【详细教程】基于pyEchart的封装（附代码）

一、项目结构

二、文件封装

请注意替换实际的项目相对路径

2.1echart.py

from pyecharts.charts import Bar,Line,Pie  # 画条形图,折线图,饼图
from pyecharts import options as op
# 下载图片的工具函数
from snapshot_selenium import snapshot
# 生成图片的函数
from pyecharts.render import make_snapshot
# 饼状图需要模拟数据
from pyecharts.faker import Faker
# 导入mock数据
from 实验报告文档.实验代码.lab4.myFun.data.pyechartMock import *# 获取图片 传入bar对象和 文件路径
def generatePic(bar,filePath):make_snapshot(snapshot,bar.render(),filePath)# 画柱状图
# 1.传入一个横坐标，
# 2.传入一个包含y轴数据的字典，里面包含多个种类的数据
# 3.传入一个标题对象 里面包含标题和副标题
# 4.html生成的路径
def drawBar(xLabelList,yLabelDict,titleDict,targetPath):bar = Bar()bar.add_xaxis(xLabelList)for k,v in yLabelDict.items():bar.add_yaxis(k,v)bar.set_global_opts(title_opts=op.TitleOpts(title=titleDict['title'],subtitle=titleDict['subTitle']))bar.render(targetPath) # 渲染 生成html# generatePic(bar,filePath) # 要画很久 性能不行！！！# 画折线图
# 1.传入一个横坐标内容列表  week_name_list
# 2.传入一个数据字典 dataDict  里面包含多个对象 每个对象包含一个name 一个itemYLabelList
# 3.传入title对象
# 4.传入是否显示工具选项
def drawLine(xLabelList,yLabelDict,titleDict,targetPath,showTools):line = Line()line.add_xaxis(xaxis_data=xLabelList)for k,v in yLabelDict.items():line.add_yaxis(series_name=k,y_axis=v,markpoint_opts=op.MarkPointOpts(data=[# op.MarkPointItem(type_="max", name="最大值"), # 标记最大值点# op.MarkPointItem(type_="min", name="最小值"), # 标记最小值点]),markline_opts=op.MarkLineOpts(data=[# op.MarkLineItem(symbol="circle", type_="max", name="最高点"),  # 标记最高值线# op.MarkLineItem(type_="average", name="平均值"),               # 标记均值线# op.MarkLineItem(symbol="circle", type_="min", name="最低点"),  # 标记最低值线]),)line.set_global_opts(title_opts=op.TitleOpts(title=titleDict['title'], subtitle=titleDict['subTitle']),tooltip_opts=op.TooltipOpts(trigger="axis"),toolbox_opts=op.ToolboxOpts(is_show=showTools), # 这里设置是否显示下载等工具xaxis_opts=op.AxisOpts(type_="category", boundary_gap=False),)line.render(targetPath)# 画饼状图
# 1.一个名字列表
# 2.一个值列表
# 3.一个颜色列表
# 4.一个文件生成路径
# 5.一个标题对象
def drawPine(nameList,valueList,colorList,titleDict,targetPath):pie = Pie()pie.add("",[list(z) for z in zip(nameList,valueList)])pie.set_colors(colorList)pie.set_global_opts(title_opts=op.TitleOpts(title=titleDict['title']))pie.set_series_opts(label_opts=op.LabelOpts(formatter="{b}: {c}"))pie.render(targetPath)# 因为是给./data/pyechartMock调用的，所以写../ (x) 这种想法是错误的！！！
# import 就相当于将函数定义在当前文件了！！！
barFilePath = r'./pic/bar.html'
lineFilePath = r'./pic/line.html'
pieFilePath = r'./pic/pie.html'# pyechart unit testing
if __name__ == '__main__':print("主函数运行成功！")# 测试bar图像drawBar(BarList,BarDict,BarTitle,barFilePath)drawLine(LineList,LineDict,LineTitle,lineFilePath,showTools=True)drawPine(PieNameList,PieValueList,PieColorList,PieTitle,pieFilePath)# drawPine(pieFilePath)

2.2pyechartMock.py

import randomLISTNUM = 10    # x轴种类
DICTNUM = 5     # y轴种类
BarList = ['物品'+str(i) for i in range(LISTNUM)]
BarDict = dict()BarTitle = {'title':'这是柱状图的主标题','subTitle': '这是柱状图的副标题',
}
# 0 -> A
def numToAlph(num):return chr(num+65)
# A -> 0
def alphToNum(ch):return ord(ch)-65for i in range(DICTNUM):BarDict['商家'+str(numToAlph(i))] = [random.randint(10,100) for i in range(LISTNUM)]################################################
LineList = ['星期'+str(i) for i in range(LISTNUM)]
LineDict = dict()LineTitle = {'title':"这是折线图的主标题",'subTitle': '这是折线图的副标题',
}for i in range(DICTNUM):LineDict["种类"+str(numToAlph(i))] = [random.randint(10,100) for i in range(LISTNUM)]################################################
PieNameList = ['名字'+str(i) for i in range(LISTNUM)]
PieValueList = [random.randint(10,90)//10 for i in range(LISTNUM)]
PieColorList = ["blue", "green", "yellow", "red", "pink", "orange", "purple"]PieTitle = {'title':"这是饼状图的主标题",'subTitle': '这是饼状图的副标题',
}