcessesManagerBase":
"""
Wait until all workers are done.
"""
for worker in self._running_workers:
PyFunceble.facility.Logger.info(
"Waiting for %r to finish.",
worker.name,
)
worker.join()
self._running_workers.remove(worker)
PyFunceble.facility.Logger.info(
"Still running: %r.",
self._running_workers,
)
for worker in self._created_workers:
if worker.exception:
worker_error, _ = worker.exception
self.terminate()
raise worker_error
self.terminate()
[docs] @create_workers_if_missing
def add_to_all_output_queues(
self,
data: Any,
*,
worker_name: Optional[str] = None,
) -> "ProcessesManagerBase":
"""
Adds the given data to the output queues.
:param data:
The data to add into the queue.
:param worker_name:
The name of the worker that is sending the message.
"""
for _ in range(self._output_workers_count):
self.add_to_output_queue(data, worker_name=worker_name)
PyFunceble.facility.Logger.debug("Added to all (output) queues: %r", data)
return self
[docs] @create_workers_if_missing
def add_to_output_queue(
self, data: Any, *, worker_name: Optional[str] = None
) -> "ProcessesManagerBase":
"""
Adds the given data to the output queue.
:param data:
The data to add into the queue.
"""
if self.is_running():
self._running_workers[0].add_to_output_queue(data, worker_name=worker_name)
else:
self._created_workers[0].add_to_output_queue(data, worker_name=worker_name)
PyFunceble.facility.Logger.debug("Added to the (output) queue: %r", data)
return self
[docs] def create(self) -> "ProcessesManagerBase":
"""
Creates the defined amount of worker.
"""
def share_concurrent_worker_names() -> None:
"""
Share the name of all concurrent worker to all workers.
"""
concurrent_names = [x.name for x in self._created_workers]
for worker in self._created_workers:
worker.concurrent_worker_names = list(concurrent_names)
worker.concurrent_worker_names.remove(worker.name)
for i in range(self.max_worker):
worker = self.WORKER_OBJ( # pylint: disable=not-callable
self.input_queue,
self.output_queue,
self.global_exit_event,
name=f"{self.WORKER_OBJ.STD_NAME}_{i + 1}",
daemon=self.daemon,
continuous_integration=self.continuous_integration,
configuration=PyFunceble.storage.CONFIGURATION.to_dict(),
)
self._created_workers.append(worker)
share_concurrent_worker_names()
PyFunceble.facility.Logger.info(
"Created %r workers of %r. Details:\n%r",
len(self._created_workers),
self.WORKER_OBJ,
self._created_workers,
)
return self
[docs] @ensure_worker_obj_is_given
@create_workers_if_missing
@ignore_if_running
def start(self) -> "ProcessesManagerBase":
"""
Starts all - previously - created workers.
"""
for worker in self._created_workers:
try:
worker.start()
except AssertionError:
# Example: cannot start a process twice
pass
self._running_workers.append(worker)
if self.input_datasets:
while self.input_datasets:
self.add_to_input_queue(self.input_datasets.pop())
if self.output_datasets:
while self.output_datasets:
self.add_to_output_queue(self.output_datasets.pop())
PyFunceble.facility.Logger.info(
"Started %r workers of %r. Details:\n%r",
len(self._running_workers),
self.WORKER_OBJ,
self._running_workers,
)
return self