plotly / plotly/plotly.R

plotly core (a community vote for a simple wrapper to plotly.js)

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还没有人认领这个 Issue。

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描述

Hello, long time user of plotly.R here. I thought this issue could start the discussion to split up the package into a core and a full ggplotly supported package.

As many have noted, I also started using plotly from the ggplot2 interface of ggplotly,
but as times are changing, and I am getting to understand the drawbacks of wrapping things through ggplot more,
we are moving more and more away from it.

In our RiboCrypt app, we have for optimizations reasons removed all ggplotly calls and transformed to native plot_ly() calls. We experiment with optimizations like pre-building plotly template objects, to speed up "time to user see something useful".
And since this is an app for complicated genomics, R/bioconductor is still a far better fit than python.

A problem has been the last few year that new plotly.R versions break stuff, so I have to keep version set to a version I know works. Problem is that new version needs to pass not just plotly.js tests, but also ggplotly tests for regression, so it is currently much more complicated than it needs to be.

I vote for a clean split of the package, for existing popular R package doing this, see for example the fst package, which has fst and fstcore

plotlycore: Simple wrapper to plotly.js
plotly: Uses plotlycore + ggplotly interface.

This way I think it is more safe especially for people using it for actual production apps and not just scripting.

I thought we could discuss here what people have noticed lately, what the relevant goals of current maintainers are, what resources exist to do this etc.

贡献指南

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从这里开始

  1. 先读完整个 Issue,再读项目的贡献指南。
  2. 在 Issue 下留言说明你要接手 —— 这能避免两个人做同样的事。
  3. Fork 仓库,在一个分支上完成修改。
  4. 提交 Pull Request,并在描述里引用这个 Issue 编号。

调研方向

首先阅读简单的 plotly.js wrapper 与支持 ggplotly 的 package 之间的拆分方案,然后对比 issue 中链接的 fst/fstcore 示例。检查当前 plotly.R package 的结构,以及 plot_ly()、ggplotly 和 regression-test 的职责。维护者就具体的 package 边界和实现目标达成一致后,即视为完成。

由索引模型根据 Issue 内容生成。

评估

技术栈
javascript, r
领域
data-visualization
Issue 类型
功能
难度
5/5
预计耗时
一周以上
活跃度
冷清
描述清晰度
需要澄清
新手友好度
25/100

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