import datetime, pandas as pd, warnings
from time import strftime, localtime
from twint.tweet import Tweet_formats

Tweets_df = None
Follow_df = None
User_df = None

_object_blocks = {
    "tweet": [],
    "user": [],
    "following": [],
    "followers": []
}

weekdays = {
        "Monday": 1,
        "Tuesday": 2,
        "Wednesday": 3,
        "Thursday": 4,
        "Friday": 5,
        "Saturday": 6,
        "Sunday": 7,
        }

_type = ""

def _concat(df, _type):
    if df is None:
        df = pd.DataFrame(_object_blocks[_type])
    else:
        _df = pd.DataFrame(_object_blocks[_type])
        df = pd.concat([df, _df], sort=True)
    return df

def _autoget(_type):
    global Tweets_df
    global Follow_df
    global User_df

    if _type == "tweet":
        Tweets_df = _concat(Tweets_df, _type)
    elif _type == "followers" or _type == "following":
        Follow_df = _concat(Follow_df, _type)
    elif _type == "user":
        User_df = _concat(User_df, _type)
    else:
        error("[x] Wrong type of object passed")


def update(object, config):
    global _type

    #try:
    #    _type = ((object.__class__.__name__ == "tweet")*"tweet" +
    #             (object.__class__.__name__ == "user")*"user")
    #except AttributeError:
    #    _type = config.Following*"following" + config.Followers*"followers"
    if object.__class__.__name__ == "tweet":
        _type = "tweet"
    elif object.__class__.__name__ == "user":
        _type = "user"
    elif object.__class__.__name__ == "dict":
        _type = config.Following*"following" + config.Followers*"followers"

    if _type == "tweet":
        Tweet = object
        if 'Naoaianeia a?aiy (ceia)' in Tweet.datetime:
            Tweet.datetime = Tweet.datetime[:19]
        try:
            datetime_ms = datetime.datetime.strptime(Tweet.datetime, Tweet_formats['datetime']).timestamp() * 1000
        except:
            datetime_ms = datetime.datetime.strptime(Tweet.datetime, '%Y-%m-%d %H:%M:%S').timestamp() * 1000
        day = weekdays[strftime("%A", localtime(datetime_ms/1000))]
        dt = f"{object.datestamp} {object.timestamp}"
        _data = {
            "id": str(Tweet.id),
            "conversation_id": Tweet.conversation_id,
            "created_at": datetime_ms,
            "date": dt,
            "timezone": Tweet.timezone,
            "place": Tweet.place,
            "tweet": Tweet.tweet,
            "language": Tweet.lang,
            "hashtags": Tweet.hashtags,
            "cashtags": Tweet.cashtags,
            "user_id": Tweet.user_id,
            "user_id_str": Tweet.user_id_str,
            "username": Tweet.username,
            "name": Tweet.name,
            "day": day,
            "hour": strftime("%H", localtime(datetime_ms/1000)),
            "link": Tweet.link,
            "urls": Tweet.urls,
            "photos": Tweet.photos,
            "video": Tweet.video,
            "thumbnail": Tweet.thumbnail,
            "retweet": Tweet.retweet,
            "nlikes": int(Tweet.likes_count),
            "nreplies": int(Tweet.replies_count),
            "nretweets": int(Tweet.retweets_count),
            "quote_url": Tweet.quote_url,
            "search": str(config.Search),
            "near": Tweet.near,
            "geo": Tweet.geo,
            "source": Tweet.source,
            "user_rt_id": Tweet.user_rt_id,
            "user_rt": Tweet.user_rt,
            "retweet_id": Tweet.retweet_id,
            "reply_to": Tweet.reply_to,
            "retweet_date": Tweet.retweet_date,
            "translate": Tweet.translate,
            "trans_src": Tweet.trans_src,
            "trans_dest": Tweet.trans_dest
            }
        _object_blocks[_type].append(_data)
    elif _type == "user":
        user = object
        try:
            background_image = user.background_image
        except:
            background_image = ""
        _data = {
            "id": user.id,
            "name": user.name,
            "username": user.username,
            "bio": user.bio,
            "url": user.url,
            "join_datetime": user.join_date + " " + user.join_time,
            "join_date": user.join_date,
            "join_time": user.join_time,
            "tweets": user.tweets,
            "location": user.location,
            "following": user.following,
            "followers": user.followers,
            "likes": user.likes,
            "media": user.media_count,
            "private": user.is_private,
            "verified": user.is_verified,
            "avatar": user.avatar,
            "background_image": background_image,
            }
        _object_blocks[_type].append(_data)
    elif _type == "followers" or _type == "following":
        _data = {
            config.Following*"following" + config.Followers*"followers" :
                             {config.Username: object[_type]}
        }
        _object_blocks[_type] = _data
    else:
        print("Wrong type of object passed!")


def clean():
    global Tweets_df
    global Follow_df
    global User_df
    _object_blocks["tweet"].clear()
    _object_blocks["following"].clear()
    _object_blocks["followers"].clear()
    _object_blocks["user"].clear()
    Tweets_df = None
    Follow_df = None
    User_df = None

def save(_filename, _dataframe, **options):
    if options.get("dataname"):
        _dataname = options.get("dataname")
    else:
        _dataname = "twint"

    if not options.get("type"):
        with warnings.catch_warnings():
            warnings.simplefilter("ignore")
            _store = pd.HDFStore(_filename + ".h5")
            _store[_dataname] = _dataframe
            _store.close()
    elif options.get("type") == "Pickle":
        with warnings.catch_warnings():
            warnings.simplefilter("ignore")
            _dataframe.to_pickle(_filename + ".pkl")
    else:
        print("""Please specify: filename, DataFrame, DataFrame name and type
              (HDF5, default, or Pickle)""")

def read(_filename, **options):
    if not options.get("dataname"):
        _dataname = "twint"
    else:
        _dataname = options.get("dataname")

    if not options.get("type"):
        _store = pd.HDFStore(_filename + ".h5")
        _df = _store[_dataname]
        return _df
    elif options.get("type") == "Pickle":
        _df = pd.read_pickle(_filename + ".pkl")
        return _df
    else:
        print("""Please specify: DataFrame, DataFrame name (twint as default),
              filename and type (HDF5, default, or Pickle""")

pandas.HDFStore pandas.DataFrame pandas.read_pickle pandas.concat