python将绘图保存到本地文件并插入到html中 [英] python save plotly plot to local file and insert into html

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问题描述

我正在使用 python 和 plotly 来生成交互式 html 报告.这篇文章提供了一个很好的框架.

I am using python and plotly to product interactive html report. This post gives a nice framework.

如果我在线生成绘图(通过 plotly),并将 url 插入 html 文件,它可以工作,但刷新图表需要很长时间.我想知道我是否可以离线生成图表并将其嵌入到 html 报告中,这样加载速度就不是问题了.

If I produce the plot(via plotly) online, and insert the url into the html file, it works but refreshing the charts takes a long time. I wonder if I could produce the chart offline and have it embedded in the html report, so that loading speed is not a problem.

我发现离线绘图会为图表生成一个 html,但我不知道如何将它嵌入到另一个 html 中.有人可以帮忙吗?

I find plot offline would generate a html for the chart, but I don't know how to embed it in another html. Anyone could help?

推荐答案

选项 1:在您的 Jupyter Notebook 中使用 plotly 的离线功能(我想您正在使用您提供的链接中的 Jupyter Notebook).您可以简单地将整个笔记本保存为 HTML 文件.当我这样做时,唯一的外部参考是 JQuery;plotly.js 将内联在 HTML 源代码中.

Option 1: Use plotly's offline functionality in your Jupyter Notebook (I suppose you are using a Jupyter Notebook from the link you are providing). You can simply save the whole notebook as a HTML file. When I do this, the only external reference is to JQuery; plotly.js will be inlined in the HTML source.

选项 2:最好的方法可能是直接针对 plotly 的 JavaScript 库进行编码.可在此处找到相关文档:https://plot.ly/javascript/

Option 2: The best way is probably to code directly against plotly's JavaScript library. Documentation for this can be found here: https://plot.ly/javascript/

更新:调用内部函数从来都不是一个好主意.我建议使用@Fermin Silva 给出的方法.在较新的版本中,现在还有一个专用函数:plotly.io.to_html(参见 https://plotly.com/python-api-reference/generated/plotly.io.to_html.html)

Update: Calling an internal function has never been a good idea. I recommend to use the approach given by @Fermin Silva. In newer versions, there now is also a dedicated function for this: plotly.io.to_html (see https://plotly.com/python-api-reference/generated/plotly.io.to_html.html)

Hacky Option 3(原版仅供参考):如果你真的想继续使用 Python,可以使用一些 hack 来提取它生成的 HTML.您需要一些最新版本的 plotly(我使用 plotly.__version__ == '1.9.6' 对其进行了测试).现在,您可以使用内部函数来获取生成的 HTML:

Hacky Option 3 (original version for reference only): If you really want to continue using Python, you can use some hack to extract the HTML it generates. You need some recent version of plotly (I tested it with plotly.__version__ == '1.9.6'). Now, you can use an internal function to get the generated HTML:

from plotly.offline.offline import _plot_html
data_or_figure = [{"x": [1, 2, 3], "y": [3, 1, 6]}]
plot_html, plotdivid, width, height = _plot_html(
    data_or_figure, False, "", True, '100%', 525)
print(plot_html)

您可以简单地将输出粘贴到 HTML 文档正文中的某个位置.只需确保在头部包含对 plotly 的引用:

You can simply paste the output somewhere in the body of your HTML document. Just make sure that you include a reference to plotly in the head:

<script src="https://cdn.plot.ly/plotly-latest.min.js"></script>

或者,您还可以引用用于生成 HTML 或内联 JavaScript 源代码的确切 plotly 版本(这会删除任何外部依赖项;但请注意法律方面的问题).

Alternatively, you can also reference the exact plotly version you used to generate the HTML or inline the JavaScript source (which removes any external dependencies; be aware of the legal aspects however).

你最终会得到一些像这样的 HTML 代码:

You end up with some HTML code like this:

<html>
<head>
  <script src="https://cdn.plot.ly/plotly-latest.min.js"></script>
</head>
<body>
  <!-- Output from the Python script above: -->
  <div id="7979e646-13e6-4f44-8d32-d8effc3816df" style="height: 525; width: 100%;" class="plotly-graph-div"></div><script type="text/javascript">window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL="https://plot.ly";Plotly.newPlot("7979e646-13e6-4f44-8d32-d8effc3816df", [{"x": [1, 2, 3], "y": [3, 1, 6]}], {}, {"showLink": false, "linkText": ""})</script>
</body>
</html>

注意:函数名称开头的下划线表示 _plot_html 并不意味着从外部代码调用.因此,此代码很可能会在未来版本的 plotly 中中断.

Note: The underscore at the beginning of the function's name suggests that _plot_html is not meant to be called from external code. So it is likely that this code will break with future versions of plotly.

这篇关于python将绘图保存到本地文件并插入到html中的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!

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