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Class BatchResult

quantmind/flows/batch.py:22–48  ·  view source on GitHub ↗

Aggregate result of running a flow over many inputs. ``results[i]`` is the output for ``inputs[i]`` or ``None`` if that input failed. ``errors`` carries ``(index, exception)`` for every failure, sorted by index. ``successes`` and ``failures`` are convenience views derived from these

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20
21@dataclass(slots=True)
22class BatchResult(Generic[OutputT]):
23 """Aggregate result of running a flow over many inputs.
24
25 ``results[i]`` is the output for ``inputs[i]`` or ``None`` if that
26 input failed. ``errors`` carries ``(index, exception)`` for every
27 failure, sorted by index. ``successes`` and ``failures`` are
28 convenience views derived from these primary fields.
29 """
30
31 total: int
32 success_count: int
33 failure_count: int
34 results: list[OutputT | None]
35 errors: list[tuple[int, Exception]]
36 duration_seconds: float
37 tokens_total: dict[str, int] = field(default_factory=dict)
38 cost_estimate_usd: float = 0.0
39
40 @property
41 def successes(self) -> list[tuple[int, OutputT]]:
42 """``(index, result)`` for every input that succeeded."""
43 return [(i, r) for i, r in enumerate(self.results) if r is not None]
44
45 @property
46 def failures(self) -> list[tuple[int, Exception]]:
47 """Alias for ``errors`` to mirror ``successes`` for symmetry."""
48 return list(self.errors)
49
50
51async def batch_run(

Callers 2

batch_runFunction · 0.85

Calls

no outgoing calls

Tested by 1