import json
from asyncio import Event

import ray
from mtranslate.core import translate
from ray.actor import ActorHandle
from tqdm import tqdm

ray.init()
from typing import Tuple


# Back on the local node, once you launch your remote Ray tasks, call
# `print_until_done`, which will feed everything back into a `tqdm` counter.
@ray.remote
class ProgressBarActor:
    counter: int
    delta: int
    event: Event

    def __init__(self) -> None:
        self.counter = 0
        self.delta = 0
        self.event = Event()

    def update(self, num_items_completed: int) -> None:
        """Updates the ProgressBar with the incremental
        number of items that were just completed.
        """
        self.counter += num_items_completed
        self.delta += num_items_completed
        self.event.set()

    async def wait_for_update(self) -> Tuple[int, int]:
        """Blocking call.

        Waits until somebody calls `update`, then returns a tuple of
        the number of updates since the last call to
        `wait_for_update`, and the total number of completed items.
        """
        await self.event.wait()
        self.event.clear()
        saved_delta = self.delta
        self.delta = 0
        return saved_delta, self.counter

    def get_counter(self) -> int:
        """
        Returns the total number of complete items.
        """
        return self.counter


class ProgressBar:
    progress_actor: ActorHandle
    total: int
    description: str
    pbar: tqdm

    def __init__(self, total: int, description: str = ""):
        # Ray actors don't seem to play nice with mypy, generating
        # a spurious warning for the following line,
        # which we need to suppress. The code is fine.
        self.progress_actor = ProgressBarActor.remote()  # type: ignore
        self.total = total
        self.description = description

    @property
    def actor(self) -> ActorHandle:
        """Returns a reference to the remote `ProgressBarActor`.

        When you complete tasks, call `update` on the actor.
        """
        return self.progress_actor

    def print_until_done(self) -> None:
        """Blocking call.

        Do this after starting a series of remote Ray tasks, to which you've
        passed the actor handle. Each of them calls `update` on the actor.
        When the progress meter reaches 100%, this method returns.
        """
        pbar = tqdm(desc=self.description, total=self.total)
        while True:
            delta, counter = ray.get(self.actor.wait_for_update.remote())
            pbar.update(delta)
            if counter >= self.total:
                pbar.close()
                return


with open("answer_reverse_mapping.json") as f:
    answer_reverse_mapping = json.load(f)


@ray.remote
def translate_answer(value, pba):
    temp = {}
    for lang in ["fr", "es", "de"]:
        temp.update({lang: translate(value, lang, "en")})
    pba.update.remote(1)
    return temp


translation_dicts = []
pb = ProgressBar(len(answer_reverse_mapping.values()))
actor = pb.actor
for value in answer_reverse_mapping.values():
    translation_dicts.append(translate_answer.remote(value, actor))

pb.print_until_done()
translation_dict = dict(
    zip(answer_reverse_mapping.values(), ray.get(translation_dicts))
)


with open("translation_dict.json", "w") as f:
    json.dump(translation_dict, f)