import dataclasses
import datetime
import operator
import pathlib

import pandas as pd
import tqdm.auto
import yaml
from huggingface_hub import HfApi

from constants import (OWNER_CHOICES, SLEEP_TIME_INT_TO_STR,
                       SLEEP_TIME_STR_TO_INT, WHOAMI)


@dataclasses.dataclass(frozen=True)
class DemoInfo:
    space_id: str
    url: str
    title: str
    owner: str
    sdk: str
    sdk_version: str
    likes: int
    status: str
    last_modified: str
    sleep_time: int
    replicas: int
    private: bool
    hardware: str
    suggested_hardware: str
    created: str = ''
    arxiv: list[str] = dataclasses.field(default_factory=list)
    github: list[str] = dataclasses.field(default_factory=list)
    tags: list[str] = dataclasses.field(default_factory=list)

    def __post_init__(self):
        object.__setattr__(self, 'last_modified',
                           DemoInfo.convert_timestamp(self.last_modified))
        object.__setattr__(self, 'created',
                           DemoInfo.convert_timestamp(self.created))

    @staticmethod
    def convert_timestamp(timestamp: str) -> str:
        try:
            return datetime.datetime.strptime(
                timestamp,
                '%Y-%m-%dT%H:%M:%S.%fZ').strftime('%Y/%m/%d %H:%M:%S')
        except ValueError:
            return timestamp

    @classmethod
    def from_space_id(cls, space_id: str) -> 'DemoInfo':
        api = HfApi()
        space_info = api.space_info(repo_id=space_id)
        card = space_info.cardData
        runtime = space_info.runtime
        resources = runtime['resources']

        return cls(
            space_id=space_id,
            url=f'https://huggingface.co/spaces/{space_id}',
            title=card['title'] if 'title' in card else '',
            owner=space_id.split('/')[0],
            sdk=card['sdk'],
            sdk_version=card.get('sdk_version', ''),
            likes=space_info.likes,
            status=runtime['stage'],
            last_modified=space_info.lastModified,
            sleep_time=runtime['gcTimeout'] or 0,
            replicas=resources['replicas'] if resources is not None else 0,
            private=space_info.private,
            hardware=runtime['hardware']['current']
            or runtime['hardware']['requested'],
            suggested_hardware=card.get('suggested_hardware', ''),
        )


def get_df_from_yaml(path: pathlib.Path | str) -> pd.DataFrame:
    with pathlib.Path(path).open() as f:
        data = yaml.safe_load(f)
    demo_info = []
    for space_id in tqdm.auto.tqdm(list(data)):
        base_info = DemoInfo.from_space_id(space_id)
        info = DemoInfo(**(dataclasses.asdict(base_info) | data[space_id]))
        demo_info.append(info)
    return pd.DataFrame([dataclasses.asdict(info) for info in demo_info])


class Prettifier:
    @staticmethod
    def get_arxiv_link(links: list[str]) -> str:
        links = [
            Prettifier.create_link(link.split('/')[-1], link) for link in links
        ]
        return '\n'.join(links)

    @staticmethod
    def get_github_link(links: list[str]) -> str:
        links = [Prettifier.create_link('github', link) for link in links]
        return '\n'.join(links)

    @staticmethod
    def get_tag_list(tags: list[str]) -> str:
        return ', '.join(tags)

    @staticmethod
    def create_link(text: str, url: str) -> str:
        return f'<a href={url} target="_blank">{text}</a>'

    @staticmethod
    def to_div(text: str | None, category_name: str) -> str:
        if text is None:
            text = ''
        class_name = f'{category_name}-{text.lower()}'
        return f'<div class="{class_name}">{text}</div>'

    @staticmethod
    def add_div_tag_to_replicas(replicas: int) -> str:
        if replicas == 0:
            return ''
        if replicas == 1:
            return '1'
        return f'<div class="multiple-replicas">{replicas}</div>'

    @staticmethod
    def add_div_tag_to_sleep_time(sleep_time_s: str, hardware: str) -> str:
        if hardware == 'cpu-basic':
            return f'<div class="sleep-time-cpu-basic">{sleep_time_s}</div>'
        s = sleep_time_s.replace(' ', '-')
        return f'<div class="sleep-time-{s}">{sleep_time_s}</div>'

    def __call__(self, df: pd.DataFrame) -> pd.DataFrame:
        new_rows = []
        for _, row in df.iterrows():
            new_row = dict(row) | {
                'status':
                self.to_div(row.status, 'status'),
                'hardware':
                self.to_div(row.hardware, 'hardware'),
                'suggested_hardware':
                self.to_div(row.suggested_hardware, 'hardware'),
                'title':
                self.create_link(row.title, row.url),
                'owner':
                self.create_link(row.owner,
                                 f'https://huggingface.co/{row.owner}'),
                'sdk':
                self.to_div(row.sdk, 'sdk'),
                'sleep_time':
                self.add_div_tag_to_sleep_time(
                    SLEEP_TIME_INT_TO_STR[row.sleep_time], row.hardware),
                'replicas':
                self.add_div_tag_to_replicas(row.replicas),
                'arxiv':
                self.get_arxiv_link(row.arxiv),
                'github':
                self.get_github_link(row.github),
                'tags':
                self.get_tag_list(row.tags),
            }
            new_rows.append(new_row)
        return pd.DataFrame(new_rows, columns=df.columns)


class DemoList:
    COLUMN_INFO = [
        ['status', 'markdown'],
        ['hardware', 'markdown'],
        ['title', 'markdown'],
        ['owner', 'markdown'],
        ['arxiv', 'markdown'],
        ['github', 'markdown'],
        ['likes', 'number'],
        ['tags', 'str'],
        ['last_modified', 'str'],
        ['created', 'str'],
        ['sdk', 'markdown'],
        ['sdk_version', 'str'],
        ['suggested_hardware', 'markdown'],
        ['sleep_time', 'markdown'],
        ['replicas', 'markdown'],
        ['private', 'bool'],
    ]

    def __init__(self, df: pd.DataFrame):
        self.df_raw = df
        self._prettifier = Prettifier()
        self.df_prettified = self._prettifier(df).loc[:, self.column_names]

    @property
    def column_names(self):
        return list(map(operator.itemgetter(0), self.COLUMN_INFO))

    @property
    def column_datatype(self):
        return list(map(operator.itemgetter(1), self.COLUMN_INFO))

    def filter(
        self,
        status: list[str],
        hardware: list[str],
        sleep_time: list[str],
        multiple_replicas: bool,
        sdk: list[str],
        visibility: list[str],
        owner: list[str],
    ) -> pd.DataFrame:
        df = self.df_raw.copy()

        if multiple_replicas:
            df = df[self.df_raw.replicas > 1]

        if visibility == ['public']:
            df = df[~self.df_raw.private]
        elif visibility == ['private']:
            df = df[self.df_raw.private]

        df = df[(self.df_raw.status.isin(status))
                & (self.df_raw.hardware.isin(hardware))
                & (self.df_raw.sdk.isin(sdk))]

        sleep_time_int = [SLEEP_TIME_STR_TO_INT[s] for s in sleep_time]
        df = df[self.df_raw.sleep_time.isin(sleep_time_int)]

        if set(owner) == set(OWNER_CHOICES):
            pass
        elif WHOAMI in owner:
            df = df[self.df_raw.owner == WHOAMI]
        else:
            df = df[self.df_raw.owner != WHOAMI]

        return self._prettifier(df).loc[:, self.column_names]