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Multiple Outputs

Return multiple outputs at once - combine text, images, plots, tables, and files in a single response.

Basic Usage

Return a tuple or list with mixed types: 

from func_to_web import run
from func_to_web.types import FileResponse, ImageFile
from PIL import Image, ImageFilter
import matplotlib.pyplot as plt
import numpy as np

def analyze_image(image: ImageFile, blur_radius: int = 5):
    """Process image and return multiple outputs"""

    # Process image
    img = Image.open(image)
    blurred = img.filter(ImageFilter.GaussianBlur(blur_radius))

    # Create plot
    fig, ax = plt.subplots(figsize=(8, 4))
    x = np.linspace(0, 10, 100)
    y = np.sin(x)
    ax.plot(x, y)
    ax.set_title('Sample Plot')
    ax.grid(True)

    # Generate data table
    analysis_data = [
        {"metric": "Width", "value": img.size[0]},
        {"metric": "Height", "value": img.size[1]},
        {"metric": "Blur Radius", "value": blur_radius}
    ]

    # Create downloadable file
    report = FileResponse(
        data=f"Processed with blur: {blur_radius}".encode('utf-8'),
        filename="report.txt"
    )

    # Return everything at once
    return (
        "✓ Analysis complete!",  # Text
        blurred,                  # PIL Image
        fig,                      # Matplotlib plot
        analysis_data,            # Table (list[dict])
        report                    # File download
    )

run(analyze_image)

Each output is displayed in its own container, one after another.

Multiple Outputs

Combining Tables and Files

Tables can be included in multiple outputs alongside other types: 

from func_to_web import run
from func_to_web.types import FileResponse

def export_users_report():
    """Generate users table AND downloadable CSV"""

    users = [
        {"name": "Alice", "age": 25, "city": "NYC"},
        {"name": "Bob", "age": 30, "city": "LA"},
        {"name": "Charlie", "age": 35, "city": "SF"}
    ]

    # Generate CSV
    csv_lines = ["name,age,city"]
    for user in users:
        csv_lines.append(f"{user['name']},{user['age']},{user['city']}")
    csv_content = "\n".join(csv_lines)

    csv_file = FileResponse(
        data=csv_content.encode('utf-8'),
        filename="users.csv"
    )

    return (
        users,                    # Table display
        csv_file                  # Download button
    )

run(export_users_report)

Perfect for reports where you want to view AND download data.

Combined Types

Supported Output Types

You can combine any of these in a tuple or list:

  • Text: Plain strings are displayed as formatted text
  • PIL Images: Automatically rendered inline
  • Matplotlib Figures: Converted to images and displayed
  • Tables: list[dict] or list[tuple] rendered as HTML tables
  • File Downloads: Show download buttons with filenames
  • Multiple Files: Lists of FileResponse objects

How It Works

  • Return a tuple or list from your function
  • Each item is processed according to its type
  • All outputs are displayed sequentially in the UI
  • Each output gets its own styled container
  • Works with any combination of types

Limitations

  • No nesting: Tuples/lists cannot contain other tuples/lists (except valid tables)
  • Valid: return (table_data, file) where table_data is list[dict]
  • Invalid: return (("text", img), file) - nested tuples not allowed
  • Solution: Flatten to return ("text", img, file)

Key Points

  • Flexible: Mix text, images, plots, tables, and files freely
  • Simple syntax: Just return a tuple or list
  • Clean UI: Each output in its own styled box
  • No configuration: Works automatically with existing types
  • Tables included: list[dict] or list[tuple] are automatically detected

What's Next?

You've completed all Output Types! Explore additional features.

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