AirQuility/AirQuilitySys/DayAirbing.py

import logging
import pymysql
import subprocess
import numpy as np
from matplotlib import pyplot as plt
#%matplotlib inline
from tkinter import Tk
from pyecharts import options as _opts
from pyecharts.charts import Bar

logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')

#db_config={'host':'127.0.0.1','user':'root','password':'mysql>hyx123','db':'airquility','charset':'utf8'}
#ptimelist=[]
#cilist=[]
#data_dict=dict(zip(ptimelist,cilist))

jan_list = []
feb_list = []
mar_list = []
apr_list = []
may_list = []
ptime_list = []

def get_data(db_config):
    """
    从数据库中获取ptime和ci数据。
    :param db_config: 数据库配置字典
    :return: 包含ptime和ci的元组列表
    """
 # 存储ptime数据的列表

    try:
        with pymysql.connect(**db_config) as conn:
            logging.info("数据库连接成功")

            with conn.cursor() as cursor:
                # 使用单个查询以提高性能

                sql_ptime = "SELECT ptime FROM May"
                cursor.execute(sql_ptime)
                data_ptime = cursor.fetchall()
                ptime_list = [row['ptime'] for row in data_ptime if 'ptime' in row]

                sql_may = "SELECT pm FROM may"
                cursor.execute(sql_may)
                data_may = cursor.fetchall()
                may_list = [row['pm'] for row in data_may if 'pm' in row]

                sql_feb="SELECT pm FROM feb"
                cursor.execute(sql_feb)
                data_feb=cursor.fetchall()
                #print(data_ci)
                feb_list = [row['pm'] for row in data_feb if 'pm' in row]

                sql_jan = "SELECT pm FROM jan"
                cursor.execute(sql_jan)
                data_jan = cursor.fetchall()
                # print(data_ci)
                jan_list = [row['pm'] for row in data_jan if 'pm' in row]

                sql_mar = "SELECT pm FROM mar"
                cursor.execute(sql_mar)
                data_mar = cursor.fetchall()
                # print(data_ci)
                mar_list = [row['pm'] for row in data_mar if 'pm' in row]

                sql_apr = "SELECT pm FROM apr"
                cursor.execute(sql_apr)
                data_apr = cursor.fetchall()
                # print(data_ci)
                apr_list = [row['pm'] for row in data_apr if 'pm' in row]

            return ptime_list, may_list, feb_list, jan_list, mar_list, apr_list
    except pymysql.err.OperationalError as e:
        logging.error(f"数据库操作失败: {e}")
        # 根据具体场景，可以选择返回空列表、抛出异常或返回特定错误码
        return [], [], [], [], [], []

def average(str_list):
    if not str_list:  # 检查列表是否为空
        return 0  # 或者根据需要处理，比如返回None或者抛出异常
    num_list = [float(item) for item in str_list]  # 假设可能有浮点数
    return sum(num_list) / len(num_list)



def visualize_data(ptime_list, may_list, feb_list, jan_list, mar_list, apr_list):
    """
    可视化数据。
    :param ptime_list: ptime数据列表
    :param ci_list: ci数据列表
    :param column_to_plot: 需要绘制的列名
    """
    if not may_list or not feb_list or not jan_list:
        logging.error("数据为空，无法进行可视化")
        return
    #y_list=[]
    #for i in range(4,8):
     #   y_list.append(i)
    x = np.arange(26)
    bar_width = 0.2
    # 调用函数并打印结果
    jan_value = average(jan_list)
    feb_value = average(feb_list)
    may_value = average(may_list)
    mar_value = average(mar_list)
    apr_value = average(apr_list)
    # 创建图形对象
    fig = plt.figure("average_pm2.5")

    #plt.title('每月pm2.5平均指数')
    # 创建子图
    ax = fig.add_axes([0, 0, 1, 1])
    # 让饼状图变成圆形
    ax.axis('equal')
    # 准备数据
    #labels = ['jan', 'feb', 'may','mar','apr']
    #num_data = [jan_value, feb_value, may_value, mar_value, apr_value]
    plt.figure(figsize=(15, 10), dpi=80)
    plt.bar(ptime_list, apr_value, tick_label=ptime_list, width=bar_width)
    plt.bar(x + bar_width, may_value, width=bar_width)
    # 饼状图之间的间隙大小
    #explode = (0.02, 0.03, 0.02, 0.01, 0.01)
    # 画饼
    #ax.pie(num_data, labels=labels, autopct='%1.1f%%', explode=explode)
    plt.show()



if __name__ == "__main__":
    db_config = {
        "host": '127.0.0.1',
        "user": "root",
        "password": 'mysql>hyx123',
        "db": 'airquility',
        "charset": 'utf8',
        "cursorclass": pymysql.cursors.DictCursor
    }

    ptime_list, may_list, feb_list, jan_list, mar_list, apr_list= get_data(db_config)
    visualize_data(ptime_list, may_list, feb_list, jan_list, mar_list, apr_list)

    #print(pymysql.__version__)

'''
    window= Tk()
    window.title("每日空气质量")
    window.geometry("300x200")
#Label(window, text="图表已生成为air_quality_index.html").pack()

    window.mainloop()
    '''