Add region, min_hero_matches_per_player and max_hero_matches_per_play…

…er filters to hero win loss stats endpoint

deadlock_analytics_api/routers/v2.py

@@ -161,36 +161,54 @@ def get_hero_win_loss_stats(
     res: Response,
     min_badge_level: Annotated[int | None, Query(ge=0)] = None,
     max_badge_level: Annotated[int | None, Query(le=116)] = None,
+    min_hero_matches_per_player: Annotated[int | None, Query(ge=0)] = None,
+    max_hero_matches_per_player: int = None,
     min_unix_timestamp: Annotated[int | None, Query(ge=0)] = None,
-    max_unix_timestamp: Annotated[int | None, Query(le=4070908800)] = None,
+    max_unix_timestamp: int | None = None,
     match_mode: Literal["Ranked", "Unranked"] | None = None,
+    region: (
+        Literal["Row", "Europe", "SEAsia", "SAmerica", "Russia", "Oceania"] | None
+    ) = None,
 ) -> list[HeroWinLossStat]:
     limiter.apply_limits(
         req, res, "/v2/hero-win-loss-stats", [RateLimit(limit=100, period=1)]
     )
     res.headers["Cache-Control"] = "public, max-age=1200"
     query = """
-    SELECT hero_id,
-            countIf(team == mi.winning_team) AS wins,
-            countIf(team != mi.winning_team) AS losses
-    FROM default.match_player
-    INNER JOIN match_info mi USING (match_id)
-    WHERE ranked_badge_level IS NULL OR (ranked_badge_level >= %(min_badge_level)s AND ranked_badge_level <= %(max_badge_level)s)
-    AND mi.start_time >= toDateTime(%(min_unix_timestamp)s) AND mi.start_time <= toDateTime(%(max_unix_timestamp)s)
-    AND (%(match_mode)s IS NULL OR mi.match_mode = %(match_mode)s)
+    WITH filtered_players AS (
+        SELECT hero_id, account_id, countIf(team == mi.winning_team) AS player_wins, countIf(team != mi.winning_team) AS player_losses
+        FROM match_player
+        INNER JOIN match_info mi USING (match_id)
+        INNER JOIN player p USING (account_id)
+        WHERE 1=1
+        AND (ranked_badge_level IS NULL OR %(min_badge_level)s IS NULL OR ranked_badge_level >= %(min_badge_level)s)
+        AND (ranked_badge_level IS NULL OR %(max_badge_level)s IS NULL OR ranked_badge_level <= %(max_badge_level)s)
+        AND (%(min_unix_timestamp)s IS NULL OR mi.start_time >= toDateTime(%(min_unix_timestamp)s))
+        AND (%(max_unix_timestamp)s IS NULL OR mi.start_time <= toDateTime(%(max_unix_timestamp)s))
+        AND (%(match_mode)s IS NULL OR mi.match_mode = %(match_mode)s)
+        AND (%(match_mode)s IS NULL OR mi.match_mode = %(match_mode)s)
+        AND (%(region)s IS NULL OR p.region_mode = %(region)s)
+        GROUP BY hero_id, account_id
+    )
+    SELECT hero_id, sum(player_wins) AS wins, sum(player_losses) AS losses
+    FROM filtered_players
+    WHERE (%(min_hero_matches)s IS NULL OR player_wins + player_losses <= %(min_hero_matches)s)
+    AND (%(max_hero_matches)s IS NULL OR player_wins + player_losses <= %(max_hero_matches)s)
     GROUP BY hero_id
-    HAVING wins + losses > 100
     ORDER BY wins + losses DESC;
     """
     with CH_POOL.get_client() as client:
         result = client.execute(
             query,
             {
-                "min_badge_level": min_badge_level or 0,
-                "max_badge_level": max_badge_level or 116,
-                "min_unix_timestamp": min_unix_timestamp or 0,
-                "max_unix_timestamp": max_unix_timestamp or 4070908800,
+                "min_badge_level": min_badge_level,
+                "max_badge_level": max_badge_level,
+                "min_unix_timestamp": min_unix_timestamp,
+                "max_unix_timestamp": max_unix_timestamp,
                 "match_mode": match_mode,
+                "region": region,
+                "min_hero_matches": min_hero_matches_per_player,
+                "max_hero_matches": max_hero_matches_per_player,
             },
         )
     return [HeroWinLossStat(hero_id=r[0], wins=r[1], losses=r[2]) for r in result]