diff --git a/app/data/processing/predictive_models/v1.py b/app/data/processing/predictive_models/v1.py
index 6ee2c01..efc540e 100644
--- a/app/data/processing/predictive_models/v1.py
+++ b/app/data/processing/predictive_models/v1.py
@@ -56,16 +56,16 @@ def process_data(df_hobolink: pd.DataFrame, df_usgs: pd.DataFrame) -> pd.DataFra
         df_hobolink.groupby("time")
         .agg(
             {
-                "pressure": np.mean,
-                "par": np.mean,
-                "rain": np.sum,
-                "rh": np.mean,
-                "dew_point": np.mean,
-                "wind_speed": np.mean,
-                "gust_speed": np.mean,
-                "wind_dir": np.mean,
+                "pressure": "mean",
+                "par": "mean",
+                "rain": "sum",
+                "rh": "mean",
+                "dew_point": "mean",
+                "wind_speed": "mean",
+                "gust_speed": "mean",
+                "wind_dir": "mean",
                 # 'water_temp': np.mean,
-                "air_temp": np.mean,
+                "air_temp": "mean",
             }
         )
         .reset_index()
diff --git a/app/data/processing/predictive_models/v2.py b/app/data/processing/predictive_models/v2.py
index 5054aeb..ab87133 100644
--- a/app/data/processing/predictive_models/v2.py
+++ b/app/data/processing/predictive_models/v2.py
@@ -62,14 +62,14 @@ def process_data(df_hobolink: pd.DataFrame, df_usgs: pd.DataFrame) -> pd.DataFra
         df_usgs.groupby("time")
         .agg(
             {
-                "log_stream_flow": np.mean,
+                "log_stream_flow": "mean",
             }
         )
         .reset_index()
     )
     df_hobolink = (
         df_hobolink.groupby("time")
-        .agg({"rain": np.sum, "log_air_temp": np.mean, "days_since_sig_rain": np.min})
+        .agg({"rain": "sum", "log_air_temp": "mean", "days_since_sig_rain": "min"})
         .reset_index()
     )
 
diff --git a/app/data/processing/predictive_models/v3.py b/app/data/processing/predictive_models/v3.py
index 21f1cbc..6facdc7 100644
--- a/app/data/processing/predictive_models/v3.py
+++ b/app/data/processing/predictive_models/v3.py
@@ -43,16 +43,16 @@ def process_data(df_hobolink: pd.DataFrame, df_usgs: pd.DataFrame) -> pd.DataFra
         df_hobolink.groupby("time")
         .agg(
             {
-                "pressure": np.mean,
-                "par": np.mean,
-                "rain": np.sum,
-                "rh": np.mean,
-                "dew_point": np.mean,
-                "wind_speed": np.mean,
-                "gust_speed": np.mean,
-                "wind_dir": np.mean,
+                "pressure": "mean",
+                "par": "mean",
+                "rain": "sum",
+                "rh": "mean",
+                "dew_point": "mean",
+                "wind_speed": "mean",
+                "gust_speed": "mean",
+                "wind_dir": "mean",
                 # 'water_temp': np.mean,
-                "air_temp": np.mean,
+                "air_temp": "mean",
             }
         )
         .reset_index()
diff --git a/app/main.py b/app/main.py
index 36f1269..73e4677 100644
--- a/app/main.py
+++ b/app/main.py
@@ -285,11 +285,11 @@ def update_db_command(async_: bool = False, tweet_status: bool = False):
         from app.data.celery import update_db_task
 
         if async_:
-            res = update_db_task.delay(tweet_status=tweet_status)
+            res = update_db_task.s(tweet_status=tweet_status).delay()
             click.echo(f"Started update database task ({res.id!r}).")
         else:
             click.echo("Updating the database...")
-            update_db_task.run(tweet_status=tweet_status)
+            update_db_task.s(tweet_status=tweet_status).run()
             click.echo("Updated the database successfully.")
 
     @app.cli.command("gen-mock-data")
diff --git a/pytest.ini b/pytest.ini
index 2df2815..f39fde7 100644
--- a/pytest.ini
+++ b/pytest.ini
@@ -1,5 +1,4 @@
 [pytest]
-mocked-sessions = app.data.database.db.session
 addopts = --cov=app
 testpaths =
     tests