How to call Baidu Map API through Python programming to display urban traffic hotspot maps?

How to call Baidu Map API through Python programming to display urban traffic heat map?

As urban traffic becomes increasingly congested, understanding urban traffic hot spots is very important for travel planning and traffic management. Baidu Maps provides a powerful API interface that can easily obtain traffic hotspot data and display it visually. This article will introduce how to use Python programming to call Baidu Map API to display urban traffic heat maps.

First, we need to create an application on the Baidu Map open platform and obtain the API key. Open the Baidu Map Open Platform website, register and log in to your account. Create a new application, select "Web Service Application", and fill in the application name, security code and other information. After successful creation, the API key can be found on the application management page.

Next, we need to install Python’s HTTP request library requests. Run the following command in the command line to install:

pip install requests

After the installation is complete, we can start writing code.

First, import the requests library and define some variables:

import requests

# 百度地图API密钥
API_KEY = 'your_api_key'

# 请求URL
url = 'http://api.map.baidu.com/traffic/v1/heatmap/weight'

Next, we need to construct the request parameters. First, define the city name and timestamp:

# 城市名称
city = '北京市'

# 时间戳，当前时间的前一个小时
import time
timestamp = int(time.time()) - 3600

Then, build the request parameter dictionary:

# 请求参数
params = {
    "ak": API_KEY,
    "region": city,
    "timestamp": timestamp
}

Next, send an HTTP GET request and get the returned data:

# 发送请求
response = requests.get(url, params=params)

# 获取返回的JSON数据
data = response.json()

According to the returned JSON data, we can obtain information about urban traffic hot spots. For example, you can obtain the city range, layer list, thermal parameters, etc. of the heat map.

Finally, we can perform visual display based on the obtained data. Here, we use Python’s visualization library matplotlib to draw urban traffic hotspot maps. You need to install the matplotlib library first, and run the following command on the command line to install it:

pip install matplotlib

Then, write the code to draw the heat map:

import matplotlib.pyplot as plt

# 获取热力图数据
heatmap_data = data['data']

# 绘制热力图
plt.imshow(heatmap_data, cmap='hot', interpolation='nearest')

# 隐藏坐标轴
plt.axis('off')

# 添加标题
plt.title(f'{city}交通热点图')

# 显示热力图
plt.show()

In the above code, we use the plt.imshow function to draw For heat maps, the cmap parameter specifies the color mapping scheme used, and the interpolation parameter specifies the interpolation method. Next, use plt.axis('off') to hide the axis, and use plt.title to add a title. Finally, use plt.show() to display the heat map.

So far, we have completed the entire process of calling Baidu Map API through Python programming to display urban traffic hotspot maps. Through the above code example, we can easily obtain urban traffic hotspot data and display it visually, helping us understand urban traffic conditions and optimize travel planning.

It is worth noting that Baidu Map API has a certain number of access restrictions. If you need high-frequency access, please apply for a higher-level service based on actual needs. In addition, refer to the Baidu Map API documentation to learn more details about parameters and return data, and make appropriate adjustments and optimizations to the code according to needs.

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