roboreactor 0.1.4

A unified Python client for Roboreactor edge devices and robot simulators.

roboreactor

Official Python client library for connecting edge devices, emulators, and robot controls directly to the RoboReactor ecosystem.

Installation

pip install roboreactor

Digital Twin Motion Control

To stream joint motion feedback and synchronize with the motion twin simulation, use the following example:

from roboreactor import RoboReactor
import time

# Initialize the synchronized connection client
client = RoboReactor(
    email="[e-mail]",
    project_name="Smart_Robots",
    base_url="https://roboreactor.com"  # Defaults to https://roboreactor.com if omitted
)

print("[INFO] Initiating joint loop feedback sequence...")

# Emulating a real-world physical sweeping path (0° to 269°)
for angle in range(0, 270):
    joint_telemetry = {
        'wrist': {'Analog-read': float(angle)},
        'shoulder': {'Analog-read': float(angle)},
        'base': {'Analog-read': float(angle)}
    }
    
    # Broadcast state variables directly to the cloud dashboard
    response = client.update_feedback_sensors(joint_telemetry)
    print(f"[TX] Angle: {angle}° | Status Response: {response}")
    time.sleep(0.01)

Absolute Target Kinematics & Orientation Control in Navigation simulation digital twin sync on the web

To sync high-level coordinates, orientations, and specific target angles to the navigation simulator rendering engine:

import math
from roboreactor import RoboReactor

# Initialize the client
client = RoboReactor(
    email="[e-mail]",
    project_name="Smart_Robots",
    base_url="https://roboreactor.com"
)

# Define targeted joint spatial layout arrays (configured in Radians)
joint_targets = {
    "shoulder": math.radians(150),
    "base": math.radians(45),
    "wrist": math.radians(20)
}

# Fire absolute multi-axis coordinate trajectories into the rendering engine
response = client.send_navigation_control(
    x=1.5,
    y=0.0,
    z=1.5,
    roll_deg=0.0,
    pitch_deg=0.0,
    yaw_deg=0.0,
    joint_targets_rad=joint_targets,
    robot_name="Robot_arm_01"
)

print(f"[NAV-TX] Kinematics Status Update: {response}")

Heterogeneous Multi-Sensor Payload Ingestion

Leverage the standard unified telemetry pipeline (post_sensor_data) to ingest complex multidimensional arrays, spatial matrices, audio streams, or specialized hardware telemetry.

import random
import math
from roboreactor import RoboReactor

# Initialize the client
client = RoboReactor(
    email="[e-mail]",
    project_name="Smart_Robots",
    base_url="https://roboreactor.com"
)

# --- Category 1: Battery Management Systems (BMS Telemetry) ---
bms_payload = {
    "BMS_sensor": {
        "main_pack": 88.5, 
        "aux_cell_1": 86.5, 
        "temp_sensor_5": 35.5
    }
}
client.post_sensor_data(bms_payload)

# --- Category 2: Inertial Measurement Units (IMU Kinematics) ---
imu_payload = {
    "Motion_sensor": {
        "imu_1": {
            "x": random.uniform(-0.1, 0.1),
            "y": random.uniform(-0.1, 0.1),
            "z": 1.015
        },
        "radar_2": 3.45
    }
}
client.post_sensor_data(imu_payload)

# --- Category 3: Spatial Matrices (2D Tactile Arrays / Temperature Heatmaps) ---
# Constructs a standard 10x10 floating matrix grid 
tactile_matrix = [[round(random.uniform(8.5, 9.0), 4) for _ in range(10)] for _ in range(10)]
matrix_payload = {
    "Array_sensor": {
        "Tactile_finger_sensor_1": tactile_matrix
    }
}
client.post_sensor_data(matrix_payload)

# --- Category 4: High-Frequency Audio Signals (Digital Signal Processing Vectors) ---
audio_waveform = [round(math.sin(i * 0.5) * 0.05, 4) for i in range(50)]
audio_payload = {
    "Audio_sensor": {
        "mic_1": audio_waveform
    }
}
client.post_sensor_data(audio_payload)

print("[SUCCESS] Multi-category sensory dataset dispatched.")