qianxing-openapi 0.1.4

Qianxing OpenAPI SDK for Python - A client library for accessing Qianxing's simulation platform

Qianxing OpenAPI SDK for Python

A Python SDK for interacting with Qianxing's simulation platform. This package provides a simple and intuitive way to control and monitor simulations for autonomous driving scenarios.

Installation

You can install the package directly from PyPI:

pip install qianxing-openapi

Quick Start

Here's a simple example of how to use the SDK:

from qianxing_openapi.client import Client
from qianxing_openapi.http_client import HttpConfig
from qianxing_openapi.simulator import SimulatorConfig
from qianxing_openapi.request_model import Point

# Initialize the client
client = Client(
    HttpConfig(
        token="your_token_here",
        endpoint="your_endpoint_here"
    )
)

# Get available scenes from training task
res = client.train_task.get_scene_id_list(task_id)
print(f"Available scenes: {res}")

# Create a simulator instance
simulator = client.init_simulator_from_config(
    SimulatorConfig(
        scenario_id=res.scene_id_list[0],
        scenario_version=res.scene_version_list[0]
    )
)

# Run simulation steps
for i in range(10):
    step_res = simulator.step()
    print(f"Step {i} result: {step_res}")

# Get vehicle information
vehicle_ids = simulator.get_vehicle_id_list()
print(f"Vehicle IDs: {vehicle_ids}")

# Control vehicle movement
simulator.set_vehicle_control_info(
    vehicle_id="test_vehicle_1", 
    ste_wheel=1.2,
    lon_acc=1.1
)

# Set vehicle position
simulator.set_vehicle_position(
    vehicle_id="test_vehicle_1",
    point=Point(x=-8.75, y=-537.0316, z=0)
)

# Stop the simulation
simulator.stop()

Features

• Easy-to-use client interface
• Comprehensive simulation control
• Vehicle state monitoring and control
• Support for pedestrians and non-motorized vehicles
• Training task management
• Map resource handling

Main Components

• Client: Main entry point for the SDK
• HttpConfig: Configuration for API endpoints and authentication
• SimulatorConfig: Configuration for simulation scenarios
• Simulator: Core simulation control interface
• TrainTask: Training task management
• Resources: Map and resource handling

Available Methods

Simulation Control

• step(): Advance simulation by one step
• stop(): Stop the simulation

Vehicle Control

• get_vehicle_id_list(): Get all vehicle IDs
• get_vehicle_position(): Get vehicle positions
• set_vehicle_position(): Set vehicle position
• set_vehicle_control_info(): Set vehicle control parameters
• set_vehicle_moving_info(): Set vehicle movement parameters
• get_vehicle_base_info(): Get vehicle basic information

Pedestrian Control

• get_ped_id_list(): Get all pedestrian IDs
• get_ped_base_info(): Get pedestrian information
• set_ped_position(): Set pedestrian position

Non-motorized Vehicle Control

• get_nmv_id_list(): Get all non-motorized vehicle IDs
• get_nmv_base_info(): Get non-motorized vehicle information
• set_nmv_position(): Set non-motorized vehicle position

Requirements

• Python >= 3.0
• requests >= 2.25.0

License

This project is licensed under the terms of the MIT license.

Support

For bug reports and feature requests, please use the GitHub Issues page.