fix: connection leak, Rice index excludes absences, per-party motion count guard

main
Sven Geboers 1 month ago
parent bcf9407957
commit 50f8a06c6d
  1. 21
      explorer.py

@ -258,7 +258,10 @@ def compute_party_discipline(
Rice index per motion per party = fraction of party MPs voting with the party majority. Rice index per motion per party = fraction of party MPs voting with the party majority.
The per-party score is the average Rice index across all motions in the date range. The per-party score is the average Rice index across all motions in the date range.
Only 'voor' and 'tegen' votes are counted; absent and abstaining MPs are excluded from the
Rice index calculation.
""" """
conn = None
try: try:
conn = duckdb.connect(db_path, read_only=True) conn = duckdb.connect(db_path, read_only=True)
result = conn.execute( result = conn.execute(
@ -272,7 +275,7 @@ def compute_party_discipline(
WHERE mp_name LIKE '%,%' WHERE mp_name LIKE '%,%'
AND date >= CAST(? AS DATE) AND date >= CAST(? AS DATE)
AND date <= CAST(? AS DATE) AND date <= CAST(? AS DATE)
AND vote IN ('voor', 'tegen', 'afwezig', 'onthouden') AND vote IN ('voor', 'tegen')
), ),
vote_counts AS ( vote_counts AS (
SELECT SELECT
@ -313,11 +316,16 @@ def compute_party_discipline(
""", """,
[start_date, end_date], [start_date, end_date],
).fetchdf() ).fetchdf()
conn.close()
return result return result
except Exception as exc: except Exception as exc:
logger.warning("compute_party_discipline failed: %s", exc) logger.warning("compute_party_discipline failed: %s", exc)
return pd.DataFrame(columns=["party", "n_motions", "discipline"]) return pd.DataFrame(columns=["party", "n_motions", "discipline"])
finally:
if conn is not None:
try:
conn.close()
except Exception:
pass
@st.cache_data(show_spinner="Partijposities op SVD-assen laden…") @st.cache_data(show_spinner="Partijposities op SVD-assen laden…")
@ -955,14 +963,19 @@ def build_compass_tab(db_path: str, window_size: str) -> None:
disc_df = compute_party_discipline(db_path, start_date, end_date) disc_df = compute_party_discipline(db_path, start_date, end_date)
st.subheader("Stemgedrag cohesie") st.subheader("Stemgedrag cohesie")
if disc_df.empty or disc_df["n_motions"].max() < _MIN_MOTIONS_FOR_DISCIPLINE: if disc_df.empty:
st.caption(
"Te weinig hoofdelijke stemmingen in dit venster voor een cohesieanalyse."
)
else:
disc_df = disc_df[disc_df["n_motions"] >= _MIN_MOTIONS_FOR_DISCIPLINE].copy()
if disc_df.empty:
st.caption( st.caption(
"Te weinig hoofdelijke stemmingen in dit venster voor een cohesieanalyse." "Te weinig hoofdelijke stemmingen in dit venster voor een cohesieanalyse."
) )
else: else:
compass_parties = set(df_pos["party"].unique()) compass_parties = set(df_pos["party"].unique())
disc_df = disc_df[disc_df["party"].isin(compass_parties)].copy() disc_df = disc_df[disc_df["party"].isin(compass_parties)].copy()
if disc_df.empty: if disc_df.empty:
st.caption("Geen overlappende partijen tussen kompas en stemmingsdata.") st.caption("Geen overlappende partijen tussen kompas en stemmingsdata.")
else: else:

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