"""Rendu HTML « Recherchabilité fuzzy » — Sprint 86 (A.II.5a HTML).
Suite directe ``picarones/core/searchability.py`` (Sprint 84) +
câblage runner (Sprint 86).
Pattern identique aux autres rendus (Sprints 41/43/62/67/72) :
**server-side**, pas de JavaScript, anti-injection systématique.
Vue
---
Tableau résumé : moteur × (rappel, n_searchable / n_gt_tokens,
docs). Cellule rappel colorée par gradient rouge → vert.
Adaptative : ``""`` si aucun moteur n'a de
``aggregated_searchability``.
"""
from __future__ import annotations
from html import escape as _e
from typing import Optional
from picarones.report.render_helpers import color_traffic_light
def build_searchability_summary_html(
engines: list[dict],
labels: Optional[dict[str, str]] = None,
) -> str:
"""Construit la table HTML de recherchabilité.
Parameters
----------
engines:
Liste de dicts moteur ; chacun peut avoir
``aggregated_searchability``.
labels:
Dict i18n, clés ``search_*``.
Returns
-------
str
``""`` si aucun moteur n'a de signal.
"""
rows = [
e for e in engines
if isinstance(e.get("aggregated_searchability"), dict)
]
if not rows:
return ""
labels = labels or {}
title = labels.get("search_title", "Recherchabilité fuzzy")
note = labels.get(
"search_note",
"Proportion de tokens GT retrouvés dans la sortie OCR à "
"distance de Levenshtein ≤ 2 — proxy direct de la "
"qualité pour la recherche plein-texte (Elastic, Solr).",
)
col_engine = labels.get("search_engine", "Moteur")
col_recall = labels.get("search_recall", "Rappel")
col_count = labels.get("search_count", "Tokens retrouvés / total")
col_docs = labels.get("search_docs", "Docs")
parts = [
'',
f'
{_e(title)}
',
f'
'
f'{_e(note)}
',
'
',
'',
]
for col in (col_engine, col_recall, col_count, col_docs):
parts.append(
f'| '
f'{_e(col)} | '
)
parts.append("
")
for engine in rows:
agg = engine["aggregated_searchability"]
name = engine.get("name") or "?"
recall = float(agg.get("recall") or 0.0)
n_search = int(agg.get("n_searchable") or 0)
n_total = int(agg.get("n_gt_tokens") or 0)
n_docs = int(agg.get("n_docs") or 0)
color = color_traffic_light(recall)
parts.append(
f''
f'| {_e(str(name))} | '
f''
f'{recall * 100:.1f}% | '
f'{n_search} / {n_total} | '
f'{n_docs} | '
f'
'
)
parts.append("