# coding: utf-8

"""
    Vayu API

    The Vayu API is a RESTful API that allows you to submit events for processing and storage & manage billing related entities.           The API is secured using the Bearer Authentication scheme with JWT tokens.           To obtain a JWT token, please contact Vayu at team@withvayu.com

    The version of the OpenAPI document: 1.0.0
    Contact: dev@withvayu.com
    Generated by OpenAPI Generator (https://openapi-generator.tech)

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


from __future__ import annotations
import pprint
import re  # noqa: F401
import json

from pydantic import BaseModel, ConfigDict, Field, StrictBool, StrictFloat, StrictInt, field_validator
from typing import Any, ClassVar, Dict, List, Optional, Union
from typing_extensions import Annotated
from typing import Optional, Set
from typing_extensions import Self

class ProductConsumption(BaseModel):
    """
    ProductConsumption
    """ # noqa: E501
    product_id: Annotated[str, Field(strict=True)] = Field(description="The id of the product.", alias="productId")
    product_name: Annotated[str, Field(min_length=1, strict=True)] = Field(description="The name of the product.", alias="productName")
    provisioned_amount: Union[Annotated[float, Field(strict=True, ge=0)], Annotated[int, Field(strict=True, ge=0)]] = Field(description="The amount of units provisioned to the customer.", alias="provisionedAmount")
    consumed_amount: Union[Annotated[float, Field(strict=True, ge=0)], Annotated[int, Field(strict=True, ge=0)]] = Field(description="The amount of units consumed by the customer.", alias="consumedAmount")
    usage_percentage: Union[Annotated[float, Field(strict=True, ge=0)], Annotated[int, Field(strict=True, ge=0)]] = Field(description="The percentage of the provisioned amount that has been consumed.", alias="usagePercentage")
    has_access: StrictBool = Field(description="Whether the customer has access to the product.", alias="hasAccess")
    remaining_amount: Optional[Union[StrictFloat, StrictInt]] = Field(default=None, description="The amount of units remaining to consume.", alias="remainingAmount")
    exceeded_amount: Optional[Union[StrictFloat, StrictInt]] = Field(default=None, description="The amount of units exceeded.", alias="exceededAmount")
    additional_properties: Dict[str, Any] = {}
    __properties: ClassVar[List[str]] = ["productId", "productName", "provisionedAmount", "consumedAmount", "usagePercentage", "hasAccess", "remainingAmount", "exceededAmount"]

    @field_validator('product_id')
    def product_id_validate_regular_expression(cls, value):
        """Validates the regular expression"""
        if not re.match(r"^[0-9a-fA-F]{24}$", value):
            raise ValueError(r"must validate the regular expression /^[0-9a-fA-F]{24}$/")
        return value

    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 ProductConsumption 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.
        * Fields in `self.additional_properties` are added to the output dict.
        """
        excluded_fields: Set[str] = set([
            "additional_properties",
        ])

        _dict = self.model_dump(
            by_alias=True,
            exclude=excluded_fields,
            exclude_none=True,
        )
        # puts key-value pairs in additional_properties in the top level
        if self.additional_properties is not None:
            for _key, _value in self.additional_properties.items():
                _dict[_key] = _value

        return _dict

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

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

        _obj = cls.model_validate({
            "productId": obj.get("productId"),
            "productName": obj.get("productName"),
            "provisionedAmount": obj.get("provisionedAmount"),
            "consumedAmount": obj.get("consumedAmount"),
            "usagePercentage": obj.get("usagePercentage"),
            "hasAccess": obj.get("hasAccess"),
            "remainingAmount": obj.get("remainingAmount"),
            "exceededAmount": obj.get("exceededAmount")
        })
        # store additional fields in additional_properties
        for _key in obj.keys():
            if _key not in cls.__properties:
                _obj.additional_properties[_key] = obj.get(_key)

        return _obj


