数据可视化Pyecharts的实际使用方式

import sys
import os
import requests

QUERY_ENDPOINT = "query"
QUERY_RANGE_ENDPOINT = "query_range"

class PrometheusQueryAPI:
    """Class Create Prometheus query api"""

    def __init__(self, api, proxy=None) -> None:
        self.api = api
        self.endpoint = "query"
        self.params = {}
        self.result = None
        self.proxy = proxy
        
    def clean(self):
        """清理查询参数
        """
        self.params = {}

    def query(self, query, time=None):
        """Create the query"""
        self.params["query"] = query
        if time:
            self.params["time"] = time

        self.endpoint = QUERY_ENDPOINT
        return self
    
    def query_range(self, query, start=None, end=None, step=None):
        """Create the Query range"""
        self.params["query"] = query
        if start:
            self.params["start"] = start
        if end:
            self.params["end"] = end
        if step:
            self.params["step"] = step
        self.endpoint = QUERY_RANGE_ENDPOINT
        return self
    
    def run(self):
        """Run the prometheus query"""
        url = os.path.join(self.api, self.endpoint)
        if sys.platform.startswith('win'):
            url = url.replace('\\', '/')
        res = requests.get(url=url, params=self.params,
                           proxies=self.proxy, timeout=30)
        self.result = res.json()
        self.clean()
        return self

p = prometheus.PrometheusQueryAPI(
    PROMETHEUS, proxy=PROXY)
p.query("yarn_exporter_allocateMem/(yarn_exporter_availableMem+yarn_exporter_allocateMem)")
p.run()
data = round(float(p.result["data"]["result"][0]["value"][1])*100, 2)

from pyecharts.charts import Gauge
	gauge1 = (
        Gauge()
        .add(
            # 必要配置
            series_name="内存使用率",
            data_pair=[["内存使用率", data]],
            # 设置仪表盘的条例
            axisline_opts=opts.AxisLineOpts(
                linestyle_opts=opts.LineStyleOpts(
                    # 设置不同区间的颜色，color中划分不通区间的颜色，width为线条粗细
                    color=[(0.3, "#E9EB2E"), (0.9, "#37a2da"), (1, "#fd666d")], width=10
                )
            ),
            # tooltip的设置，进行显示的格式化
            tooltip_opts=opts.TooltipOpts(
                is_show=True, formatter="{b} : {c}%"),
            max_=100,
            min_=0,
            # 设置相对位置，横纵坐标，当使用Grid组合Gauge时必须设置，否则图表会重合
            center=["25%", "50%"],
            # 仪表盘内的指标名称字体设置
            title_label_opts=opts.GaugeTitleOpts(
                font_weight="bold",
                font_size=20
            ),
            # 仪表盘内的指标数值的设置
            detail_label_opts=opts.GaugeDetailOpts(
                formatter="{value}%",
                color="#1267CB",
                font_weight="bold",
                font_size="20",
                offset_center=["0%", "40%"],
            )
        )
        .set_global_opts(
            # Gauge的标题设置
            title_opts=opts.TitleOpts(
                title="内存使用率",
            ),
            # 设置图例格式
            legend_opts=opts.LegendOpts(is_show=False),
        )
    )

    bar = (
        Bar(init_opts=opts.InitOpts(width="850px", height="800px"))
        .add_xaxis(xaxis_data=province)
        .add_yaxis("HDFS", values)
        .set_global_opts(
            title_opts=opts.TitleOpts(title="HDFS使用情况"),
            visualmap_opts=opts.VisualMapOpts(
                min_=0,
                max_=100,
                # 组件映射维度
                dimension=0,
                # 是否为分段型，如果设置为False，会出现一个完整的分段条可以拖动调节
                is_piecewise=True,
                # 设置不同取值区间的颜色
                range_color=[
                    "#00EC00", "#00A600",
                    "#FFD306", "#FF8000", "#FF2D2D"],
                orient="horizontal",
                pos_top="0%", pos_left="40%"
            ),
            legend_opts=opts.LegendOpts(
                is_show=False
            ),
            xaxis_opts=opts.AxisOpts(
                max_=100
            )
        )
        .set_series_opts(
            # 设置标记线，如果进行了行列转置，这里的操作就要对X轴进行了而不是Y轴！
            markline_opts=opts.MarkLineOpts(
                data=[
                    opts.MarkLineItem(
                        x=80,
                        name="使用率过高",
                        linestyle_opts=opts.LineStyleOpts(
                            color="red",
                        )
                    )
                ]
            ),
        )
        # 翻转XY轴
        .reversal_axis()
    )

Bar(
    opts.InitOpts(width="850px", height="800px")
)

return render_template("view.j2", data=bar.render_embed())

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