Source code for flatland.integrations.interactiveai.context_api.models.metadata_schema_railway
# coding: utf-8
"""
APIFlask
No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator)
The version of the OpenAPI document: 0.1.0
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
from typing import Optional, Set
from pydantic import BaseModel, ConfigDict, StrictInt
from typing_extensions import Self
[docs]
class MetadataSchemaRailway(BaseModel):
"""
MetadataSchemaRailway
""" # noqa: E501
direction_agents: Optional[List[StrictInt]] = None
list_of_target: Optional[Dict[str, Any]] = None
position_agents: Optional[Dict[str, Any]] = None
trains: Optional[List[Dict[str, Any]]] = None
__properties: ClassVar[List[str]] = ["direction_agents", "list_of_target", "position_agents", "trains"]
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 MetadataSchemaRailway 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 MetadataSchemaRailway from a dict"""
if obj is None:
return None
if not isinstance(obj, dict):
return cls.model_validate(obj)
_obj = cls.model_validate({
"direction_agents": obj.get("direction_agents"),
"list_of_target": obj.get("list_of_target"),
"position_agents": obj.get("position_agents"),
"trains": obj.get("trains")
})
return _obj