Try to migrate the existing database, by adding missing columns

assume/common/forecasts.py

@@ -94,12 +94,15 @@ def set_forecast(self, data: pd.DataFrame | pd.Series | None, prefix=""):
             return
         elif isinstance(data, pd.DataFrame):
             if prefix:
+                # set prefix for columns to set
                 columns = [prefix + column for column in data.columns]
                 data.columns = columns
             if len(data.index) == 1:
+                # if we have a single value which should be set for the whole series
                 for column in data.columns:
                     self.forecasts[column] = data[column].item()
             else:
+                # if some columns already exist, just add the new columns
                 new_columns = set(data.columns) - set(self.forecasts.columns)
                 self.forecasts = pd.concat(
                     [self.forecasts, data[list(new_columns)]], axis=1

assume/common/outputs.py

@@ -7,6 +7,7 @@
 import pandas as pd
 from dateutil import rrule as rr
 from mango import Role
+from pandas.api.types import is_numeric_dtype
 from sqlalchemy import inspect, text
 from sqlalchemy.exc import ProgrammingError
 
@@ -84,10 +85,10 @@ def delete_db_scenario(self, simulation_id):
 
         # Loop throuph all database tables
         # Get list of table names in database
-        table_names = inspect(self.db.bind).get_table_names()
+        table_names = inspect(self.db).get_table_names()
         # Iterate through each table
         for table_name in table_names:
-            with self.db() as db:
+            with self.db.begin() as db:
                 # Read table into Pandas DataFrame
                 query = text(
                     f"delete from {table_name} where simulation = '{simulation_id}'"
@@ -101,7 +102,7 @@ def del_similar_runs(self):
         query = text("select distinct simulation from market_meta")
 
         try:
-            with self.db() as db:
+            with self.db.begin() as db:
                 simulations = db.execute(query).fetchall()
         except Exception:
             simulations = []
@@ -212,9 +213,39 @@ async def store_dfs(self):
                 df.to_csv(data_path, mode="a", header=not data_path.exists())
 
             if self.db is not None:
-                df.to_sql(table, self.db.bind, if_exists="append")
+                try:
+                    with self.db.begin() as db:
+                        df.to_sql(table, db, if_exists="append")
+                except ProgrammingError:
+                    self.check_columns(table, df)
+                    # now try again
+                    with self.db.begin() as db:
+                        df.to_sql(table, db, if_exists="append")
+
             self.write_dfs[table] = []
 
+    def check_columns(self, table: str, df: pd.DataFrame):
+        """
+        If a simulation before has been started which does not include an additional field
+        we try to add the field.
+        For now, this only works for float and text.
+        An alternative which finds the correct types would be to use
+        """
+        with self.db.begin() as db:
+            # Read table into Pandas DataFrame
+            query = f"select * from {table} where 1=0"
+            db_columns = pd.read_sql(query, db).columns
+        for column in df.columns:
+            if column not in db_columns:
+                try:
+                    # TODO this only works for float and text
+                    column_type = "float" if is_numeric_dtype(df[column]) else "text"
+                    query = f"ALTER TABLE {table} ADD COLUMN {column} {column_type}"
+                    with self.db.begin() as db:
+                        db.execute(text(query))
+                except Exception:
+                    logger.exception("Error converting column")
+
     def check_for_tensors(self, data):
         """
         Checks if the data contains tensors and converts them to floats.
@@ -321,7 +352,7 @@ async def on_stop(self):
 
         try:
             for query in queries:
-                df = pd.read_sql(query, self.db.bind)
+                df = pd.read_sql(query, self.db)
                 dfs.append(df)
             df = pd.concat(dfs)
             df.reset_index()
@@ -335,7 +366,8 @@ async def on_stop(self):
                     index=None,
                 )
             if self.db is not None and not df.empty:
-                df.to_sql("kpis", self.db.bind, if_exists="append", index=None)
+                with self.db.begin() as db:
+                    df.to_sql("kpis", self.db, if_exists="append", index=None)
         except ProgrammingError as e:
             self.db.rollback()
             logger.error(f"No scenario run Yet {e}")
@@ -357,7 +389,7 @@ def get_sum_reward(self):
         )
 
         try:
-            with self.db() as db:
+            with self.db.begin() as db:
                 avg_reward = db.execute(query).fetchall()[0]
         except Exception:
             avg_reward = 0

assume/world.py

@@ -54,13 +54,13 @@ def __init__(
         self.export_csv_path = export_csv_path
         # intialize db connection at beginning of simulation
         if database_uri:
-            self.db = scoped_session(sessionmaker(create_engine(database_uri)))
+            self.db = create_engine(database_uri)
             connected = False
             while not connected:
                 try:
-                    self.db.connection()
-                    connected = True
-                    self.logger.info("connected to db")
+                    with self.db.connect():
+                        connected = True
+                        self.logger.info("connected to db")
                 except OperationalError as e:
                     self.logger.error(
                         f"could not connect to {database_uri}, trying again"

tests/test_outputs.py

@@ -12,7 +12,7 @@
 
 
 def test_output_market_orders():
-    engine = scoped_session(sessionmaker(create_engine(DB_URI)))
+    engine = create_engine(DB_URI)
     start = datetime(2020, 1, 1)
     end = datetime(2020, 1, 2)
     output_writer = WriteOutput("test_sim", start, end, engine)
@@ -73,7 +73,7 @@ def test_output_market_orders():
 
 
 def test_output_market_results():
-    engine = scoped_session(sessionmaker(create_engine(DB_URI)))
+    engine = create_engine(DB_URI)
     start = datetime(2020, 1, 1)
     end = datetime(2020, 1, 2)
     output_writer = WriteOutput("test_sim", start, end, engine)
@@ -106,7 +106,7 @@ def test_output_market_results():
 
 
 def test_output_market_dispatch():
-    engine = scoped_session(sessionmaker(create_engine(DB_URI)))
+    engine = create_engine(DB_URI)
     start = datetime(2020, 1, 1)
     end = datetime(2020, 1, 2)
     output_writer = WriteOutput("test_sim", start, end, engine)
@@ -118,7 +118,7 @@ def test_output_market_dispatch():
 
 
 def test_output_unit_dispatch():
-    engine = scoped_session(sessionmaker(create_engine(DB_URI)))
+    engine = create_engine(DB_URI)
     start = datetime(2020, 1, 1)
     end = datetime(2020, 1, 2)
     output_writer = WriteOutput("test_sim", start, end, engine)