import json
import random
import string
from datetime import datetime
from pathlib import Path

import ffmpeg
import imageio_ffmpeg
import numpy as np
import torch
from addict import Dict


def icycle(iterable):
    while True:
        for it in iterable:
            yield it


async def acycle(aiterable):
    while True:
        async for it in aiterable:
            yield it


def read_config(config_path):
    try:
        with open(config_path) as fd:
            conf = json.load(fd)
            conf = Dict(conf)
    except Exception as e:
        print("read config exception in ", config_path)
        raise e
    return conf


def get_preprocess_dir(work_root_path, name):
    return str(Path(work_root_path) / "preprocess" / name)


def get_crop_mp4_dir(preprocess_dir, video_path):
    return f"{preprocess_dir}/crop_video_{Path(video_path).stem}"


def get_frame_dir(preprocess_dir, video_path, ratio):
    ratio_s = "" if ratio == 1.0 else f"_{ratio}"
    return f"{preprocess_dir}/{Path(video_path).stem}/frames{ratio_s}"


def get_template_ratio_file_path(preprocess_dir, video_path, ratio):
    if ratio == 1.0:
        return video_path

    root_path = f"{preprocess_dir}/{Path(video_path).name}"
    return f"{root_path}/{Path(video_path).name}_ratio_{ratio}{Path(video_path).suffix}"


class _CallBack(object):
    def __init__(self, callback, min_per, max_per, desc, verbose=False):
        assert max_per > min_per
        self.callback = callback
        self.min_per = min_per
        self.max_per = max_per
        if isinstance(callback, _CallBack):
            self.desc = callback.desc + "/" + desc
        else:
            self.desc = desc
        self.last_per = -1
        self.verbose = verbose
        self.callback_interval = 1

    def __call__(self, per):
        if self.callback is None:
            return
        my_per = self.min_per + (per + 1) / 100.0 * (self.max_per - self.min_per)
        my_per = int(my_per)
        if my_per - self.last_per >= self.callback_interval:
            # if self.verbose:
            #    print(self.desc, ' : ', my_per)
            self.callback(my_per)
            self.last_per = my_per


def callback_inter(callback, min_per=0, max_per=100, desc="", verbose=False):
    assert min_per >= 0 and max_per >= 0 and max_per > min_per
    return _CallBack(callback, min_per, max_per, desc, verbose=verbose)


def callback_test():
    def callback(per):
        print("real callback", per)

    callback1 = callback_inter(callback, min_per=0, max_per=50, desc="1")
    callback2 = callback_inter(callback, min_per=50, max_per=90, desc="2")
    callback3 = callback_inter(callback, min_per=90, max_per=100, desc="3")
    # for i in range(0,101,10):
    #    callback1(i)

    callback11 = callback_inter(callback1, min_per=0, max_per=20, desc="a")
    callback12 = callback_inter(callback1, min_per=20, max_per=80, desc="b")
    callback13 = callback_inter(callback1, min_per=80, max_per=100, desc="c")

    for i in range(0, 101, 1):
        callback11(i)
    for i in range(0, 101, 1):
        callback12(i)
    for i in range(0, 101, 1):
        callback13(i)

    for i in range(0, 101, 1):
        callback2(i)
    for i in range(0, 101, 1):
        callback3(i)


def fix_seed(random_seed):
    """
    fix seed to control any randomness from a code
    (enable stability of the experiments' results.)
    """
    torch.manual_seed(random_seed)
    torch.cuda.manual_seed(random_seed)
    torch.cuda.manual_seed_all(random_seed)  # if use multi-GPU
    torch.backends.cudnn.deterministic = True
    torch.backends.cudnn.benchmark = False
    np.random.seed(random_seed)
    random.seed(random_seed)


def seed_worker(worker_id):
    worker_seed = torch.initial_seed() % 2**32
    np.random.seed(worker_seed)
    random.seed(worker_seed)


def get_three_channel_ffmpeg_reader(path):
    reader = imageio_ffmpeg.read_frames(path)
    meta = reader.__next__()  # meta data, e.g. meta["size"] -> (width, height)
    return reader, meta


def get_four_channel_ffmpeg_reader(path):
    if path.endswith(".mov"):
        reader = imageio_ffmpeg.read_frames(
            str(path), pix_fmt="rgba", bits_per_pixel=32
        )
    elif path.endswith(".webm"):
        stream_meta = [
            it
            for it in ffmpeg.probe(str(path))["streams"]
            if it["codec_type"] == "video"
        ][0]
        reader = imageio_ffmpeg.read_frames(
            path=str(path),
            pix_fmt="rgba",
            input_params=["-c:v", "libvpx-vp9"]
            if stream_meta["codec_name"] == "vp9"
            else ["-c:v", "libvpx"],
            bits_per_pixel=32,
        )

    meta = reader.__next__()  # meta data, e.g. meta["size"] -> (width, height)
    return reader, meta


def get_three_channel_ffmpeg_writer(out_path, size, fps, ffmpeg_params, wav_path):
    writer = imageio_ffmpeg.write_frames(
        out_path,
        size=size,
        fps=fps,
        ffmpeg_log_level="error",
        quality=10,  # 0~10
        output_params=ffmpeg_params,
        audio_path=wav_path,
        macro_block_size=1,
    )
    return writer


def get_webm_ffmpeg_writer(out_path, size, fps, wav_path, low_quality=False):
    writer = imageio_ffmpeg.write_frames(
        out_path,
        size=size,
        fps=fps / 2 if low_quality else fps,
        ffmpeg_log_level="error",
        quality=10,  # 0~10
        # hojin
        pix_fmt_in="rgba",
        pix_fmt_out="yuva420p",
        codec="libvpx",
        bitrate="10M",
        output_params=["-crf", "4", "-auto-alt-ref", "0"]
        + (["-deadline", "realtime"] if low_quality else []),
        # output_params=['-b','37800k', '-vf', 'hflip'], # 좌우 반전 테스트 (완료)
        # hojin end
        audio_path=wav_path,
        macro_block_size=1,
    )
    return writer


def get_mov_ffmpeg_writer(out_path, size, fps, wav_path):
    writer = imageio_ffmpeg.write_frames(
        out_path,
        size=size,
        fps=fps,
        ffmpeg_log_level="error",
        quality=10,  # 0~10
        pix_fmt_in="rgba",
        pix_fmt_out="yuva444p10le",
        # codec="prores_ks",
        output_params=[
            "-c:v",
            "prores_ks",
            "-profile:v",
            "4",
            "-vendor",
            "apl0",
            "-bits_per_mb",
            "8000",
        ],
        audio_path=wav_path,
        macro_block_size=1,
    )
    return writer


def get_reader(template_video_path):
    # document : https://github.com/imageio/imageio-ffmpeg
    if template_video_path.endswith(".mp4"):
        reader, meta = get_three_channel_ffmpeg_reader(template_video_path)
    elif template_video_path.endswith(".mov") or template_video_path.endswith(".webm"):
        reader, meta = get_four_channel_ffmpeg_reader(template_video_path)
    else:
        assert False
    return reader, meta


def get_writer(out_path, size, fps, wav_path, slow_write):
    if out_path.endswith(".mp4"):
        # 합성하면서 비디오 생성
        ffmpeg_params = None
        if slow_write:
            # ffmpeg_params=['-acodec', 'aac', '-preset', 'veryslow', '-crf', '17']
            ffmpeg_params = ["-acodec", "aac", "-crf", "17"]
        writer = get_three_channel_ffmpeg_writer(
            out_path, size, fps, ffmpeg_params, wav_path
        )
    elif out_path.endswith(".mov"):
        writer = get_mov_ffmpeg_writer(out_path, size, fps, wav_path)
    elif out_path.endswith(".webm"):
        writer = get_webm_ffmpeg_writer(
            out_path, size, fps, wav_path
        )  # webm fps 변경한다.(속도를 위해)
    else:
        print('out_path should one of ["mp4", "webm"]')
        assert False
    return writer


def pretty_string_dict(d, tab=4):
    s = ["{\n"]
    for k, v in d.items():
        if isinstance(v, dict):
            v = pretty_string_dict(v, tab + 1)
        else:
            v = repr(v)

        s.append("%s%r: %s,\n" % ("  " * tab, k, v))
    s.append("%s}" % ("  " * tab))
    return "".join(s)


def get_random_string_with_len(size: int):
    time_str = datetime.now().strftime("%y%m%d_%H%M%S_")
    return "".join([time_str] + random.choices(string.ascii_letters, k=size))