Metadata-Version: 2.4
Name: sphero_unsw
Version: 0.1.11
Summary: Extensions and patches for spherov2 to support Sphero BOLT+ (UNSW Canberra fork)
Author-email: Kathryn Kasmarik <kathryn.kasmarik@unsw.edu.au>, Reda Ghanem <reda.ghanem@unsw.edu.au>
License-Expression: MIT
Project-URL: Homepage, https://github.com/redaghanem/sphero_unsw
Project-URL: Source, https://github.com/redaghanem/sphero_unsw
Keywords: sphero,sphero bolt,robotics,unsw
Classifier: Development Status :: 3 - Alpha
Classifier: Framework :: Robot Framework :: Library
Classifier: Intended Audience :: Education
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.12
Requires-Python: <3.13,>=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: bleak
Requires-Dist: spherov2
Dynamic: license-file

<!-- 
# ========================================================================
#  sphero_unsw: Extensions and patches for Sphero BOLT+
#  A fork of the original spherov2 library
#
#  Copyright (c) 2019-2021
#      Hanbang Wang,  https://www.cis.upenn.edu/~hanbangw
#      Elionardo Feliciano
#  Original project: https://github.com/EnotPoloskun/spherov2.py
#
#  library spherov2 was originally created for educational use in CIS 521: 
#  Artificial Intelligence at the University of Pennsylvania, where Sphero 
#  robots are used to help teach the foundations of AI.
#
#
#  This extension was developed by:
#       Kathryn Kasmarik (kathryn.kasmarik@unsw.edu.au)
#       Reda Ghanem (reda.ghanem@unsw.edu.au)
#  From the School of Systems and Computing, UNSW Canberra, to support the Sphero BOLT+ robot.
#
#  This extension has been developed for educational use as part of the course ZEIT1102:
#  Introduction to Programming at the University of New South Wales, Canberra (UNSW Canberra).
#  It is specifically designed to support students in learning programming fundamentals and 
#  introductory robotics concepts through hands-on activities using Sphero BOLT+ robots.
#
#  |---------------------------------------------------------------------|
#  | Version: 0.1.11                                                      |
#  | License: MIT License                                                |
#  | Repository: https://github.com/redaghanem/sphero_unsw               |
#  | Pypi package: https://pypi.org/project/sphero-unsw                  |
#  |---------------------------------------------------------------------|
#
# ========================================================================
-->

<!-- ----------------------------------------------------------------------------------------- -->
# sphero_unsw

![status](https://img.shields.io/pypi/status/sphero_unsw?style=for-the-badge)
![python version](https://img.shields.io/pypi/pyversions/sphero_unsw?style=for-the-badge)
[![pypi](https://img.shields.io/pypi/v/sphero_unsw?style=for-the-badge)](https://pypi.org/project/sphero_unsw/)
[![license](https://img.shields.io/pypi/l/sphero_unsw?style=for-the-badge)](https://github.com/redaghanem/sphero_unsw/blob/main/LICENSE)
![last commit](https://img.shields.io/github/last-commit/redaghanem/sphero_unsw?style=for-the-badge)
[![Downloads](https://static.pepy.tech/badge/sphero_unsw?style=for-the-badge)](https://pepy.tech/project/sphero_unsw)


An unofficial Python library for [Sphero](https://sphero.com/) toys.


<a href="https://sphero.com.au/collections/bolt-plus">
  <img src="https://github.com/redaghanem/sphero_unsw/blob/main/sphero_bolt_plus.jpg?raw=true" alt="Sphero BOLT+" width="300" height="300"/>
</a>


`sphero_unsw` is a fork of the [spherov2](https://github.com/artificial-intelligence-class/spherov2.py) Python library, extended to support the Sphero BOLT+ robot.

<!-- ----------------------------------------------------------------------------------------- -->
## About Us

This extension was developed by:
- [**Kathryn Kasmarik**](https://www.unsw.edu.au/staff/kathryn-kasmarik) (kathryn.kasmarik@unsw.edu.au)
- [**Reda Ghanem**](https://redaghanem.github.io) (reda.ghanem@unsw.edu.au)

From the [**School of Systems and Computing**](https://www.unsw.edu.au/canberra/about-us/our-schools/school-of-systems-and-computing), [**UNSW Canberra**](https://www.unsw.edu.au/canberra), to support the Sphero BOLT+ robot.

This extension has been developed for educational use as part of the course [**ZEIT1102: Introduction to Programming**](https://www.handbook.unsw.edu.au/undergraduate/courses/2025/zeit1102) at the University of New South Wales, Canberra (UNSW Canberra). It is specifically designed to support students in learning programming fundamentals and introductory robotics concepts through hands-on activities using Sphero BOLT+ robots.


<!-- ----------------------------------------------------------------------------------------- -->
## Installation

```bash
pip install sphero_unsw
```

<!-- ----------------------------------------------------------------------------------------- -->
## Features

- All features from the original [`spherov2`](https://github.com/artificial-intelligence-class/spherov2.py) library.
- Extended functionality for Sphero BOLT+.
- Compatible with Python 3.7 through 3.12.x (inclusive)

<!-- ----------------------------------------------------------------------------------------- -->
## Current Progress

The library is still under active development. Some features are implemented but not yet fully functional or reliable. Current work includes:

### ✅ Fully working
- Core robot connectivity and Bluetooth scanning
- Movement commands: `roll()`, `spin()`, `stop_roll()`
- Main LED and back LED control
- Sensor readings (light, orientation, velocity, gyroscope, acceleration, distance, heading)
- Event handling (e.g. collision, landing, freefall)

### ⚠️ Under development (not working yet)
- **IR Communication**: Not yet fully functional or reliable
- **Matrix Display**: Showing images on the BOLT+ matrix not working


We are actively working on identifying and resolving these compatibility issues.

<!-- ----------------------------------------------------------------------------------------- -->
## Usage
Usage Example: Sphero BOLT+ Demo with `sphero_unsw`

This script demonstrates a full-range test of Sphero BOLT+ capabilities using the `sphero_unsw` library. It includes:

- Connecting to a robot via Bluetooth
- Registering and handling multiple real-time events (e.g. collision, landing, freefall, charging)
- Testing main LED, back LED, and 8×8 matrix display
- Displaying static characters and scrolling messages
- Performing simple movements (roll, spin, stop)
- Reading real-time sensor data including light, orientation, velocity, gyroscope, and more


```python
# Import required libraries
import time
from sphero_unsw.toys_scanner import toys_scanner
from sphero_unsw.sphero_edu import SpheroEduAPI, EventType
from sphero_unsw.types import Color

# ---------------------------
# Define event handler functions
# ---------------------------

def on_collision(api):
    print("💥 Collision detected!")
    api.set_main_led(Color(255, 0, 0))  # Flash red
    time.sleep(0.3)
    api.set_main_led(Color(0, 0, 255))  # Return to blue

def on_freefall(api):
    print("🪂 Freefall detected")
    api.set_main_led(Color(255, 0, 0))  # Red

def on_landing(api):
    print("🟢 Landed")
    api.set_main_led(Color(0, 255, 0))  # Green

def on_gyro_max(api):
    print("🚀 Gyro max")
    api.set_main_led(Color(255, 0, 255))  # Magenta

def on_charging(api):
    print("⚡ Charging")
    api.set_main_led(Color(6, 0, 255))  # Indigo

def on_not_charging(api):
    print("🔋 Not charging")
    api.set_main_led(Color(255, 0, 47))  # Pinkish red

# ---------------------------
# Scan for nearby Sphero robots and connect to one
# ---------------------------

scanner = toys_scanner()
selected_toy = scanner.scan_and_select_toy()

# ---------------------------
# Open connection to the selected robot
# ---------------------------

with SpheroEduAPI(selected_toy) as api:
    print(f"Connected to {selected_toy.name}!")

    # Register events and handlers
    api.register_event(EventType.on_collision, on_collision)
    api.register_event(EventType.on_freefall, on_freefall)
    api.register_event(EventType.on_landing, on_landing)
    api.register_event(EventType.on_gyro_max, on_gyro_max)
    api.register_event(EventType.on_charging, on_charging)
    api.register_event(EventType.on_not_charging, on_not_charging)
    print("Event handlers registered.\n")


    # ---------------------------
    #  Fill the LED matrix using set_matrix_fill
    # ---------------------------
    api.set_matrix_fill(0,0,7,7,Color(255, 255, 255))        # Fill the LED matrix with white color using form pixel (0,0) to (7,7)

    # ---------------------------
    # Fill Main LED (RGB color)
    # ---------------------------
    api.set_main_led(Color(255, 0, 0))  # Red
    time.sleep(0.5)
    api.set_main_led(Color(0, 255, 0))  # Green
    time.sleep(0.5)
    api.set_main_led(Color(0, 0, 255))  # Blue
    time.sleep(0.5)

    # ---------------------------
    # Test Back LED and Front LED
    # ---------------------------
    api.set_back_led(255)                   # Full brightness
    time.sleep(1)
    api.set_back_led(0)                     # Turn off
    time.sleep(1)
    api.set_back_led(255)                   # Set back LED to full brightness
    time.sleep(1)
    api.set_front_led(Color(255, 0, 0))     # Set front LED to red
    time.sleep(1)

    # ---------------------------
    # Light up the LED matrix pixel by pixel
    # ---------------------------
    for x in range(8):
        for y in range(8):
            r = 255 // (x + 1)
            g = 255 // (y + 1)
            api.set_matrix_pixel(x, y, Color(r, g, 0))  # Gradient color
    time.sleep(1)

    # ---------------------------
    # Display a character on the matrix
    # ---------------------------
    api.set_matrix_character("A", Color(255, 255, 0))  # Yellow A
    time.sleep(1)

    # ---------------------------
    # Scroll a message across the matrix
    # ---------------------------
    api.scroll_matrix_text("UNSW", Color(255, 0, 0), fps=5, wait=True)
    time.sleep(8)

    # ---------------------------
    # Movement Tests
    # ---------------------------
    api.roll(0, 100, 2)   # Roll forward at heading 0° for 2 seconds
    time.sleep(2)

    api.spin(720, 3)      # Spin 720° over 3 seconds
    time.sleep(3)

    api.stop_roll()       # Stop movement

    # ---------------------------
    # Change the heading direction
    # ---------------------------
    api.set_heading(0)    # Set heading to 0°
    time.sleep(1)
    api.set_heading(90)   # Set heading to 90°
    time.sleep(1)

    # ---------------------------
    # Read sensor data
    # ---------------------------
    print("Ambient Light:", api.get_luminosity())
    print("Orientation:", api.get_orientation())
    print("Velocity:", api.get_velocity())
    print("Location:", api.get_location())
    print("Gyroscope:", api.get_gyroscope())
    print("Acceleration:", api.get_acceleration())
    print("Travel Distance:", api.get_distance())
    print("Heading:", api.get_heading())

    print("\nDemo complete.")
```

<!-- ----------------------------------------------------------------------------------------- -->
## Acknowledgments

We gratefully acknowledge the original authors of the [`spherov2`](https://github.com/artificial-intelligence-class/spherov2.py) library:

- **Hanbang Wang** – https://www.cis.upenn.edu/~hanbangw/
- **Elionardo Feliciano**

This library [`spherov2`](https://github.com/artificial-intelligence-class/spherov2.py) was originally created for educational use in **CIS 521: Artificial Intelligence** at the University of Pennsylvania, where Sphero robots are used to help teach the foundations of AI.

<!-- ----------------------------------------------------------------------------------------- -->
## License

MIT License. See the [LICENSE](https://github.com/redaghanem/sphero_unsw/blob/main/LICENSE) file.

This library is based on the original [`spherov2`](https://github.com/artificial-intelligence-class/spherov2.py) library developed by the University of Pennsylvania.
