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Python SDK

The official Python SDK for Vehk Axle Fleet Management Platform.

Installation​

pip install vehk-axle

Requirements: Python 3.8+

Quick Start​

from vehk_axle import VehkClient

# Initialize client
client = VehkClient(api_key="vehk_your_api_key")

# Send telemetry
client.telemetry.send(
    vehicle_id="VH-001",
    sensor_data={"speed": 65, "rpm": 2500}
)

# Get prediction
prediction = client.predict("VH-001", {"speed": 65, "rpm": 2500})
print(f"Health: {prediction.health_score}%")

Client Configuration​

from vehk_axle import VehkClient

client = VehkClient(
    api_key="vehk_your_api_key",
    base_url="https://api.vehk.in",  # Custom URL (optional)
    timeout=60,                       # Request timeout in seconds
    retries=3,                        # Number of retry attempts
    retry_delay=1.0                   # Delay between retries
)

Telemetry API​

Send Single Telemetry​

response = client.telemetry.send(
    vehicle_id="TRUCK-001",
    sensor_data={
        "speed": 65,
        "rpm": 2500,
        "coolant_temp": 92,
        "fuel_level": 45,
        "battery_voltage": 12.6
    },
    timestamp="2026-01-14T10:00:00Z",  # Optional
    location={"lat": 12.97, "lng": 77.59}  # Optional
)

print(response["telemetry_id"])  # Unique ID for this data point

Send Batch Telemetry​

Send up to 100 records at once for better performance:

from vehk_axle import TelemetryData

batch_result = client.telemetry.send_batch([
    {"vehicle_id": "TRUCK-001", "sensor_data": {"speed": 65, "rpm": 2500}},
    {"vehicle_id": "TRUCK-002", "sensor_data": {"speed": 70, "rpm": 2800}},
    {"vehicle_id": "TRUCK-003", "sensor_data": {"speed": 55, "rpm": 2200}},
])

print(f"Processed: {batch_result.records_processed}")
print(f"Time: {batch_result.processing_time_ms}ms")

Predictions API​

Get Prediction​

prediction = client.predictions.get(
    vehicle_id="TRUCK-001",
    sensor_data={
        "speed": 65,
        "rpm": 2500,
        "coolant_temp": 92
    }
)

# Access prediction data
print(f"Health Score: {prediction.health_score}%")
print(f"Health Status: {prediction.health_status.value}")  # healthy/warning/critical
print(f"Risk Level: {prediction.risk_level.value}")  # low/medium/high

# Check if critical
if prediction.is_critical:
    print("⚠️ Vehicle needs immediate attention!")

# Get maintenance recommendations
for alert in prediction.maintenance_alerts:
    print(f"- {alert.type}: {alert.description} (Urgency: {alert.urgency})")

# Get AI recommendations
for rec in prediction.recommendations:
    print(f"💡 {rec}")

List Recent Predictions​

# Get all recent predictions
predictions = client.predictions.list(limit=50)

# Filter by vehicle
vehicle_predictions = client.predictions.list(vehicle_id="TRUCK-001", limit=10)

for p in predictions:
    print(f"{p.vehicle_id}: {p.health_score}%")

Vehicles API​

List All Vehicles​

vehicles = client.vehicles.list()

for vehicle in vehicles:
    print(f"{vehicle.vehicle_id}: {vehicle.make} {vehicle.model}")
    print(f"  Health Score: {vehicle.health_score}%")
    print(f"  VIN: {vehicle.vin}")

Error Handling​

from vehk_axle import (
    VehkClient,
    VehkAuthenticationError,
    VehkRateLimitError,
    VehkConnectionError,
    VehkAPIError,
)

try:
    prediction = client.predict("VH-001", {"speed": 65})
    
except VehkAuthenticationError:
    print("❌ Invalid API key")
    
except VehkRateLimitError as e:
    print(f"⏳ Rate limited. Retry after {e.retry_after} seconds")
    
except VehkConnectionError:
    print("🔌 Network error - check your connection")
    
except VehkAPIError as e:
    print(f"⚠️ API Error [{e.status_code}]: {e.message}")

Data Models​

Prediction​

PropertyTypeDescription
health_scorefloatOverall health score (0-100)
health_statusHealthStatuscritical, warning, or healthy
risk_levelRiskLevelhigh, medium, low, or none
componentsdictComponent-level health scores
maintenance_alertslistPending maintenance items
recommendationslist[str]AI-generated recommendations
is_criticalboolTrue if immediate attention needed
needs_maintenanceboolTrue if maintenance is pending

Vehicle​

PropertyTypeDescription
vehicle_idstrUnique vehicle identifier
vinstrVehicle Identification Number
makestrManufacturer name
modelstrModel name
yearintManufacturing year
health_scorefloatCurrent health score

Context Manager​

# Automatically close the session when done
with VehkClient(api_key="vehk_your_key") as client:
    prediction = client.predict("VH-001", {"speed": 65})
    print(prediction.health_score)

Health Check​

# Check if API is reachable (no auth required)
health = client.health_check()
print(f"API Status: {health['status']}")

Supported Sensor Fields​

FieldDescriptionUnit
speedVehicle speedkm/h
rpmEngine RPMRPM
coolant_tempCoolant temperature°C
fuel_levelFuel level%
battery_voltageBattery voltageV
oil_pressureOil pressurePSI
throttleThrottle position%
intake_air_tempIntake air temperature°C
ambient_tempAmbient temperature°C
odometerOdometer readingkm

Full Example​

from vehk_axle import VehkClient
import time

def monitor_fleet():
    client = VehkClient(api_key="vehk_your_key")
    
    # Get all vehicles
    vehicles = client.vehicles.list()
    print(f"Monitoring {len(vehicles)} vehicles...")
    
    for vehicle in vehicles:
        # Simulate sensor reading
        sensor_data = {
            "speed": 65,
            "rpm": 2500,
            "coolant_temp": 92,
            "fuel_level": 45
        }
        
        # Get prediction
        prediction = client.predict(vehicle.vehicle_id, sensor_data)
        
        # Alert on critical vehicles
        if prediction.is_critical:
            print(f"🚨 CRITICAL: {vehicle.vehicle_id}")
            print(f"   Health: {prediction.health_score}%")
            for alert in prediction.maintenance_alerts:
                print(f"   - {alert.description}")
        elif prediction.health_score < 70:
            print(f"⚠️ WARNING: {vehicle.vehicle_id} - Health: {prediction.health_score}%")
        else:
            print(f"✅ OK: {vehicle.vehicle_id} - Health: {prediction.health_score}%")

if __name__ == "__main__":
    monitor_fleet()