@app.route('/')

def hello_world():

    return 'Hello World!'

<li class="layui-col-xs3">

                      <a href="https://www.bilibili.com/v/popular/all?spm_id_from=333.851.b_7072696d61727950616765546162.3" target="_blank">

                        <cite class="c1">综合热门</cite>

                        <p><span>各个领域中新奇好玩的优质内容都在这里~</span></p>

                      </a>

                    </li>

if __name__ == '__main__':

    # 调用函数

    jsonData = TableToJson()

    print(u'转换为json格式的数据：', jsonData)

    # 以读写方式w+打开文件，路径前加r，防止字符转义

    f = open(r'D:/Bdatas/data01.json', 'w+',encoding="utf-8") 

    f.write(jsonData)    # 写数据

    f.close()    # 关闭文件

<link rel="stylesheet" href="../static/layui/css/layui.css"/>

<link rel="stylesheet" href="../static/css/admin.css"/>

    <link rel="stylesheet" href="../static/layui/css/bootstrap.css">

    <link rel="stylesheet" href="../static/layui/css/bootstrap-table.min.css">

    <script type="text/javascript" src="../static/layui/jquery-3.5.1.js"></script>

<script>

            $('#mytab03').bootstrapTable({

                method: 'get',

                url: "../static/json/data01.json", // 请求路径

                striped: true, // 是否显示行间隔色

                search: true, //是否显示表格搜索

                pageNumber: 1, // 初始化加载第一页

                pagination: true, // 是否分页

                sidePagination: 'client', // server:服务器端分页|client：前端分页

                pageSize: 20, // 单页记录数

                pageList: [5, 10, 20, 30],

                columns: [{

                        title: '标题',

                        field: 'title',

                    }]

            })

    </script>

#创建SparkSession对象

sc = SparkContext('local', 'spark_project')

sc.setLogLevel('WARN')

spark = SparkSession.builder.getOrCreate()

#创建DataFrame

df = spark.read.format('com.databricks.spark.csv')

.options(header='true', inferschema='true').load(

    'D:/SPARKFiles/listdata0012.csv')

#删除不需要的字段

df = df.drop('types', 'bv', 'date', 'url', 'title', 'danmu', 'favorite', 'likes', 'replay', 'share', 'view')

#将字符串字段转换为整型

df = df.withColumn("coins", df["coins"].cast(IntegerType()))

#去除选择字段为空值记录

df = df.dropna(subset = ["author","mid","coins"])

#打印默认的字段类型信息

df.printSchema()

#打印前20条数据

df.show()

#打印总行数

print(df.count())

df.coalesce(1).write.option("header", "true").csv("D:/Bdatas/technology04")

#播放量最高的10个视频

def maxplay():

    maxplayDF = spark.sql("SELECT title,MAX(replay) AS maxreplay FROM data GROUP BY title ORDER BY maxreplay DESC LIMIT 10")

    return maxplayDF.collect()

  def save(path, data):

        with open(path, 'w') as f:

            f.write(data)

if __name__ == "__main__":

    base = "static/json/"

    if not os.path.exists(base):

        os.mkdir(base)

    m = {

        "typeCount": {

            "method": typeCount,

            "path": "typeCount.json"

        } }

    for k in m:

        p = m[k]

        f = p["method"]

        save(base + m[k]["path"],

json.dumps(f(),ensure_ascii=False))

        print ("done -> " + k + " , save to -> " + base + m[k]["path"])

<script>

    var base64image = "data:image/png;base64,iVBORw0KGgo……Jggg=="

    var myChart = echarts.init(document.getElementById('chart'));

    myChart.showLoading();

    var maskImage = new Image();

    maskImage.src = base64image

    maskImage.onload = function () {

        $.getJSON("../static/json/authorCount.json", data => {

            var wc = [];

            data = data.map(v => ({

                author: v[0],

                count: parseInt(v[1]),

            }))

            for (var i = 0; i < 300; i++) {

                wc.push({

                    "name": data[i].author,

                    "value": data[i].count,

                });

            }

            myChart.setOption({

                backgroundColor: '#fff',

                title:{

                text: '视频热词'

                },

                tooltip: {

                    show: true

                },

                series: [{

                    type: 'wordCloud',

                    gridSize: 1,

                    sizeRange: [12, 55],

                    rotationRange: [-45, 0, 45, 90],

                    maskImage: maskImage,

                    textStyle: {

                        normal: {

                            color: function () {

                                return 'rgb(' +

                                    Math.round(Math.random() * 255) +

                                    ', ' + Math.round(Math.random() * 255) +

                                    ', ' + Math.round(Math.random() * 255) + ')'

                            }

                        }

                    },

                    left: 'center',

                    top: 'center',

                    right: null,

                    bottom: null,

                    data: wc

                }]

            });

            myChart.hideLoading();

        })

    }

</script>

plt.figure(figsize=(10,8))     #画布大小

#绘制训练集数据

plt.scatter(x=t0["share"][:300],y=t0["coins"][:300],color="r",label="types")

plt.scatter(x=t1["share"][:300],y=t1["coins"][:300],color="g",label="types")

#绘制测试集数据

right = test_X[result == test_y]

wrong = test_X[result != test_y]

plt.scatter(x = right["share"],y=right["coins"],color="c",marker="x",label="right")

plt.scatter(x = wrong["share"],y=wrong["coins"],color="m",marker=">",label="wrong")

plt.xlabel("分享数")

plt.ylabel("投币数")

plt.title("KNN分类结果显示")

plt.legend(loc="best")

# figure 保存为二进制文件

buffer = BytesIO()

plt.savefig(buffer)

plot_data = buffer.getvalue()

#plt.show()  # 显示绘制出的图

# 图像数据转化为 HTML 格式

imb = base64.b64encode(plot_data)

ims = imb.decode()

imd = "data:image/png;base64,"+ims

test_im = """<h1>Demo Figure</h1>  """ + """<img src="%s">""" % imd

# lxml 库的 etree 解析字符串为 html 代码，并写入文件

html = etree.HTML(test_im)

tree = etree.ElementTree(html)

tree.write('demo.html')