fix: derive SEASON_PCT from date range instead of hardcoding half-season (#9)

Closes #9

Previously SEASON_PCT was hardcoded to 81/162 (~0.5) while END_DATE was
set to 20050731 (~65% through the season). Running retrosheet_data.py
directly (without the CLI which overrides SEASON_PCT at runtime) would
silently generate cards using half-season normalizations on stats covering
a larger portion of the season.

Fix: move START_DATE/END_DATE before SEASON_PCT and derive SEASON_PCT
from the date range using SEASON_END_DATE (2005 regular season end).
Now changing END_DATE automatically produces the correct SEASON_PCT.

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

retrosheet_data.py

@@ -60,10 +60,21 @@ MIN_TBF_VR = 40
 CARDSET_ID = 27  # 27: 2005 Live, 28: 2005 Promos
 
 # Per-Update Parameters
-SEASON_PCT = 81 / 162  # Through end of July (~half season)
 START_DATE = 20050403  # YYYYMMDD format - 2005 Opening Day
 # END_DATE = 20050531     # YYYYMMDD format - May PotM
 END_DATE = 20050731  # End of July 2005
+SEASON_END_DATE = 20051002  # 2005 regular season end date (used to derive SEASON_PCT)
+SEASON_PCT = min(
+    (
+        datetime.datetime.strptime(str(END_DATE), "%Y%m%d")
+        - datetime.datetime.strptime(str(START_DATE), "%Y%m%d")
+    ).days
+    / (
+        datetime.datetime.strptime(str(SEASON_END_DATE), "%Y%m%d")
+        - datetime.datetime.strptime(str(START_DATE), "%Y%m%d")
+    ).days,
+    1.0,
+)
 POST_DATA = True
 LAST_WEEK_RATIO = 0.0
 LAST_TWOWEEKS_RATIO = 0.0
@@ -1427,7 +1438,7 @@ def calc_pitching_cards(ps: pd.DataFrame, season_pct: float) -> pd.DataFrame:
                 "closer_rating": [
                     cpi.closer_rating(int(row["GF"]), int(row["SV"]), int(row["G"]))
                 ],
-                "batting": [f'#1W{row["pitch_hand"].upper()}-C'],
+                "batting": [f"#1W{row['pitch_hand'].upper()}-C"],
             }
         )
         return y.loc[0]
@@ -1596,7 +1607,7 @@ def calc_positions(bs: pd.DataFrame) -> pd.DataFrame:
         ]:
             if row["key_bbref"] in pos_df.index:
                 logger.info(
-                    f'Running {position} stats for {row["use_name"]} {row["last_name"]}'
+                    f"Running {position} stats for {row['use_name']} {row['last_name']}"
                 )
                 try:
                     if "bis_runs_total" in pos_df.columns:
@@ -1863,8 +1874,8 @@ async def get_or_post_players(
 
     def new_player_payload(row, ratings_df: pd.DataFrame):
         return {
-            "p_name": f'{row["use_name"]} {row["last_name"]}',
+            "p_name": f"{row['use_name']} {row['last_name']}",
-            "cost": f'{ratings_df.loc[row['key_bbref']]["cost"]}',
+            "cost": f"{ratings_df.loc[row['key_bbref']]['cost']}",
             "image": "change-me",
             "mlbclub": CLUB_LIST[row["Tm"]],
             "franchise": FRANCHISE_LIST[row["Tm"]],
@@ -1914,11 +1925,11 @@ async def get_or_post_players(
                 # Update positions for existing players too
                 all_pos = get_player_record_pos(def_rat_df, row)
                 patch_params = [
-                    ("cost", f'{bat_rat_df.loc[row['key_bbref']]["cost"]}'),
+                    ("cost", f"{bat_rat_df.loc[row['key_bbref']]['cost']}"),
                     ("rarity_id", int(bat_rat_df.loc[row["key_bbref"]]["rarity_id"])),
                     (
                         "image",
-                        f'{CARD_BASE_URL}{player_id}/battingcard{urllib.parse.quote("?d=")}{RELEASE_DIRECTORY}',
+                        f"{CARD_BASE_URL}{player_id}/battingcard{urllib.parse.quote('?d=')}{RELEASE_DIRECTORY}",
                     ),
                 ]
                 # Add position updates - set all 8 slots to clear any old positions
@@ -1962,7 +1973,7 @@ async def get_or_post_players(
                     params=[
                         (
                             "image",
-                            f'{CARD_BASE_URL}{player_id}/battingcard{urllib.parse.quote("?d=")}{RELEASE_DIRECTORY}',
+                            f"{CARD_BASE_URL}{player_id}/battingcard{urllib.parse.quote('?d=')}{RELEASE_DIRECTORY}",
                         )
                     ],
                 )
@@ -2001,11 +2012,11 @@ async def get_or_post_players(
 
                 # Determine pitcher positions based on ratings
                 patch_params = [
-                    ("cost", f'{pit_rat_df.loc[row['key_bbref']]["cost"]}'),
+                    ("cost", f"{pit_rat_df.loc[row['key_bbref']]['cost']}"),
                     ("rarity_id", int(pit_rat_df.loc[row["key_bbref"]]["rarity_id"])),
                     (
                         "image",
-                        f'{CARD_BASE_URL}{player_id}/pitchingcard{urllib.parse.quote("?d=")}{RELEASE_DIRECTORY}',
+                        f"{CARD_BASE_URL}{player_id}/pitchingcard{urllib.parse.quote('?d=')}{RELEASE_DIRECTORY}",
                     ),
                 ]
 
@@ -2079,7 +2090,7 @@ async def get_or_post_players(
                     params=[
                         (
                             "image",
-                            f'{CARD_BASE_URL}{player_id}/pitchingcard{urllib.parse.quote("?d=")}{RELEASE_DIRECTORY}',
+                            f"{CARD_BASE_URL}{player_id}/pitchingcard{urllib.parse.quote('?d=')}{RELEASE_DIRECTORY}",
                         )
                     ],
                 )
@@ -2103,10 +2114,10 @@ async def get_or_post_players(
         raise KeyError("Could not get players - not enough stat DFs were supplied")
 
     pd.DataFrame(player_deltas[1:], columns=player_deltas[0]).to_csv(
-        f'{"batter" if bstat_df is not None else "pitcher"}-deltas.csv'
+        f"{'batter' if bstat_df is not None else 'pitcher'}-deltas.csv"
     )
     pd.DataFrame(new_players[1:], columns=new_players[0]).to_csv(
-        f'new-{"batter" if bstat_df is not None else "pitcher"}s.csv'
+        f"new-{'batter' if bstat_df is not None else 'pitcher'}s.csv"
     )
 
     players_df = pd.DataFrame(all_players).set_index("bbref_id")
@@ -2278,7 +2289,7 @@ async def post_positions(pos_df: pd.DataFrame, delete_existing: bool = False):
                         deleted_count += 1
                     except Exception as e:
                         logger.warning(
-                            f'Failed to delete cardposition {pos["id"]}: {e}'
+                            f"Failed to delete cardposition {pos['id']}: {e}"
                         )
             logger.info(f"Deleted {deleted_count} positions for players in current run")