from datetime import datetime
from typing import Any, Dict, List, Optional

from pandas import DataFrame
from pydantic import BaseModel, ValidationError

from freqtrade.constants import PairWithTimeframe
from freqtrade.enums.rpcmessagetype import RPCMessageType, RPCRequestType


__all__ = ('WSRequestSchema', 'WSMessageSchema', 'ValidationError')


class BaseArbitraryModel(BaseModel):
    class Config:
        arbitrary_types_allowed = True


class WSRequestSchema(BaseArbitraryModel):
    type: RPCRequestType
    data: Optional[Any] = None


class WSMessageSchema(BaseArbitraryModel):
    type: RPCMessageType
    data: Optional[Any] = None

    class Config:
        extra = 'allow'


# ------------------------------ REQUEST SCHEMAS ----------------------------


class WSSubscribeRequest(WSRequestSchema):
    type: RPCRequestType = RPCRequestType.SUBSCRIBE
    data: List[RPCMessageType]


class WSWhitelistRequest(WSRequestSchema):
    type: RPCRequestType = RPCRequestType.WHITELIST
    data: None = None


class WSAnalyzedDFRequest(WSRequestSchema):
    type: RPCRequestType = RPCRequestType.ANALYZED_DF
    data: Dict[str, Any] = {"limit": 1500}


# ------------------------------ MESSAGE SCHEMAS ----------------------------

class WSWhitelistMessage(WSMessageSchema):
    type: RPCMessageType = RPCMessageType.WHITELIST
    data: List[str]


class WSAnalyzedDFMessage(WSMessageSchema):
    class AnalyzedDFData(BaseArbitraryModel):
        key: PairWithTimeframe
        df: DataFrame
        la: datetime

    type: RPCMessageType = RPCMessageType.ANALYZED_DF
    data: AnalyzedDFData

# --------------------------------------------------------------------------


if __name__ == "__main__":
    message = WSAnalyzedDFMessage(
        data={
            "key": ("1", "5m", "spot"),
            "df": DataFrame(),
            "la": datetime.now()
        }
    )

    print(message)