# coding: utf-8 """ Daytona Daytona AI platform API Docs The version of the OpenAPI document: 1.0 Contact: support@daytona.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, StrictInt, StrictStr, field_validator from typing import Any, ClassVar, Dict, List, Optional from daytona_api_client.models.create_build_info import CreateBuildInfo from daytona_api_client.models.sandbox_volume import SandboxVolume from pydantic import TypeAdapter from typing import Optional, Set from typing_extensions import Self _JSON_ADAPTER = TypeAdapter(Dict[str, Any]) class CreateWorkspace(BaseModel): """ CreateWorkspace """ # noqa: E501 image: Optional[StrictStr] = Field(default=None, description="The image used for the workspace") user: Optional[StrictStr] = Field(default=None, description="The user associated with the project") env: Optional[Dict[str, StrictStr]] = Field(default=None, description="Environment variables for the workspace") labels: Optional[Dict[str, StrictStr]] = Field(default=None, description="Labels for the workspace") public: Optional[StrictBool] = Field(default=None, description="Whether the workspace http preview is publicly accessible") var_class: Optional[StrictStr] = Field(default=None, description="The workspace class type", serialization_alias="class") target: Optional[StrictStr] = Field(default=None, description="The target (region) where the workspace will be created") cpu: Optional[StrictInt] = Field(default=None, description="CPU cores allocated to the workspace") gpu: Optional[StrictInt] = Field(default=None, description="GPU units allocated to the workspace") memory: Optional[StrictInt] = Field(default=None, description="Memory allocated to the workspace in GB") disk: Optional[StrictInt] = Field(default=None, description="Disk space allocated to the workspace in GB") auto_stop_interval: Optional[StrictInt] = Field(default=None, description="Auto-stop interval in minutes (0 means disabled)", serialization_alias="autoStopInterval") auto_archive_interval: Optional[StrictInt] = Field(default=None, description="Auto-archive interval in minutes (0 means the maximum interval will be used)", serialization_alias="autoArchiveInterval") volumes: Optional[List[SandboxVolume]] = Field(default=None, description="Array of volumes to attach to the workspace") build_info: Optional[CreateBuildInfo] = Field(default=None, description="Build information for the workspace", serialization_alias="buildInfo") additional_properties: Dict[str, Any] = {} __properties: ClassVar[List[str]] = ["image", "user", "env", "labels", "public", "class", "target", "cpu", "gpu", "memory", "disk", "autoStopInterval", "autoArchiveInterval", "volumes", "buildInfo"] @field_validator('var_class') def var_class_validate_enum(cls, value): """Validates the enum""" if value is None: return value if value not in set(['small', 'medium', 'large']): raise ValueError("must be one of enum values ('small', 'medium', 'large')") return value @field_validator('target') def target_validate_enum(cls, value): """Validates the enum""" if value is None: return value if value not in set(['eu', 'us', 'asia']): raise ValueError("must be one of enum values ('eu', 'us', 'asia')") 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""" return _JSON_ADAPTER.dump_json(self.to_dict()).decode() @classmethod def from_json(cls, json_str: str) -> Optional[Self]: """Create an instance of CreateWorkspace 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, ) # override the default output from pydantic by calling `to_dict()` of each item in volumes (list) _items = [] if self.volumes: for _item_volumes in self.volumes: if _item_volumes: _items.append(_item_volumes.to_dict()) _dict['volumes'] = _items # override the default output from pydantic by calling `to_dict()` of build_info if self.build_info: _dict['buildInfo'] = self.build_info.to_dict() # 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 CreateWorkspace from a dict""" if obj is None: return None if not isinstance(obj, dict): return cls.model_validate(obj) _obj = cls.model_validate({ "image": obj.get("image"), "user": obj.get("user"), "env": obj.get("env"), "labels": obj.get("labels"), "public": obj.get("public"), "var_class": obj.get("class"), "target": obj.get("target"), "cpu": obj.get("cpu"), "gpu": obj.get("gpu"), "memory": obj.get("memory"), "disk": obj.get("disk"), "auto_stop_interval": obj.get("autoStopInterval"), "auto_archive_interval": obj.get("autoArchiveInterval"), "volumes": [SandboxVolume.from_dict(_item) for _item in obj["volumes"]] if obj.get("volumes") is not None else None, "build_info": CreateBuildInfo.from_dict(obj["buildInfo"]) if obj.get("buildInfo") is not None else None }) # 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