Files
2026-07-13 12:47:58 +08:00

127 lines
3.4 KiB
Python
Generated

import datetime
from collections.abc import Mapping
from typing import Any, TypeVar
from attrs import define as _attrs_define
from attrs import field as _attrs_field
from dateutil.parser import isoparse
T = TypeVar("T", bound="SandboxMetric")
@_attrs_define
class SandboxMetric:
"""Metric entry with timestamp and line
Attributes:
cpu_count (int): Number of CPU cores
cpu_used_pct (float): CPU usage percentage
disk_total (int): Total disk space in bytes
disk_used (int): Disk used in bytes
mem_cache (int): Cached memory (page cache) in bytes
mem_total (int): Total memory in bytes
mem_used (int): Memory used in bytes
timestamp (datetime.datetime): Timestamp of the metric entry
timestamp_unix (int): Timestamp of the metric entry in Unix time (seconds since epoch)
"""
cpu_count: int
cpu_used_pct: float
disk_total: int
disk_used: int
mem_cache: int
mem_total: int
mem_used: int
timestamp: datetime.datetime
timestamp_unix: int
additional_properties: dict[str, Any] = _attrs_field(init=False, factory=dict)
def to_dict(self) -> dict[str, Any]:
cpu_count = self.cpu_count
cpu_used_pct = self.cpu_used_pct
disk_total = self.disk_total
disk_used = self.disk_used
mem_cache = self.mem_cache
mem_total = self.mem_total
mem_used = self.mem_used
timestamp = self.timestamp.isoformat()
timestamp_unix = self.timestamp_unix
field_dict: dict[str, Any] = {}
field_dict.update(self.additional_properties)
field_dict.update(
{
"cpuCount": cpu_count,
"cpuUsedPct": cpu_used_pct,
"diskTotal": disk_total,
"diskUsed": disk_used,
"memCache": mem_cache,
"memTotal": mem_total,
"memUsed": mem_used,
"timestamp": timestamp,
"timestampUnix": timestamp_unix,
}
)
return field_dict
@classmethod
def from_dict(cls: type[T], src_dict: Mapping[str, Any]) -> T:
d = dict(src_dict)
cpu_count = d.pop("cpuCount")
cpu_used_pct = d.pop("cpuUsedPct")
disk_total = d.pop("diskTotal")
disk_used = d.pop("diskUsed")
mem_cache = d.pop("memCache")
mem_total = d.pop("memTotal")
mem_used = d.pop("memUsed")
timestamp = isoparse(d.pop("timestamp"))
timestamp_unix = d.pop("timestampUnix")
sandbox_metric = cls(
cpu_count=cpu_count,
cpu_used_pct=cpu_used_pct,
disk_total=disk_total,
disk_used=disk_used,
mem_cache=mem_cache,
mem_total=mem_total,
mem_used=mem_used,
timestamp=timestamp,
timestamp_unix=timestamp_unix,
)
sandbox_metric.additional_properties = d
return sandbox_metric
@property
def additional_keys(self) -> list[str]:
return list(self.additional_properties.keys())
def __getitem__(self, key: str) -> Any:
return self.additional_properties[key]
def __setitem__(self, key: str, value: Any) -> None:
self.additional_properties[key] = value
def __delitem__(self, key: str) -> None:
del self.additional_properties[key]
def __contains__(self, key: str) -> bool:
return key in self.additional_properties