"""
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://docs.pyfunceble.com

Project homepage:
    https://pyfunceble.github.io/

License:
::


    Copyright 2017, 2018, 2019, 2020, 2022, 2023, 2024 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

        https://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


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)

    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

    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

    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

    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

    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

    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
        )

    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")

    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()

    @create_workers_if_missing
    def add_to_all_input_queues(
        self,
        data: Any,
        *,
        worker_name: Optional[str] = None,
        include_destination: bool = False,
    ) -> "ProcessesManagerBase":
        """
        Adds the given data to the input queues.

        :param data:
            The data to add into the queue.

        :param include_destination:
            Authorizes the addition of the destination into the message.
        """

        if self.is_running():
            workers = self._running_workers
        else:
            workers = self._created_workers

        for worker in workers:
            if include_destination:
                worker.add_to_input_queue(
                    data, worker_name=worker_name, destination_worker=worker.name
                )
            else:
                worker.add_to_input_queue(data, worker_name=worker_name)

        PyFunceble.facility.Logger.debug("Added to all (input) queues: %r", data)

    @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

    @create_workers_if_missing
    def add_to_input_queue(
        self, data: Any, *, worker_name: Optional[str] = None
    ) -> "ProcessesManagerBase":
        """
        Adds the given data to the current queue.

        :param data:
            The data to add into the queue.
        """

        if self.is_running():
            self._running_workers[0].add_to_input_queue(data, worker_name=worker_name)
        else:
            self._created_workers[0].add_to_input_queue(data, worker_name=worker_name)

        PyFunceble.facility.Logger.debug("Added to the (main) queue: %r", data)

    @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

    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

    @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