1-json库的使用
`json`库是Python标准库的一部分，用于处理JSON数据。它提供了`loads`、`dumps`等方法。
安装三方库
pip install json1-1-将JSON字符串解析为Python对象
1-1-1-语法
将JSON字符串解析为Python对象，然后可以像访问普通Python字典一样访问解析后的数据。
json.loads(json_str)1-1-2-例子
import json
# 定义一个JSON字符串
json_str = '{"name": "张三", "age": 30, "city": "北京"}'
# 将JSON字符串解析为Python对象
data = json.loads(json_str)
# 访问解析后的数据
print(data['name'])
print(data['age'])
print(data['city'])1-1-3-输出结果
1-2-将Python对象转换为JSON字符串
1-2-1-语法
`json.dumps`方法将Python字典转换为JSON字符串
json.dumps(pythonObj)1-2-2-例子
import json
# 定义一个Python字典
data = {
'name': 'John',
'age': 30,
'city': 'New York'
}
# 将Python对象转换为JSON字符串
json_str = json.dumps(data)
# 打印JSON字符串
print(json_str)1-2-3-输出结果
1-3-例子
实现从json文件中读取不同省份的人口总数并显示成柱状图
1-3-1-例子01
population.json
[
{"province": "广东省", "population": 126012510},
{"province": "山东省", "population": 101527453},
{"province": "河南省", "population": 98830000},
{"province": "四川省", "population": 83674866},
{"province": "江苏省", "population": 85054000},
{"province": "河北省", "population": 74610235},
{"province": "湖南省", "population": 66444864},
{"province": "浙江省", "population": 65400000},
{"province": "安徽省", "population": 61130000},
{"province": "湖北省", "population": 58300000}
]province_population_chart.py
用于封装json文件
import json
from jinja2 import Environment, FileSystemLoader
from collections import defaultdict
def read_province_population_from_json(json_file_path):
province_population = defaultdict(int)
try:
with open(json_file_path, 'r', encoding='utf-8') as file:
data = json.load(file)
for item in data:
province = item.get('province')
population = item.get('population', 0)
if province:
province_population[province] += population
return province_population
except FileNotFoundError:
print(f"错误：未找到文件 {json_file_path}")
except json.JSONDecodeError:
print(f"错误：无法解析 {json_file_path} 为有效的 JSON")
return province_population
def generate_bar_chart_html(province_population, html_output_path):
env = Environment(loader=FileSystemLoader('.'))
template = env.get_template('bar_chart_template.html')
provinces = list(province_population.keys())
populations = list(province_population.values())
html_content = template.render(provinces=provinces, populations=populations)
try:
with open(html_output_path, 'w', encoding='utf-8') as file:
file.write(html_content)
print(f"HTML 文件已生成：{html_output_path}")
except Exception as e:
print(f"错误：写入 HTML 文件时出错 - {e}")
if __name__ == "__main__":
json_file_path = 'province_population.json'
html_output_path = 'province_population_chart.html'
province_population = read_province_population_from_json(json_file_path)
generate_bar_chart_html(province_population, html_output_path)
bar_chart_template.html
省份人口柱状图
<script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
<script>
const ctx = document.getElementById('provincePopulationChart').getContext('2d');
const provinces = {{ provinces|tojson }};
const populations = {{ populations|tojson }};
new Chart(ctx, {
type: 'bar',
data: {
labels: provinces,
datasets: [{
label: '人口总数',
data: populations,
backgroundColor: 'rgba(75, 192, 192, 0.2)',
borderColor: 'rgba(75, 192, 192, 1)',
borderWidth: 1
}]
},
options: {
scales: {
y: {
beginAtZero: true
}
}
}
});
</script>
1-3-2-输出结果
输出结果
1-3-3-例子02
创建 MySQL 数据库表，并将 2020 年到 2025 年不同省份的人口总数以饼状图形式显示在 HTML 中
database_operations.py
import random
def create_table(mycursor):
mycursor.execute("""
CREATE TABLE IF NOT EXISTS population (
id INT AUTO_INCREMENT PRIMARY KEY,
province VARCHAR(255),
year INT,
population INT
)
""")
def insert_data(mycursor, mydb):
provinces = ["广东", "山东", "河南", "四川", "江苏"]
years = [2020, 2021, 2022, 2023, 2024, 2025]
for province in provinces:
for year in years:
population = random.randint(10000000, 20000000)
sql = "INSERT INTO population (province, year, population) VALUES (%s, %s, %s)"
val = (province, year, population)
mycursor.execute(sql, val)
mydb.commit()
def query_data(mycursor):
provinces = ["广东", "山东", "河南", "四川", "江苏"]
total_population = {}
for province in provinces:
sql = "SELECT SUM(population) FROM population WHERE province = %s AND year BETWEEN 2020 AND 2025"
val = (province,)
mycursor.execute(sql, val)
result = mycursor.fetchone()
total_population[province] = result[0]
return total_population
database_connection.py
import mysql.connector
def create_connection():
mydb = mysql.connector.connect(
host="localhost",
user="your_username",
password="your_password",
database="your_database"
)
return mydb
chart_generator.py
import matplotlib.pyplot as plt
import os
def generate_chart(total_population):
labels = total_population.keys()
sizes = total_population.values()
plt.pie(sizes, labels=labels, autopct='%1.1f%%')
plt.axis('equal')
if not os.path.exists('charts'):
os.makedirs('charts')
chart_path = 'charts/population_pie_chart.png'
plt.savefig(chart_path)
plt.close()
return chart_path
html_generator.py
def generate_html(chart_path):
html_content = f"""
2020 - 2025 年不同省份人口总数饼状图
2020 - 2025 年不同省份人口总数饼状图
"""
with open('population_chart.html', 'w', encoding='utf-8') as f:
f.write(html_content)
main.py
from database_connection import create_connection
from database_operations import create_table, insert_data, query_data
from chart_generator import generate_chart
from html_generator import generate_html
# 建立数据库连接
mydb = create_connection()
mycursor = mydb.cursor()
# 创建表
create_table(mycursor)
# 插入数据
insert_data(mycursor, mydb)
# 查询数据
total_population = query_data(mycursor)
# 生成饼状图
chart_path = generate_chart(total_population)
# 生成 HTML 文件
generate_html(chart_path)
print("数据库表创建成功，数据插入成功，饼状图已保存为图片，HTML 文件已生成。")