hoops_ai

Quick Overview

Modules

hoops_ai.cadaccess	CAD Access Module
hoops_ai.cadencoder	CAD Encoding Module
hoops_ai.dataset	Dataset Management Module
hoops_ai.flowmanager	Data Flow Management Module
hoops_ai.ml	Machine Learning Module
hoops_ai.storage	Data Storage Module
hoops_ai.insights	Data Analysis and Visualization Module

Functions

set_license(license_key[, validate])	Set the HOOPS AI license key with validation.
get_license_info()	Get current license configuration status (masked for security).
use_test_license()	Returns the HOOPS AI test license key for evaluation purposes.
create_flow(name, tasks, flows_outputdir[, ...])	Module-level flow creation function with simplified parameters.

HOOPS AI - Machine Learning Framework for CAD Data Analysis

HOOPS AI is a comprehensive machine learning framework specifically designed for Computer-Aided Design (CAD) data analysis and processing. It provides a complete toolkit for working with CAD models, from data access and encoding to machine learning workflows and interactive visualization.

Core Modules

The framework is organized into specialized modules, each with dedicated programming guides:

• CAD Access (hoops_ai.cadaccess): Load and access CAD models from various formats

  • Programming Guide: CAD Data Access

• CAD Encoding (hoops_ai.cadencoder): Convert CAD geometry into ML-ready representations

  • Programming Guide: CAD Data Encoding

• Dataset Management (hoops_ai.dataset): Handle large-scale CAD datasets efficiently

  • Programming Guide: Datasets - ML-Ready Inputs

• Data Storage (hoops_ai.storage): Persistent storage solutions for CAD data and ML models

  • Programming Guide: Data Storage

• Flow Management (hoops_ai.flowmanager): Build and execute ML workflows with CAD data

  • Programming Guide: Data Flow Customisation

• Machine Learning (hoops_ai.ml): ML models and training infrastructure for CAD analysis

  • Programming Guide: Machine Learning Model

• Insights & Visualization (hoops_ai.insights): Interactive visualization and data exploration

  • Programming Guide: Data Visualization Experience

hoops_ai.get_license_info()

Get current license configuration status (masked for security).

Returns:

Dictionary with license status

Return type:

dict

Example:

info = hoops_ai.get_license_info()
print(info)
{
    'license': 'ABCD1234***',
    'configured': True,
    'valid': True,
    'is_test_license': False
}

hoops_ai.set_license(license_key, validate=True)

Set the HOOPS AI license key with validation.

⚠️ REQUIRED: You must call this function before using any HOOPS functionality.

By default, this function validates the license to ensure it works correctly with all HOOPS AI components.

Parameters:

• license_key (str) – Your HOOPS license key as a string

• validate (bool) – Whether to validate the license immediately (default: True)

Returns:

None (raises RuntimeError if validation fails)

Raises:

• ValueError – If license_key is empty

• RuntimeError – If license validation fails

Example:

import hoops_ai
import os

# Use test license for evaluation
hoops_ai.set_license(hoops_ai.use_test_license())

# Set and validate your own license (recommended)
hoops_ai.set_license(os.getenv("HOOPS_LICENSE"))

# Set without validation (not recommended)
hoops_ai.set_license("my-license", validate=False)

hoops_ai.use_test_license()

Returns the HOOPS AI test license key for evaluation purposes.

⚠️ TEST LICENSE - Expires January 31, 2026

This license is provided for evaluation and experimentation purposes only. For production use, please obtain your own license from Tech Soft 3D.

Returns:

The test license key string

Return type:

str

Example

>>> import hoops_ai
>>>
>>> # Use test license for evaluation
>>> hoops_ai.set_license(hoops_ai.use_test_license())
>>>
>>> # Later, switch to your own license
>>> hoops_ai.set_license(os.getenv("HOOPS_LICENSE"))