Update match_parser.py

match_parser.py

@@ -10,7 +10,7 @@ import seaborn as sns
 from bs4 import BeautifulSoup
 from wordcloud import WordCloud
 
-from util import get_max_abs_int, snake_case_to_human_readable
+from util import get_max_abs_int, snake_case_to_human_readable, int_csv_to_list
 
 
 def _rename_columns(df: pd.DataFrame, is_tournament: bool) -> pd.DataFrame:
@@ -308,6 +308,26 @@ def get_opponent_rating_dist_over_time_fig(df: pd.DataFrame, is_tournament: bool
     return fig
 
 
+def get_total_match_points(score_str: str) -> int:
+  single_game_scores = int_csv_to_list(score_str)
+  total_points = 0
+  for single_game_score in single_game_scores:
+    abs_gscore = abs(single_game_score)
+    if abs_gscore < 10:
+      total_points += abs_gscore + 11
+    else:
+      total_points += 2 * abs_gscore + 2
+  return total_points
+
+def get_longest_match(df: pd.DataFrame, is_tournament: bool) -> Optional[pd.DataFrame]:
+    """Get the longest match, where longest is defined as the most number of points played."""
+    if not is_tournament:
+        return None
+    df_non_null = df.loc[~df.scores.isna()]
+    df_non_null["total_points"] = df_non_null.scores.apply(get_total_match_points)
+    return df_non_null.iloc[[df_non_null["total_points"].argmax()]]
+
+
 def load_match_df(file_path: Path) -> Tuple[pd.DataFrame, bool]:
     match_type = _check_match_type(file_path.name.split('_')[0])
     is_tournament = match_type == "tournament"