🎨 Palette: Enhance CLI output with summary tables and visual polish

.Jules/palette.md

@@ -9,3 +9,7 @@
 ## 2026-03-30 - [Demo Scale vs. Terminal Readability]
 **Learning:** For demo scripts, larger data sets can degrade the UX by flooding the terminal with logs, making it harder for users to see the structure of the output.
 **Action:** Limit the default number of items in demo loops (e.g., 5 items) to maintain a high signal-to-noise ratio while still demonstrating the functionality.
+
+## 2026-03-31 - [Visual Polish for CLI Summaries]
+**Learning:** In CLI-based workflow scaffolds, replacing raw success messages with structured `rich.table.Table` summaries significantly improves the professional feel and readability of the output. Additionally, zero-padding generated IDs (e.g., 'customer-01') ensures natural sorting and vertical alignment, which reduces cognitive load when scanning lists. Finally, adding minimal artificial delays (e.g., `time.sleep(0.1)`) in demo scripts makes the "work" visible by giving terminal spinners and status indicators enough time to register with the user.
+**Action:** Use structured tables for final execution summaries, ensure all generated IDs are zero-padded for alignment, and include brief pacing pauses in demo tasks to make the execution flow more perceptible.

01_getting_started.py

@@ -1,41 +1,64 @@
 from prefect import flow, task
 import random
+import time
 from rich.console import Console
 from rich.panel import Panel
 from rich.rule import Rule
+from rich.table import Table
 
 console = Console()
 
 
 @task
 def get_customer_ids() -> list[str]:
-    # Fetch customer IDs from a database or API
-    return [f"customer{n}" for n in random.choices(range(100), k=5)]
+    """Fetch customer IDs from a database or API."""
+    # Use sorted and zero-padded IDs for better terminal alignment
+    ids = [f"customer-{n:02d}" for n in random.choices(range(100), k=5)]
+    return sorted(ids)
 
 
 @task
 def process_customer(customer_id: str) -> str:
-    # Process a single customer
+    """Process a single customer."""
+    # Add a brief pause to make the processing state visible in the UI
+    time.sleep(0.1)
     return f"Processed {customer_id}"
 
 
 @flow(log_prints=True)
 def main():
     """
     ### 🚀 Getting Started with Prefect
+
     This flow demonstrates how to map a task over a list of inputs.
     It fetches a list of customer IDs and processes each one individually.
     """
     with console.status("[bold green]Fetching customer data..."):
         customer_ids = get_customer_ids()
 
-    # Map the process_customer task across all customer IDs
     console.print(f"[bold blue]📦 Fetched {len(customer_ids)} customer IDs[/bold blue]")
 
     with console.status("[bold green]Processing customers..."):
-        results = process_customer.map(customer_ids)
+        futures = process_customer.map(customer_ids)
+        # Explicitly wait for results to avoid AttributeErrors on futures
+        results = [f.result() for f in futures]
+
+    # Display results in a clean table for better readability
+    table = Table(
+        title="Processing Summary", show_header=True, header_style="bold blue"
+    )
+    table.add_column("Customer ID", style="cyan")
+    table.add_column("Status", style="green")
 
+    for res in results:
+        # Extract the customer ID from the result string (e.g., "Processed customer-01")
+        customer_id = res.split()[-1]
+        table.add_row(customer_id, "✅ Success")
+
+    console.print()
+    console.print(table)
     console.print()
+
     console.print(
         Panel.fit(
             f"[bold green]✅ Successfully processed {len(results)} customers![/bold green]",

02_logging.py

@@ -1,24 +1,30 @@
 from prefect import flow, task
 from prefect.logging import get_run_logger
 import random
+import time
 from rich.console import Console
 from rich.panel import Panel
 from rich.rule import Rule
+from rich.table import Table
 
 console = Console()
 
 
 @task
 def get_customer_ids() -> list[str]:
-    # Fetch customer IDs from a database or API
-    return [f"customer{n}" for n in random.choices(range(100), k=5)]
+    """Fetch customer IDs from a database or API."""
+    # Use sorted and zero-padded IDs for better terminal alignment
+    ids = [f"customer-{n:02d}" for n in random.choices(range(100), k=5)]
+    return sorted(ids)
 
 
 @task
 def process_customer(customer_id: str) -> str:
-    # Process a single customer
+    """Process a single customer."""
     logger = get_run_logger()
     for _ in range(3):
+        # Add a brief pause to make the logging visible and realistic
+        time.sleep(0.05)
         logger.info(f"Processing customer {customer_id}")
     return f"Processed {customer_id}"
 
@@ -39,13 +45,29 @@ def main():
     with console.status("[bold green]Fetching customer data..."):
         customer_ids = get_customer_ids()
 
-    # Map the process_customer task across all customer IDs
     console.print(f"[bold blue]📦 Fetched {len(customer_ids)} customer IDs[/bold blue]")
 
     with console.status("[bold green]Processing customers with logging..."):
-        results = process_customer.map(customer_ids)
+        futures = process_customer.map(customer_ids)
+        # Explicitly wait for results to avoid AttributeErrors on futures
+        results = [f.result() for f in futures]
+
+    # Display results in a clean table for better readability
+    table = Table(
+        title="Processing Summary", show_header=True, header_style="bold blue"
+    )
+    table.add_column("Customer ID", style="cyan")
+    table.add_column("Status", style="green")
+
+    for res in results:
+        # Extract the customer ID from the result string (e.g., "Processed customer-01")
+        customer_id = res.split()[-1]
+        table.add_row(customer_id, "✅ Success")
 
     console.print()
+    console.print(table)
+    console.print()
+
     console.print(
         Panel.fit(
             f"[bold green]✅ Successfully processed {len(results)} customers with detailed logging![/bold green]",