roboreactor 0.1.2

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

## Example motion system code
```bash
from roboreactor import RoboReactor

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

import time

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 
``` bash 
import math

## 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 parse complex multidimensional arrays or specialized hardware telemetry structures.
``` bash 
import random
import math

## --- Category 1: Battery Management Systems (BMS Telemetry) ---
bms_payload = {
    "BMS_sensor": {
        "main_pack": 88.5, 
        "aux_cell_1": 86.5, 
  import random
import math

## --- 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.")      "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.")