import argparse
import json

import pika

from pyinfra.config import CONFIG, parse_disjunction_string
from pyinfra.storage.storages import get_s3_storage


def parse_args():
    parser = argparse.ArgumentParser()
    parser.add_argument("--bucket_name", "-b", required=True)
    parser.add_argument(
        "--analysis_container",
        "-a",
        choices=["detr", "ner", "image", "conversion", "extraction", "dl_error", "table_parsing"],
        required=True,
    )
    args = parser.parse_args()
    return args


def read_connection_params():
    credentials = pika.PlainCredentials(CONFIG.rabbitmq.user, CONFIG.rabbitmq.password)
    parameters = pika.ConnectionParameters(
        host=CONFIG.rabbitmq.host,
        port=CONFIG.rabbitmq.port,
        heartbeat=CONFIG.rabbitmq.heartbeat,
        credentials=credentials,
    )
    return parameters


def make_channel(connection) -> pika.adapters.blocking_connection.BlockingChannel:
    channel = connection.channel()
    channel.basic_qos(prefetch_count=1)
    return channel


def declare_queue(channel, queue: str):
    args = {"x-dead-letter-exchange": "", "x-dead-letter-routing-key": CONFIG.rabbitmq.queues.dead_letter}
    return channel.queue_declare(queue=queue, auto_delete=False, durable=True, arguments=args)


def make_connection() -> pika.BlockingConnection:
    parameters = read_connection_params()
    connection = pika.BlockingConnection(parameters)
    return connection


def build_message_bodies(analyse_container_type, bucket_name):
    def update_message(message_dict):
        if analyse_container_type == "detr" or analyse_container_type == "image":
            message_dict.update({"targetFileExtension": "ORIGIN.pdf.gz", "responseFileExtension": "IMAGE_INFO.json.gz"})
        if analyse_container_type == "conversion":
            message_dict.update(
                {
                    "targetFileExtension": "ORIGIN.pdf.gz",
                    "responseFileExtension": "json.gz",
                    "operation": "conversion",
                    "pages": [1, 2, 3],
                }
            )
        if analyse_container_type == "table_parsing":
            message_dict.update(
                {
                    "operation": "table_parsing",
                    "pages": [1, 2, 3],
                }
            )
        if analyse_container_type == "extraction":
            message_dict.update(
                {"targetFileExtension": "ORIGIN.pdf.gz", "responseFileExtension": "json.gz", "operation": "extraction"}
            )
        if analyse_container_type == "dl_error":
            message_dict.update({"targetFileExtension": "no_such_file", "responseFileExtension": "IMAGE_INFO.json.gz"})
        if analyse_container_type == "ner":
            message_dict.update(
                {"targetFileExtension": "TEXT.json.gz", "responseFileExtension": "NER_ENTITIES.json.gz"}
            )
        return message_dict

    storage = get_s3_storage()
    for pdf_name in storage.get_all_object_names(bucket_name):
        if "pdf" not in pdf_name:
            continue
        file_id = pdf_name.split(".")[0]
        dossier_id, file_id = file_id.split("/")
        message_dict = {"dossierId": dossier_id, "fileId": file_id}
        update_message(message_dict)
        yield json.dumps(message_dict).encode()


def main(args):
    connection = make_connection()
    channel = make_channel(connection)
    declare_queue(channel, CONFIG.rabbitmq.queues.input)
    declare_queue(channel, CONFIG.rabbitmq.queues.output)

    for body in build_message_bodies(args.analysis_container, args.bucket_name):
        channel.basic_publish("", CONFIG.rabbitmq.queues.input, body)
        print(f"Put {body} on {CONFIG.rabbitmq.queues.input}")

    for method_frame, _, body in channel.consume(queue=CONFIG.rabbitmq.queues.output, inactivity_timeout=1):
        if not body:
            break
        print(f"Received {json.loads(body)}")
        channel.basic_ack(method_frame.delivery_tag)
    channel.close()


if __name__ == "__main__":
    main(parse_args())