Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Impara Batch Processing with Lists | Creative Automation with Python
Python for Creators and Makers

bookBatch Processing with Lists

Batch processing is a powerful technique that lets you apply the same operation to many items at once. In creative work, this is especially useful. Imagine you want to brighten a whole folder of photos, resize a batch of shapes for an art piece, or change the color of every object in a scene. Instead of editing each item one by one, you can use batch processing to automate these repetitive tasks, saving time and ensuring consistency across your creative elements. Lists in Python make this possible by allowing you to store groups of related values—such as image brightness levels, shape sizes, or object colors—so you can process them together with just a few lines of code.

12345678910
def increase_brightness(brightness_values, increase_by): updated_values = [] for value in brightness_values: updated_values.append(value + increase_by) return updated_values # Example usage: original_brightness = [50, 120, 200, 80] brighter = increase_brightness(original_brightness, 30) print(brighter) # Output: [80, 150, 230, 110]
copy

The increase_brightness function above demonstrates how batch processing works in practice. You start with a list of numbers, each representing the brightness of an image or object. The function loops through every value in the list, increases it by a fixed amount, and collects the results in a new list. This is similar to using a batch edit tool in creative software, where you apply the same filter or adjustment to multiple files at once. Instead of handling each item separately, the loop lets you automate the process, making your workflow faster and more efficient.

123456789
# Adjust shape sizes for a generative art piece shape_sizes = [10, 20, 30, 40, 50] scaled_sizes = [] for size in shape_sizes: new_size = size * 1.5 # Scale each size by 1.5x scaled_sizes.append(new_size) print(scaled_sizes) # Output: [15.0, 30.0, 45.0, 60.0, 75.0]
copy

1. Why are lists useful for batch processing in Python?

2. What Python structure allows you to store multiple values for batch operations?

3. Fill in the blank: To apply a function to every item in a list, you typically use a ________.

question mark

Why are lists useful for batch processing in Python?

Select all correct answers

question mark

What Python structure allows you to store multiple values for batch operations?

Select the correct answer

question-icon

Fill in the blank: To apply a function to every item in a list, you typically use a ________.

Tutto è chiaro?

Come possiamo migliorarlo?

Grazie per i tuoi commenti!

Sezione 1. Capitolo 2

Chieda ad AI

expand

Chieda ad AI

ChatGPT

Chieda pure quello che desidera o provi una delle domande suggerite per iniziare la nostra conversazione

bookBatch Processing with Lists

Scorri per mostrare il menu

Batch processing is a powerful technique that lets you apply the same operation to many items at once. In creative work, this is especially useful. Imagine you want to brighten a whole folder of photos, resize a batch of shapes for an art piece, or change the color of every object in a scene. Instead of editing each item one by one, you can use batch processing to automate these repetitive tasks, saving time and ensuring consistency across your creative elements. Lists in Python make this possible by allowing you to store groups of related values—such as image brightness levels, shape sizes, or object colors—so you can process them together with just a few lines of code.

12345678910
def increase_brightness(brightness_values, increase_by): updated_values = [] for value in brightness_values: updated_values.append(value + increase_by) return updated_values # Example usage: original_brightness = [50, 120, 200, 80] brighter = increase_brightness(original_brightness, 30) print(brighter) # Output: [80, 150, 230, 110]
copy

The increase_brightness function above demonstrates how batch processing works in practice. You start with a list of numbers, each representing the brightness of an image or object. The function loops through every value in the list, increases it by a fixed amount, and collects the results in a new list. This is similar to using a batch edit tool in creative software, where you apply the same filter or adjustment to multiple files at once. Instead of handling each item separately, the loop lets you automate the process, making your workflow faster and more efficient.

123456789
# Adjust shape sizes for a generative art piece shape_sizes = [10, 20, 30, 40, 50] scaled_sizes = [] for size in shape_sizes: new_size = size * 1.5 # Scale each size by 1.5x scaled_sizes.append(new_size) print(scaled_sizes) # Output: [15.0, 30.0, 45.0, 60.0, 75.0]
copy

1. Why are lists useful for batch processing in Python?

2. What Python structure allows you to store multiple values for batch operations?

3. Fill in the blank: To apply a function to every item in a list, you typically use a ________.

question mark

Why are lists useful for batch processing in Python?

Select all correct answers

question mark

What Python structure allows you to store multiple values for batch operations?

Select the correct answer

question-icon

Fill in the blank: To apply a function to every item in a list, you typically use a ________.

Tutto è chiaro?

Come possiamo migliorarlo?

Grazie per i tuoi commenti!

Sezione 1. Capitolo 2
some-alt