网上搜索到的答案是使用chrome driver实现的， 但是本人的程序是运行在centos下的，centos下折腾chrome driver比较蛋疼，所以看了下pyecharts.render的源码，其实这个也支持使用无头phantomjs进行截图的，当然这个不是一般的直接截取屏幕，是通过JS代码把html里面的渲染图像下载下来，清晰度比普通截图要高很多很多。
 

make_snapshot(snapshot, bar.render(), f"data/{today}_cb.png", driver=driver)
 
在最后一行传入一个driver既可以了，这个driver使用phantomjs的实例。
 
import os
from pyecharts.render import make_snapshot
from snapshot_selenium import snapshot
import pandas as pd
from pyecharts import options as opts
from pyecharts.charts import Bar
import sys
from selenium import webdriver
from pyecharts.commons.utils import JsCode

if sys.platform == 'win32':
SELENIUM_PATH = r'C:\OneDrive\Tool\phantomjs-2.1.1-windows\phantomjs-2.1.1-windows\bin\phantomjs.exe'
driver = None
else:
SELENIUM_PATH = './phantomjs'
driver = webdriver.PhantomJS(executable_path=SELENIUM_PATH)


bar = (
Bar()
.add_xaxis(list(result_dict .keys()))
.add_yaxis(f"{today}-可转债价格分布", y_list, category_gap=3)
.add_yaxis(f"{today}-正股价格分布", y_zg_list, category_gap=3)
.set_series_opts(
label_opts=opts.LabelOpts(is_show=True),
axispointer_opts=opts.AxisPointerOpts(is_show=True))
.set_global_opts(
title_opts=opts.TitleOpts(title="可转债价格分布"),
xaxis_opts=opts.AxisOpts(
name="涨跌幅",
is_show=True,
name_rotate=30,
),
graphic_opts=[
opts.GraphicGroup(
graphic_item=opts.GraphicItem(
left="70%",
top="20%",
),
children=[
opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center",
top="middle",
z=100,
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
text=JsCode(
f"['涨幅>=0：{bigger}',"
f"'涨幅<0：{smaller}',"
f"'平均涨幅：{avg}%',"
f"'波动方差：{std}',"
f"'',"
f"'最大：{max_name} {max_pct}%',"
f"'最小：{min_name} {min_pct}%',"
"''].join('\\n')"
),
font="14px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#333"
)
)
)
]
)
],
)

)

bar.render(os.path.join('data', f"{today}_cb.html"))
make_snapshot(snapshot, bar.render(), f"data/{today}_cb.png", driver=driver)



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import os

from pyecharts.render import make_snapshot

from snapshot_selenium import snapshot

import pandas as pd

from pyecharts import options as opts

from pyecharts.charts import Bar

import sys

from selenium import webdriver

from pyecharts.commons.utils import JsCode



if sys.platform == 'win32':

    SELENIUM_PATH = r'C:\OneDrive\Tool\phantomjs-2.1.1-windows\phantomjs-2.1.1-windows\bin\phantomjs.exe'

    driver = None

else:

    SELENIUM_PATH = './phantomjs'

    driver = webdriver.PhantomJS(executable_path=SELENIUM_PATH)

    

    

    bar = (

        Bar()

            .add_xaxis(list(result_dict .keys()))

            .add_yaxis(f"{today}-可转债价格分布", y_list, category_gap=3)

            .add_yaxis(f"{today}-正股价格分布", y_zg_list, category_gap=3)

            .set_series_opts(

            label_opts=opts.LabelOpts(is_show=True),

            axispointer_opts=opts.AxisPointerOpts(is_show=True))

            .set_global_opts(

            title_opts=opts.TitleOpts(title="可转债价格分布"),

            xaxis_opts=opts.AxisOpts(

                name="涨跌幅",

                is_show=True,

                name_rotate=30,

            ),

            graphic_opts=[

                opts.GraphicGroup(

                    graphic_item=opts.GraphicItem(

                        left="70%",

                        top="20%",

                    ),

                    children=[

                        opts.GraphicText(

                            graphic_item=opts.GraphicItem(

                                left="center",

                                top="middle",

                                z=100,

                            ),

                            graphic_textstyle_opts=opts.GraphicTextStyleOpts(

                                text=JsCode(

                                    f"['涨幅>=0：{bigger}',"

                                    f"'涨幅<0：{smaller}',"

                                    f"'平均涨幅：{avg}%',"

                                    f"'波动方差：{std}',"

                                    f"'',"

                                    f"'最大：{max_name}  {max_pct}%',"

                                    f"'最小：{min_name}  {min_pct}%',"

                                    "''].join('\\n')"

                                ),

                                font="14px Microsoft YaHei",

                                graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(

                                    fill="#333"

                                )

                            )

                        )

                    ]

                )

            ],

        )



    )



    bar.render(os.path.join('data', f"{today}_cb.html"))

    make_snapshot(snapshot, bar.render(), f"data/{today}_cb.png", driver=driver)

难道不知道python的数据分析用的是numpy的数据类型么？
 
一些扩展的类型int64作为数据导入到绘图函数中，居然不兼容，而且也不报错。 
经过逐个参数的排查，才发现是数据类型的问题。 数据是直接在pandas里面抽取出来的，然后填充到绘图汇总，然后就显示一片空白，还一直以为是我哪个参数用错了。
 
也许是从前端设计者手里接过来的项目吧。按葫芦画瓢这样操作。
 
一个函数里面居然可以放置几十个，上百个参数，我滴神呀，而且参数里面还有其他类型的参数，尼玛！

 
当然最让人头疼是那往上不兼容的做法，现在的新版本完全已经修改了，不兼容旧版本，之前的写代码又是一通修改。 查看全部