Process historical bootstrap and leaderboard tasks
This commit is contained in:
devRaGonSa
@@ -47,6 +47,7 @@ SUPPORTED_WEEKLY_LEADERBOARD_METRICS = frozenset(
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"matches_over_100_kills",
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}
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)
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SUPPORTED_MONTHLY_LEADERBOARD_METRICS = SUPPORTED_WEEKLY_LEADERBOARD_METRICS
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def initialize_historical_storage(*, db_path: Path | None = None) -> Path:
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@@ -1289,6 +1290,165 @@ def list_weekly_top_kills(
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}
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def list_monthly_leaderboard(
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*,
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limit: int = 10,
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server_id: str | None = None,
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metric: str = "kills",
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db_path: Path | None = None,
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) -> dict[str, object]:
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"""Return ranked monthly leaderboard totals from persisted historical match stats."""
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resolved_path = initialize_historical_storage(db_path=db_path)
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aggregate_all_servers = _is_all_servers_selector(server_id)
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current_time = datetime.now(timezone.utc)
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current_month_start = _start_of_month(current_time)
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previous_month_start = _start_of_previous_month(current_month_start)
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normalized_metric = metric.strip() if isinstance(metric, str) else ""
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if normalized_metric not in SUPPORTED_MONTHLY_LEADERBOARD_METRICS:
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raise ValueError(f"Unsupported monthly leaderboard metric: {metric}")
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monthly_window = _select_monthly_window(
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server_id=server_id,
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current_time=current_time,
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current_month_start=current_month_start,
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previous_month_start=previous_month_start,
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db_path=resolved_path,
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)
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window_start = monthly_window["window_start"]
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window_end = monthly_window["window_end"]
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where_clauses = [
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"historical_matches.ended_at IS NOT NULL",
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"historical_matches.ended_at >= ?",
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"historical_matches.ended_at < ?",
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]
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params: list[object] = [
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window_start.isoformat().replace("+00:00", "Z"),
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window_end.isoformat().replace("+00:00", "Z"),
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]
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if server_id and not aggregate_all_servers:
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normalized_server_id = server_id.strip()
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where_clauses.append(
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"(historical_servers.slug = ? OR CAST(historical_servers.server_number AS TEXT) = ?)"
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)
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params.extend([normalized_server_id, normalized_server_id])
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server_slug_expression = (
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f"'{ALL_SERVERS_SLUG}'"
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if aggregate_all_servers
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else "historical_servers.slug"
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)
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server_name_expression = (
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f"'{ALL_SERVERS_DISPLAY_NAME}'"
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if aggregate_all_servers
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else "historical_servers.display_name"
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)
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partition_expression = (
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f"'{ALL_SERVERS_SLUG}'"
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if aggregate_all_servers
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else "historical_servers.slug"
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)
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group_by_expression = (
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"historical_players.id"
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if aggregate_all_servers
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else "historical_servers.slug, historical_players.id"
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)
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metric_sum_expression = {
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"kills": "COALESCE(SUM(historical_player_match_stats.kills), 0)",
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"deaths": "COALESCE(SUM(historical_player_match_stats.deaths), 0)",
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"support": "COALESCE(SUM(historical_player_match_stats.support), 0)",
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"matches_over_100_kills": (
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"COALESCE(SUM(CASE WHEN COALESCE(historical_player_match_stats.kills, 0) >= 100 "
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"THEN 1 ELSE 0 END), 0)"
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),
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}[normalized_metric]
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with _connect(resolved_path) as connection:
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rows = connection.execute(
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f"""
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WITH ranked_players AS (
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SELECT
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{server_slug_expression} AS server_slug,
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{server_name_expression} AS server_name,
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historical_players.stable_player_key,
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historical_players.display_name AS player_name,
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historical_players.steam_id,
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COUNT(DISTINCT historical_matches.id) AS matches_count,
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{metric_sum_expression} AS metric_value,
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ROW_NUMBER() OVER (
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PARTITION BY {partition_expression}
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ORDER BY
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{metric_sum_expression} DESC,
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COUNT(DISTINCT historical_matches.id) ASC,
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historical_players.display_name ASC
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) AS ranking_position
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FROM historical_player_match_stats
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INNER JOIN historical_matches
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ON historical_matches.id = historical_player_match_stats.historical_match_id
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INNER JOIN historical_servers
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ON historical_servers.id = historical_matches.historical_server_id
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INNER JOIN historical_players
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ON historical_players.id = historical_player_match_stats.historical_player_id
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WHERE {" AND ".join(where_clauses)}
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GROUP BY {group_by_expression}
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)
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SELECT *
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FROM ranked_players
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WHERE ranking_position <= ?
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ORDER BY server_slug ASC, ranking_position ASC
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""",
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[*params, limit],
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).fetchall()
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window_days = _calculate_window_days(window_start=window_start, window_end=window_end)
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items: list[dict[str, object]] = []
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for row in rows:
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items.append(
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{
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"server": {
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"slug": row["server_slug"],
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"name": row["server_name"],
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},
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"time_range": {
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"start": window_start.isoformat().replace("+00:00", "Z"),
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"end": window_end.isoformat().replace("+00:00", "Z"),
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"window_days": window_days,
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},
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"player": {
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"stable_player_key": row["stable_player_key"],
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"name": row["player_name"],
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"steam_id": row["steam_id"],
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},
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"metric": normalized_metric,
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"ranking_position": int(row["ranking_position"]),
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"metric_value": int(row["metric_value"] or 0),
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"matches_considered": int(row["matches_count"] or 0),
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}
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)
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return {
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"timeframe": "monthly",
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"metric": normalized_metric,
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"window_start": window_start.isoformat().replace("+00:00", "Z"),
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"window_end": window_end.isoformat().replace("+00:00", "Z"),
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"window_days": window_days,
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"window_kind": monthly_window["window_kind"],
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"window_label": monthly_window["window_label"],
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"uses_fallback": monthly_window["uses_fallback"],
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"selection_reason": monthly_window["selection_reason"],
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"current_month_start": current_month_start.isoformat().replace("+00:00", "Z"),
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"current_month_closed_matches": monthly_window["current_month_closed_matches"],
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"previous_month_closed_matches": monthly_window["previous_month_closed_matches"],
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"sufficient_sample": {
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"minimum_closed_matches": monthly_window["minimum_closed_matches"],
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"current_month_closed_matches": monthly_window["current_month_closed_matches"],
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"current_month_has_sufficient_sample": monthly_window["current_month_has_sufficient_sample"],
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"is_early_month": monthly_window["is_early_month"],
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},
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"items": items,
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}
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def _connect(db_path: Path) -> sqlite3.Connection:
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connection = sqlite3.connect(db_path)
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connection.row_factory = sqlite3.Row
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@@ -2236,6 +2396,59 @@ def _select_weekly_window(
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}
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def _select_monthly_window(
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*,
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server_id: str | None,
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current_time: datetime,
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current_month_start: datetime,
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previous_month_start: datetime,
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db_path: Path,
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) -> dict[str, object]:
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current_month_closed_matches = _count_closed_matches_in_window(
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server_id=server_id,
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window_start=current_month_start,
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window_end=current_time,
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db_path=db_path,
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)
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previous_month_closed_matches = _count_closed_matches_in_window(
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server_id=server_id,
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window_start=previous_month_start,
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window_end=current_month_start,
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db_path=db_path,
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)
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is_early_month = current_time.day <= 3
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uses_fallback = current_month_closed_matches <= 0 and previous_month_closed_matches > 0
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if uses_fallback:
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return {
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"window_start": previous_month_start,
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"window_end": current_month_start,
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"window_kind": "previous-closed-month-fallback",
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"window_label": "Mes cerrado anterior",
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"uses_fallback": True,
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"selection_reason": "no-current-month-matches",
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"minimum_closed_matches": 1,
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"current_month_closed_matches": current_month_closed_matches,
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"previous_month_closed_matches": previous_month_closed_matches,
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"current_month_has_sufficient_sample": False,
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"is_early_month": is_early_month,
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}
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return {
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"window_start": current_month_start,
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"window_end": current_time,
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"window_kind": "current-month",
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"window_label": "Mes actual",
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"uses_fallback": False,
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"selection_reason": "current-month",
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"minimum_closed_matches": 1,
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"current_month_closed_matches": current_month_closed_matches,
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"previous_month_closed_matches": previous_month_closed_matches,
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"current_month_has_sufficient_sample": current_month_closed_matches > 0,
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"is_early_month": is_early_month,
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}
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def _count_closed_matches_in_window(
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*,
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server_id: str | None,
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@@ -2408,6 +2621,21 @@ def _start_of_week(value: datetime) -> datetime:
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return midnight - timedelta(days=midnight.weekday())
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def _start_of_month(value: datetime) -> datetime:
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normalized = value.astimezone(timezone.utc)
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return normalized.replace(day=1, hour=0, minute=0, second=0, microsecond=0)
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def _start_of_previous_month(value: datetime) -> datetime:
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previous_day = value - timedelta(days=1)
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return _start_of_month(previous_day)
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def _calculate_window_days(*, window_start: datetime, window_end: datetime) -> int:
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delta = window_end - window_start
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return max(1, int((delta.total_seconds() + 86399) // 86400))
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def _get_nested(payload: Mapping[str, object], *path: str) -> object:
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current: object = payload
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for key in path:
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