Additional file monitoring instruction

file-monitoring/README.md

@@ -1,6 +1,8 @@
 # Problem description
 
-Data apps often sit at the end of a larger data processing pipeline, and so it is helpful to have your app update whenever the underlying data files change.
+Data apps often sit at the end of a larger data processing pipeline, and so it is helpful to have your app update whenever the underlying data files change. An example data generating script can be found in `populate-logs.py` which irregularly appends a row to a data frame.
 
 # Requirements
-- App should read in and render a csv file, whenever that csv file changes the application should update without any user action.
+- App should read in and render a csv file as a data frame, whenever that csv file changes the data frame output should rerender.
+- The application shouldn't rerender if the csv file is unchanged.
+- Othe components should be usable as the data frame rerenders.

file-monitoring/logs.csv

@@ -0,0 +1,4 @@
+date,status
+2023-12-05 18:48:35.076744,status5
+2023-12-05 18:48:36.081387,status14
+2023-12-05 18:48:37.088922,status19

file-monitoring/populate-logs.py

@@ -0,0 +1,17 @@
+import pandas as pd
+from datetime import datetime
+from pathlib import Path
+
+import random
+import time
+
+log_path = Path(__file__).parent / "logs.csv"
+
+while True:
+    status = "status" + str(random.randint(0, 20))
+    # Create a new DataFrame with the current time and the random status
+    df = pd.DataFrame({"date": [datetime.now()], "status": [status]})
+
+    df.to_csv(log_path, mode="a", header=False, index=False)
+    # Wait for a second before the next append operation
+    time.sleep(random.randint(1, 5))

file-monitoring/shiny/app.py

@@ -1,6 +1,7 @@
 from shiny import Inputs, Outputs, Session, App, render, ui, reactive
 from pathlib import Path
 import pandas as pd
+from datetime import datetime
 
 
 @reactive.file_reader(Path(__file__).parent / "logs.csv")
@@ -9,7 +10,11 @@ def logs():
 
 
 app_ui = ui.page_fillable(
-    ui.card(ui.output_data_frame("df")),
+    ui.layout_column_wrap(
+        ui.card(ui.output_data_frame("df")),
+        ui.card(ui.input_text("txt_in", "Enter text"), ui.output_text("text_out")),
+        width=1 / 2,
+    )
 )
 
 
@@ -19,5 +24,9 @@ def df():
         out = logs().sort_values("date", ascending=False)
         return render.DataTable(out, width="500px", height="95%")
 
+    @render.text
+    def text_out():
+        return f"You wrote {input.txt_in()} at {datetime.now().time()}"
+
 
 app = App(app_ui, server)

file-monitoring/shiny/populate-logs.py

@@ -14,4 +14,4 @@
 
     df.to_csv(log_path, mode="a", header=False, index=False)
     # Wait for a second before the next append operation
-    time.sleep(1)
+    time.sleep(random.randint(1, 5))