Source code for openapi_client.models.optimizer_run

# 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 datetime import datetime
from pydantic import BaseModel, ConfigDict, Field, StrictStr
from typing import Any, ClassVar, Dict, List, Optional
from typing import Optional, Set
from typing_extensions import Self



class OptimizerRun(BaseModel):
    """
    Information about an optimizer run
    """ # noqa: E501
    event_type: Optional[StrictStr] = Field(default=None, description="Type of event for the run", alias="EventType")
    start_timestamp: Optional[datetime] = Field(default=None, description="Start timestamp of the run", alias="StartTimestamp")
    end_timestamp: Optional[datetime] = Field(default=None, description="End timestamp of the run", alias="EndTimestamp")
    compaction_metrics: Optional[Dict[str, Any]] = Field(default=None, description="Metrics for compaction optimizer runs", alias="CompactionMetrics")
    retention_metrics: Optional[Dict[str, Any]] = Field(default=None, description="Metrics for retention optimizer runs", alias="RetentionMetrics")
    orphan_file_deletion_metrics: Optional[Dict[str, Any]] = Field(default=None, description="Metrics for orphan file deletion optimizer runs", alias="OrphanFileDeletionMetrics")
    __properties: ClassVar[List[str]] = ["EventType", "StartTimestamp", "EndTimestamp", "CompactionMetrics", "RetentionMetrics", "OrphanFileDeletionMetrics"]

    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 OptimizerRun 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,
        )
        return _dict




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

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

        _obj = cls.model_validate({
            "EventType": obj.get("EventType"),
            "StartTimestamp": obj.get("StartTimestamp"),
            "EndTimestamp": obj.get("EndTimestamp"),
            "CompactionMetrics": obj.get("CompactionMetrics"),
            "RetentionMetrics": obj.get("RetentionMetrics"),
            "OrphanFileDeletionMetrics": obj.get("OrphanFileDeletionMetrics")
        })
        return _obj