# coding: utf-8

"""
Trading API

API for automated trading and exchange interface. This API is used to trade on the exchange and manage bots, API keys, orders, and more.

The version of the OpenAPI document: 2.0.0
Generated by OpenAPI Generator (https://openapi-generator.tech)

Do not edit the class manually.
"""  # noqa: E501


from __future__ import annotations

import json
import pprint
import re  # noqa: F401
from typing import Any, ClassVar, Dict, List, Optional, Set

from pydantic import BaseModel, ConfigDict, Field, StrictStr
from typing_extensions import Self


class TPSL(BaseModel):
    """
    Runtime fields for take profit and stop loss
    """  # noqa: E501

    price_delta: Optional[StrictStr] = None
    price: Optional[StrictStr] = None
    allocation: StrictStr = Field(
        description="Percentage of the open order to sell. All allocations must sum up to 1. Use this allocation again when closing the order."
    )
    execution_id: Optional[StrictStr] = Field(
        default=None, description="Execution ID of the order."
    )
    __properties: ClassVar[List[str]] = [
        "price_delta",
        "price",
        "allocation",
        "execution_id",
    ]

    model_config = ConfigDict(
        populate_by_name=True,
        validate_assignment=True,
        protected_namespaces=(),
    )

    def to_str(self) -> str:
        """Returns the string representation of the model using alias"""
        return pprint.pformat(self.model_dump(by_alias=True))

    def to_json(self) -> str:
        """Returns the JSON representation of the model using alias"""
        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
        return json.dumps(self.to_dict())

    @classmethod
    def from_json(cls, json_str: str) -> Optional[Self]:
        """Create an instance of TPSL from a JSON string"""
        return cls.from_dict(json.loads(json_str))

    def to_dict(self) -> Dict[str, Any]:
        """Return the dictionary representation of the model using alias.

        This has the following differences from calling pydantic's
        `self.model_dump(by_alias=True)`:

        * `None` is only added to the output dict for nullable fields that
          were set at model initialization. Other fields with value `None`
          are ignored.
        """
        excluded_fields: Set[str] = set([])

        _dict = self.model_dump(
            by_alias=True,
            exclude=excluded_fields,
            exclude_none=True,
        )
        # set to None if price_delta (nullable) is None
        # and model_fields_set contains the field
        if self.price_delta is None and "price_delta" in self.model_fields_set:
            _dict["price_delta"] = None

        # set to None if price (nullable) is None
        # and model_fields_set contains the field
        if self.price is None and "price" in self.model_fields_set:
            _dict["price"] = None

        return _dict

    @classmethod
    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
        """Create an instance of TPSL from a dict"""
        if obj is None:
            return None

        if not isinstance(obj, dict):
            return cls.model_validate(obj)

        _obj = cls.model_validate(
            {
                "price_delta": obj.get("price_delta"),
                "price": obj.get("price"),
                "allocation": obj.get("allocation"),
                "execution_id": obj.get("execution_id"),
            }
        )
        return _obj
