feat: add memoized _load_filter_sort_postprocess helper (#72)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

src/utils/table.py

@@ -5,6 +5,7 @@ import polars as pl
 from dash import no_update
 from polars import selectors as cs
 
+from src.cache import cache
 from src.db import query_marches, schema
 from src.utils import logger
 from src.utils.data import DATA_SCHEMA
@@ -373,6 +374,37 @@ def get_default_hidden_columns(page):
     return hidden_columns
 
 
+@cache.memoize()
+def _load_filter_sort_postprocess(filter_query, sort_by_key):
+    logger.debug(
+        f"Cache miss — recomputing for filter={filter_query!r} sort={sort_by_key!r}"
+    )
+
+    lff: pl.LazyFrame = query_marches().lazy()
+
+    if filter_query:
+        lff = filter_table_data(lff, filter_query, "tableau")
+
+    if sort_by_key:
+        sort_by = [
+            {"column_id": col, "direction": direction} for col, direction in sort_by_key
+        ]
+        lff = sort_table_data(lff, sort_by)
+
+    lff = lff.cast(pl.String)
+    lff = lff.fill_null("")
+
+    dff: pl.DataFrame = lff.collect()
+
+    dff = add_links(dff)
+    if "sourceFile" in dff.columns:
+        dff = add_resource_link(dff)
+    if dff.height > 0:
+        dff = format_values(dff)
+
+    return dff
+
+
 def prepare_table_data(
     data, data_timestamp, filter_query, page_current, page_size, sort_by, source_table
 ):

tests/test_table.py

@@ -78,3 +78,80 @@ def test_normalize_sort_by_preserves_order():
         [{"column_id": "b", "direction": "asc"}, {"column_id": "a", "direction": "asc"}]
     )
     assert a_then_b != b_then_a
+
+
+@pytest.fixture(scope="module")
+def flask_app():
+    """Minimal Flask app with SimpleCache so @cache.memoize() works in tests."""
+    from flask import Flask
+
+    from src.cache import cache
+
+    app = Flask(__name__)
+    cache.init_app(app, config={"CACHE_TYPE": "SimpleCache"})
+    return app
+
+
+@pytest.fixture(autouse=True)
+def reset_cache(flask_app):
+    """Ensure the flask-caching backend is empty between tests so that
+    cache-hit assertions are meaningful. Falls back to no-op when no
+    Flask app context is active (NullCache)."""
+    from src.cache import cache
+
+    with flask_app.app_context():
+        try:
+            cache.clear()
+        except (RuntimeError, AttributeError):
+            # No app context — cache is NullCache, nothing to clear
+            pass
+        yield
+
+
+def test_load_filter_sort_postprocess_returns_dataframe(
+    flask_app, monkeypatch, sample_lff
+):
+    from src.utils import table
+
+    monkeypatch.setattr(table, "query_marches", lambda: sample_lff.collect())
+
+    with flask_app.app_context():
+        df = table._load_filter_sort_postprocess(filter_query=None, sort_by_key=())
+
+    assert isinstance(df, pl.DataFrame)
+    assert df.height == 1
+    # All values must be strings after post-processing
+    for col in df.columns:
+        assert df.schema[col] == pl.String
+
+
+def test_load_filter_sort_postprocess_applies_filter(
+    flask_app, monkeypatch, sample_lff
+):
+    from src.utils import table
+
+    monkeypatch.setattr(table, "query_marches", lambda: sample_lff.collect())
+
+    with flask_app.app_context():
+        df = table._load_filter_sort_postprocess(
+            filter_query="{objet} icontains travaux", sort_by_key=()
+        )
+        assert df.height == 1
+
+        df_empty = table._load_filter_sort_postprocess(
+            filter_query="{objet} icontains nonexistent", sort_by_key=()
+        )
+        assert df_empty.height == 0
+
+
+def test_load_filter_sort_postprocess_adds_links(flask_app, monkeypatch, sample_lff):
+    from src.utils import table
+
+    monkeypatch.setattr(table, "query_marches", lambda: sample_lff.collect())
+
+    with flask_app.app_context():
+        df = table._load_filter_sort_postprocess(filter_query=None, sort_by_key=())
+    # add_links injects an <a href> wrapper around uid, acheteur_nom, titulaire_nom
+    assert "<a href" in df["uid"][0]
+    assert "<a href" in df["acheteur_nom"][0]
+    assert "<a href" in df["titulaire_nom"][0]