blob: 636ad4ad37c15befd970b523b52871007c097745 [file]
# coding: utf-8
"""
Airflow API
Airflow API. All endpoints located under ``/api/v2`` can be used safely, are stable and backward compatible. Endpoints located under ``/ui`` are dedicated to the UI and are subject to breaking change depending on the need of the frontend. Users should not rely on those but use the public ones instead. **Filtering with pattern parameters.** Many list endpoints accept ``*_pattern`` and ``*_prefix_pattern`` query parameters. Unless a parameter's own description says otherwise, ``*_pattern`` is a case-insensitive substring match (SQL ``ILIKE '%term%'``) where ``%`` matches any sequence and ``_`` matches any single character (e.g. ``%customer_%``) — convenient, but it cannot use B-tree indexes, so it is slow on large tables. ``*_prefix_pattern`` matches the start of the value, is case-sensitive and index-friendly (prefer it at scale); there ``%`` and ``_`` are literal and trailing non-alphanumeric characters are stripped so the range scan stays index-compatible under locale-aware collations (e.g. ``test_`` matches values starting with ``test``, and ``s3://`` matches ``s3``). In both, ``|`` means OR (e.g. ``dag1|dag2``) and ``~`` matches everything. Regular expressions are not supported by these parameters; regex-capable endpoints expose a separate parameter.
The version of the OpenAPI document: 2
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
from typing import Any, ClassVar, Dict, List, Optional
from airflow_client.client.models.validation_error import ValidationError
from typing import Optional, Set
from typing_extensions import Self
from pydantic_core import to_jsonable_python
class HTTPValidationError(BaseModel):
"""
HTTPValidationError
""" # noqa: E501
detail: Optional[List[ValidationError]] = None
__properties: ClassVar[List[str]] = ["detail"]
model_config = ConfigDict(
validate_by_name=True,
validate_by_alias=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.dumps(to_jsonable_python(self.to_dict()))
@classmethod
def from_json(cls, json_str: str) -> Optional[Self]:
"""Create an instance of HTTPValidationError 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,
)
# override the default output from pydantic by calling `to_dict()` of each item in detail (list)
_items = []
if self.detail:
for _item_detail in self.detail:
if _item_detail:
_items.append(_item_detail.to_dict())
_dict['detail'] = _items
return _dict
@classmethod
def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
"""Create an instance of HTTPValidationError from a dict"""
if obj is None:
return None
if not isinstance(obj, dict):
return cls.model_validate(obj)
_obj = cls.model_validate({
"detail": [ValidationError.from_dict(_item) for _item in obj["detail"]] if obj.get("detail") is not None else None
})
return _obj