Source code for openapi_client.models.datalab_logs_response

# coding: utf-8

"""
    Amorphic Data Platform

    Amorphic Data Platform - API Definition documentation

    The version of the OpenAPI document: 1.0
    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, StrictStr
from typing import Any, ClassVar, Dict, List, Optional
from typing import Optional, Set
from typing_extensions import Self


[docs]
class DatalabLogsResponse(BaseModel):
    """
    Response for datalab logs
    """ # noqa: E501
    url: Optional[StrictStr] = Field(default=None, description="Download URL for the logs")
    log_preview: Optional[StrictStr] = Field(default=None, description="Preview of the logs", alias="logPreview")
    log_truncated: Optional[StrictBool] = Field(default=None, description="Whether the logs are truncated", alias="logTruncated")
    next_token: Optional[StrictStr] = Field(default=None, description="Next token for pagination", alias="nextToken")
    __properties: ClassVar[List[str]] = ["url", "logPreview", "logTruncated", "nextToken"]

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



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



[docs]
    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())



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



[docs]
    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,
        )
        return _dict



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

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

        _obj = cls.model_validate({
            "url": obj.get("url"),
            "logPreview": obj.get("logPreview"),
            "logTruncated": obj.get("logTruncated"),
            "nextToken": obj.get("nextToken")
        })
        return _obj