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Handle malformed API response values in model parsing #5

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38 changes: 29 additions & 9 deletions src/discourses/models.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,26 @@
from typing import Any, Dict, List, Optional


def _safe_float(value: Any, default: float = 0.0) -> float:
"""Safely convert value to float, returning default on failure."""
if value is None:
return default
try:
return float(value)
except (ValueError, TypeError):
return default


def _safe_int(value: Any, default: int = 0) -> int:
"""Safely convert value to int, returning default on failure."""
if value is None:
return default
try:
return int(value)
except (ValueError, TypeError):
return default


@dataclass
class AnalysisResult:
"""
Expand Down Expand Up @@ -51,17 +71,17 @@ def from_dict(cls, data: Dict[str, Any]) -> "AnalysisResult":

return cls(
label=classification.get("label", "neutral"),
confidence=float(classification.get("confidence", 0)),
outlook=float(scores.get("outlook", 0)),
confidence=_safe_float(classification.get("confidence")),
outlook=_safe_float(scores.get("outlook")),
scores={
"bullish": float(scores.get("bullish", 0)),
"bearish": float(scores.get("bearish", 0)),
"neutral": float(scores.get("neutral", 0)),
"confusion": float(scores.get("confusion", 0)),
"bullish": _safe_float(scores.get("bullish")),
"bearish": _safe_float(scores.get("bearish")),
"neutral": _safe_float(scores.get("neutral")),
"confusion": _safe_float(scores.get("confusion")),
},
word_count=int(analysis.get("word_count", 0)),
matched_count=int(analysis.get("matched_count", 0)),
negation_count=int(analysis.get("negation_count", 0)),
word_count=_safe_int(analysis.get("word_count")),
matched_count=_safe_int(analysis.get("matched_count")),
negation_count=_safe_int(analysis.get("negation_count")),
raw=data,
)

Expand Down