Update load files. Remove handle_on. Update requirements

emp-churn-step-by-step/requirements.txt

@@ -1 +1,4 @@
-h2o-wave==0.24.0
+h2o-wave==1.5.1
+altair==5.4.1
+pandas==2.2.2
+numpy==2.1.1

emp-churn-step-by-step/src/app1.py

@@ -1,7 +1,7 @@
 # Step 1
 # Setting Up Layout:Header, main page and footer
 # ---
-from h2o_wave import main, app, Q, ui, on, handle_on, data
+from h2o_wave import main, app, Q, ui, on, run_on, data
 
 
 @app('/')
@@ -12,7 +12,7 @@ async def serve(q: Q):
         q.client.initialized = True
 
     # Other browser interactions
-    await handle_on(q)
+    await run_on(q)
     await q.page.save()
 
 

emp-churn-step-by-step/src/app10.py

@@ -2,15 +2,15 @@
 # Refresh only relevant components. Stop re-creating cards - just refresh attributes
 # Set H2O_WAVE_NO_LOG=1 to avoid printing server (waved) messages
 # ---
-from h2o_wave import main, app, Q, ui, on, handle_on, data
+from h2o_wave import main, app, Q, ui, on, data
 
 import altair
 import numpy as np
 import pandas as pd
 from typing import List
 
 import logging
-from os import environ
+import os
 import traceback
 
 log = logging.getLogger("app")
@@ -28,7 +28,7 @@ def setup_logger():
     )
     ch.setFormatter(formatter)
     log.addHandler(ch)
-    log.setLevel(environ.get("LOG_LEVEL", "INFO").upper())
+    log.setLevel(os.environ.get("LOG_LEVEL", "INFO").upper())
 
 
 def on_startup():
@@ -95,11 +95,13 @@ async def serve(q: Q):
 
 async def init_app(q: Q) -> None:
     # Read and load data into memory
-    log.info("==Start init_app Function ==")
-    q.app.predictions = pd.read_csv("./src/static/predictions.csv")
+    file_path = os.path.abspath(__file__)
+    dir_path = os.path.dirname(file_path)
+    predictions_file = os.path.join(dir_path, 'static', 'predictions.csv')
+    shapley_file = os.path.join(dir_path, 'static', 'shapley_values.csv')
+    q.app.predictions = pd.read_csv(predictions_file)
     q.app.predictions = q.app.predictions.rename(columns={'Attrition.Yes': "Prediction"})
-    q.app.shapley = pd.read_csv("./src/static/shapley_values.csv")
-    log.info("==Complete init_app Function ==")
+    q.app.shapley = pd.read_csv(shapley_file)
 
 
 async def init(q: Q) -> None:

emp-churn-step-by-step/src/app11.py

@@ -1,7 +1,7 @@
 # Step 11
 # Add logic to read data from Delta Lake tables
 # ---
-from h2o_wave import main, app, Q, ui, on, handle_on, data
+from h2o_wave import main, app, Q, ui, on, data
 
 import altair
 import numpy as np
@@ -10,7 +10,7 @@
 import os
 
 import logging
-from os import environ
+import os
 import traceback
 
 log = logging.getLogger("app")
@@ -28,7 +28,7 @@ def setup_logger():
     )
     ch.setFormatter(formatter)
     log.addHandler(ch)
-    log.setLevel(environ.get("LOG_LEVEL", "INFO").upper())
+    log.setLevel(os.environ.get("LOG_LEVEL", "INFO").upper())
 
 
 def on_startup():
@@ -94,10 +94,13 @@ async def serve(q: Q):
 
 async def init_app(q: Q) -> None:
     # Read and load data into memory
-    log.info("==Start init_app Function ==")
-    q.app.predictions, q.app.shapley = load_data_from_db()
+    file_path = os.path.abspath(__file__)
+    dir_path = os.path.dirname(file_path)
+    predictions_file = os.path.join(dir_path, 'static', 'predictions.csv')
+    shapley_file = os.path.join(dir_path, 'static', 'shapley_values.csv')
+    q.app.predictions = pd.read_csv(predictions_file)
     q.app.predictions = q.app.predictions.rename(columns={'Attrition.Yes': "Prediction"})
-    log.info("==Complete init_app Function ==")
+    q.app.shapley = pd.read_csv(shapley_file)
 
 
 async def init(q: Q) -> None:

emp-churn-step-by-step/src/app12.py

@@ -2,15 +2,15 @@
 # Employee table pagination - handle large number of records in table
 # Set H2O_WAVE_NO_LOG=1 to avoid printing server (waved) messages
 # ---
-from h2o_wave import main, app, Q, ui, on, handle_on, data
+from h2o_wave import main, app, Q, ui, on, data
 
 import altair
 import numpy as np
 import pandas as pd
 from typing import List
 
 import logging
-from os import environ
+import os
 import traceback
 
 log = logging.getLogger("app")
@@ -29,7 +29,7 @@ def setup_logger():
     )
     ch.setFormatter(formatter)
     log.addHandler(ch)
-    log.setLevel(environ.get("LOG_LEVEL", "INFO").upper())
+    log.setLevel(os.environ.get("LOG_LEVEL", "INFO").upper())
 
 
 def on_startup():
@@ -102,11 +102,13 @@ async def serve(q: Q):
 
 async def init_app(q: Q) -> None:
     # Read and load data into memory
-    log.info("==Start init_app Function ==")
-    q.app.predictions = pd.read_csv("./src/static/predictions.csv")
+    file_path = os.path.abspath(__file__)
+    dir_path = os.path.dirname(file_path)
+    predictions_file = os.path.join(dir_path, 'static', 'predictions.csv')
+    shapley_file = os.path.join(dir_path, 'static', 'shapley_values.csv')
+    q.app.predictions = pd.read_csv(predictions_file)
     q.app.predictions = q.app.predictions.rename(columns={'Attrition.Yes': "Prediction"})
-    q.app.shapley = pd.read_csv("./src/static/shapley_values.csv")
-    log.info("==Complete init_app Function ==")
+    q.app.shapley = pd.read_csv(shapley_file)
 
 
 async def init(q: Q) -> None:

emp-churn-step-by-step/src/app13.py

@@ -2,7 +2,7 @@
 # Add tabs and tabs switching
 # Set H2O_WAVE_NO_LOG=1 to avoid printing server (waved) messages
 # ---
-from h2o_wave import main, app, Q, ui, on, handle_on, data
+from h2o_wave import main, app, Q, ui, on, data
 from h2o_wave.core import expando_to_dict
 from typing import Optional, List
 
@@ -11,7 +11,7 @@
 import pandas as pd
 
 import logging
-from os import environ
+import os
 import traceback
 
 log = logging.getLogger("app")
@@ -31,7 +31,7 @@ def setup_logger():
     )
     ch.setFormatter(formatter)
     log.addHandler(ch)
-    log.setLevel(environ.get("LOG_LEVEL", "INFO").upper())
+    log.setLevel(os.environ.get("LOG_LEVEL", "INFO").upper())
 
 
 def on_startup():
@@ -129,11 +129,13 @@ async def serve(q: Q):
 
 async def init_app(q: Q) -> None:
     # Read and load data into memory
-    log.info("==Start init_app Function ==")
-    q.app.predictions = pd.read_csv("./src/static/predictions.csv")
+    file_path = os.path.abspath(__file__)
+    dir_path = os.path.dirname(file_path)
+    predictions_file = os.path.join(dir_path, 'static', 'predictions.csv')
+    shapley_file = os.path.join(dir_path, 'static', 'shapley_values.csv')
+    q.app.predictions = pd.read_csv(predictions_file)
     q.app.predictions = q.app.predictions.rename(columns={'Attrition.Yes': "Prediction"})
-    q.app.shapley = pd.read_csv("./src/static/shapley_values.csv")
-    log.info("==Complete init_app Function ==")
+    q.app.shapley = pd.read_csv(shapley_file)
 
 
 async def init(q: Q) -> None:

emp-churn-step-by-step/src/app2.py

@@ -1,7 +1,7 @@
 # Step 2
 # Changing Cards descriptions
 # ---
-from h2o_wave import main, app, Q, ui, on, handle_on, data
+from h2o_wave import main, app, Q, ui, on, run_on, data
 
 
 @app('/')
@@ -12,7 +12,7 @@ async def serve(q: Q):
         q.client.initialized = True
 
     # Other browser interactions
-    await handle_on(q)
+    await run_on(q)
     await q.page.save()
 
 

emp-churn-step-by-step/src/app3.py

@@ -1,9 +1,10 @@
 # Step 3
 # Read data and add plot
 # ---
-from h2o_wave import main, app, Q, ui, on, handle_on, data
+from h2o_wave import main, app, Q, ui, on, run_on, data
 
 import pandas as pd
+import os
 
 
 @app('/')
@@ -19,13 +20,16 @@ async def serve(q: Q):
         q.client.initialized = True
 
     # Other browser interactions
-    await handle_on(q)
+    await run_on(q)
     await q.page.save()
 
 
 async def init_app(q: Q) -> None:
-    # Read Shapley values
-    q.app.shapley = pd.read_csv("./src/static/shapley_values.csv")
+    # Read and load data into memory
+    file_path = os.path.abspath(__file__)
+    dir_path = os.path.dirname(file_path)
+    shapley_file = os.path.join(dir_path, 'static', 'shapley_values.csv')
+    q.app.shapley = pd.read_csv(shapley_file)
 
 
 async def init(q: Q) -> None:

emp-churn-step-by-step/src/app4.py

@@ -1,10 +1,11 @@
 # Step 4
 # Add Churn Prediction Chart
 # ---
-from h2o_wave import main, app, Q, ui, on, handle_on, data
+from h2o_wave import main, app, Q, ui, on, run_on, data
 
 import altair
 import pandas as pd
+import os
 
 
 @app('/')
@@ -20,15 +21,19 @@ async def serve(q: Q):
         q.client.initialized = True
 
     # Other browser interactions
-    await handle_on(q)
+    await run_on(q)
     await q.page.save()
 
 
 async def init_app(q: Q) -> None:
     # Read and load data into memory
-    q.app.predictions = pd.read_csv("./src/static/predictions.csv")
+    file_path = os.path.abspath(__file__)
+    dir_path = os.path.dirname(file_path)
+    predictions_file = os.path.join(dir_path, 'static', 'predictions.csv')
+    shapley_file = os.path.join(dir_path, 'static', 'shapley_values.csv')
+    q.app.predictions = pd.read_csv(predictions_file)
     q.app.predictions = q.app.predictions.rename(columns={'Attrition.Yes': "Prediction"})
-    q.app.shapley = pd.read_csv("./src/static/shapley_values.csv")
+    q.app.shapley = pd.read_csv(shapley_file)
 
 
 async def init(q: Q) -> None:

emp-churn-step-by-step/src/app5.py

@@ -1,10 +1,11 @@
 # Step 5
 # Add Threshold Slider and description card above
 # ---
-from h2o_wave import main, app, Q, ui, on, handle_on, data
+from h2o_wave import main, app, Q, ui, on, run_on, data
 
 import altair
 import pandas as pd
+import os
 
 
 @app('/')
@@ -20,15 +21,19 @@ async def serve(q: Q):
         q.client.initialized = True
 
     # Other browser interactions
-    await handle_on(q)
+    await run_on(q)
     await q.page.save()
 
 
 async def init_app(q: Q) -> None:
     # Read and load data into memory
-    q.app.predictions = pd.read_csv("./src/static/predictions.csv")
+    file_path = os.path.abspath(__file__)
+    dir_path = os.path.dirname(file_path)
+    predictions_file = os.path.join(dir_path, 'static', 'predictions.csv')
+    shapley_file = os.path.join(dir_path, 'static', 'shapley_values.csv')
+    q.app.predictions = pd.read_csv(predictions_file)
     q.app.predictions = q.app.predictions.rename(columns={'Attrition.Yes': "Prediction"})
-    q.app.shapley = pd.read_csv("./src/static/shapley_values.csv")
+    q.app.shapley = pd.read_csv(shapley_file)
 
 
 async def init(q: Q) -> None:

emp-churn-step-by-step/src/app6.py

@@ -1,10 +1,11 @@
 # Step 6
 # Add Stats Card below Threshold Slider
 # ---
-from h2o_wave import main, app, Q, ui, on, handle_on, data
+from h2o_wave import main, app, Q, ui, on, run_on, data
 
 import altair
 import pandas as pd
+import os
 
 
 @app('/')
@@ -20,15 +21,19 @@ async def serve(q: Q):
         q.client.initialized = True
 
     # Other browser interactions
-    await handle_on(q)
+    await run_on(q)
     await q.page.save()
 
 
 async def init_app(q: Q) -> None:
     # Read and load data into memory
-    q.app.predictions = pd.read_csv("./src/static/predictions.csv")
+    file_path = os.path.abspath(__file__)
+    dir_path = os.path.dirname(file_path)
+    predictions_file = os.path.join(dir_path, 'static', 'predictions.csv')
+    shapley_file = os.path.join(dir_path, 'static', 'shapley_values.csv')
+    q.app.predictions = pd.read_csv(predictions_file)
     q.app.predictions = q.app.predictions.rename(columns={'Attrition.Yes': "Prediction"})
-    q.app.shapley = pd.read_csv("./src/static/shapley_values.csv")
+    q.app.shapley = pd.read_csv(shapley_file)
 
 
 async def init(q: Q) -> None:

emp-churn-step-by-step/src/app7.py

@@ -1,11 +1,12 @@
 # Step 7
 # Add Employee details table below Stats Card
 # ---
-from h2o_wave import main, app, Q, ui, on, handle_on, data
+from h2o_wave import main, app, Q, ui, on, run_on, data
 
 import altair
 import numpy as np
 import pandas as pd
+import os
 
 
 @app('/')
@@ -21,15 +22,19 @@ async def serve(q: Q):
         q.client.initialized = True
 
     # Other browser interactions
-    await handle_on(q)
+    await run_on(q)
     await q.page.save()
 
 
 async def init_app(q: Q) -> None:
     # Read and load data into memory
-    q.app.predictions = pd.read_csv("./src/static/predictions.csv")
+    file_path = os.path.abspath(__file__)
+    dir_path = os.path.dirname(file_path)
+    predictions_file = os.path.join(dir_path, 'static', 'predictions.csv')
+    shapley_file = os.path.join(dir_path, 'static', 'shapley_values.csv')
+    q.app.predictions = pd.read_csv(predictions_file)
     q.app.predictions = q.app.predictions.rename(columns={'Attrition.Yes': "Prediction"})
-    q.app.shapley = pd.read_csv("./src/static/shapley_values.csv")
+    q.app.shapley = pd.read_csv(shapley_file)
 
 
 async def init(q: Q) -> None: