✨ [alan-turing-institute#162]: implemented tracking transfers in and …

…out into a new table

airsenal/framework/schema.py

@@ -400,6 +400,24 @@ class SessionBudget(Base):
     id = Column(Integer, primary_key=True, autoincrement=True)
     session_id = Column(String(100), nullable=False)
     budget = Column(Integer, nullable=False)
+
+
+class TransferPriceTracker(Base):
+    __tablename__ = "transfer_price_tracker"
+    id = Column(Integer, primary_key=True, autoincrement=True)
+    player_id = Column(Integer, ForeignKey("player.player_id"))
+    gameweek = Column(Integer, nullable=False)
+    season = Column(String(4), nullable=False)
+    timestamp = Column(String(100), nullable=False)
+    price = Column(Integer, nullable=False)
+    transfers_in = Column(Integer, nullable=False)
+    transfers_out = Column(Integer, nullable=False)
+
+    def __str__(self):
+        return (
+            f"{self.player_id} ({self.season} GW{self.gameweek}): "
+            f"£{self.price / 10}, {self.transfers_in}, {self.transfers_out}"
+        )
 
 
 def get_connection_string():

airsenal/scripts/price_change_data.py

@@ -0,0 +1,40 @@
+"""
+Classes for fetching and storing the transfers in/out for each player
+The aim of this is to attempt to predict the price changes of players
+and accordingly make transfers to maximise profit
+"""
+from sqlalchemy.orm.session import Session
+
+from airsenal.framework.data_fetcher import FPLDataFetcher
+from airsenal.framework.schema import session, TransferPriceTracker
+from airsenal.framework.utils import NEXT_GAMEWEEK, CURRENT_SEASON
+
+import datetime as dt
+import pandas as pd
+
+
+def fill_global_transfers_from_api(season: str, dbsession=Session):
+    """
+    Get the global transfers in/out at the current time.
+    """
+    fetcher = FPLDataFetcher()
+    summary: dict = fetcher.get_current_summary_data()
+    df: pd.DataFrame = (
+        pd.DataFrame(summary["elements"])
+        .rename(columns={"id": "player_id", "now_cost": "price"})[
+            ["player_id", "price", "transfers_in", "transfers_out"]
+        ]
+        .assign(
+            timestamp=dt.datetime.now().strftime("%Y-%m-%dT%H:%M:%SZ"),
+            gameweek=NEXT_GAMEWEEK,
+            season=season,
+        )
+    )
+    # add to database
+    for _, row in df.iterrows():
+        print(f"Adding transfer data for player {row['player_id']}")
+        dbsession.add(TransferPriceTracker(**row.to_dict()))
+    dbsession.commit()
+
+if __name__ == "__main__":
+    fill_global_transfers_from_api(CURRENT_SEASON, dbsession=session)