将IPython笔记本保持在版本控制下的好策略是什么?

笔记本格式非常适合版本控制:如果想对笔记本和输出进行版本控制,那么这种方法非常有效。当人们只想对输入进行版本控制,而不包括单元格输出时,就会出现烦恼。“构建产品”),可以是大的二进制blob,特别是电影和情节。特别是,我试图找到一个好的工作流程:

allows me to choose between including or excluding output, prevents me from accidentally committing output if I do not want it, allows me to keep output in my local version, allows me to see when I have changes in the inputs using my version control system (i.e. if I only version control the inputs but my local file has outputs, then I would like to be able to see if the inputs have changed (requiring a commit). Using the version control status command will always register a difference since the local file has outputs.) allows me to update my working notebook (which contains the output) from an updated clean notebook. (update)

如前所述,如果我选择包含输出(例如,在使用nbviewer时,这是可取的),那么一切都没问题。问题是当我不想对输出进行版本控制时。有一些工具和脚本可以剥离笔记本的输出,但我经常遇到以下问题:

I accidentally commit a version with the the output, thereby polluting my repository. I clear output to use version control, but would really rather keep the output in my local copy (sometimes it takes a while to reproduce for example). Some of the scripts that strip output change the format slightly compared to the Cell/All Output/Clear menu option, thereby creating unwanted noise in the diffs. This is resolved by some of the answers. When pulling changes to a clean version of the file, I need to find some way of incorporating those changes in my working notebook without having to rerun everything. (update)

我已经考虑了下面将要讨论的几个选项,但是还没有找到一个好的全面的解决方案。完整的解决方案可能需要对IPython进行一些更改,或者可能依赖于一些简单的外部脚本。我目前使用mercurial,但希望有一个解决方案也能与git一起工作:一个理想的解决方案是版本控制不可知的。

这个问题已经讨论过很多次了,但是从用户的角度来看,还没有明确的解决方案。这个问题的答案应该能提供明确的策略。如果它需要IPython的最新(甚至是开发版)版本或易于安装的扩展,那是没问题的。

更新:我一直在玩我修改过的笔记本版本,它可以选择保存一个.clean版本,每次保存都使用Gregory Crosswhite的建议。这满足了我的大部分约束条件,但留下了以下问题:

This is not yet a standard solution (requires a modification of the ipython source. Is there a way of achieving this behaviour with a simple extension? Needs some sort of on-save hook. A problem I have with the current workflow is pulling changes. These will come in to the .clean file, and then need to be integrated somehow into my working version. (Of course, I can always re-execute the notebook, but this can be a pain, especially if some of the results depend on long calculations, parallel computations, etc.) I do not have a good idea about how to resolve this yet. Perhaps a workflow involving an extension like ipycache might work, but that seems a little too complicated.

笔记

移除(剥离)输出

When the notebook is running, one can use the Cell/All Output/Clear menu option for removing the output. There are some scripts for removing output, such as the script nbstripout.py which remove the output, but does not produce the same output as using the notebook interface. This was eventually included in the ipython/nbconvert repo, but this has been closed stating that the changes are now included in ipython/ipython,but the corresponding functionality seems not to have been included yet. (update) That being said, Gregory Crosswhite's solution shows that this is pretty easy to do, even without invoking ipython/nbconvert, so this approach is probably workable if it can be properly hooked in. (Attaching it to each version control system, however, does not seem like a good idea — this should somehow hook in to the notebook mechanism.)

新闻组

关于版本控制的笔记本格式的思考。

问题

977:笔记本功能请求(打开)。 1280:清除-all保存选项(打开)。(从下面的讨论。) 3295:自动导出的笔记本:只导出显式标记的单元格(关闭)。扩展解决11添加写和执行魔法(合并)。

把请求

1621: clear In[] prompt numbers on "Clear All Output" (Merged). (See also 2519 (Merged).) 1563: clear_output improvements (Merged). 3065: diff-ability of notebooks (Closed). 3291: Add the option to skip output cells when saving. (Closed). This seems extremely relevant, however was closed with the suggestion to use a "clean/smudge" filter. A relevant question what can you use if you want to strip off output before running git diff? seems not to have been answered. 3312: WIP: Notebook save hooks (Closed). 3747: ipynb -> ipynb transformer (Closed). This is rebased in 4175. 4175: nbconvert: Jinjaless exporter base (Merged). 142: Use STDIN in nbstripout if no input is given (Open).


当前回答

由于存在如此多的策略和工具来处理笔记本电脑的版本控制,我试图创建一个流程图来选择一个合适的策略(创建于2019年4月)

其他回答

下面是Cyrille rosant为IPython 3.0提供的一个新解决方案,它坚持标记文件,而不是基于json的ipymd文件:

https://github.com/rossant/ipymd

我们有一个合作项目,产品是Jupyter notebook,我们在过去六个月里使用了一种非常有效的方法:我们自动激活保存。py文件,并跟踪。ipynb文件和。py文件。

这样,如果有人想查看/下载最新的笔记本,他们可以通过github或nbviewer来完成,如果有人想查看笔记本代码是如何更改的,他们可以只查看.py文件的更改。

对于Jupyter笔记本服务器,可以通过添加这些行来实现

import os
from subprocess import check_call

def post_save(model, os_path, contents_manager):
    """post-save hook for converting notebooks to .py scripts"""
    if model['type'] != 'notebook':
        return # only do this for notebooks
    d, fname = os.path.split(os_path)
    check_call(['jupyter', 'nbconvert', '--to', 'script', fname], cwd=d)

c.FileContentsManager.post_save_hook = post_save

到jupyter_notebook_config.py文件并重新启动笔记本服务器。

如果你不确定在哪个目录中找到你的jupyter_notebook_config.py文件,你可以输入jupyter——config-dir,如果你没有找到这个文件,你可以输入jupyter notebook——generate-config来创建它。

对于Ipython 3笔记本服务器,可以通过添加这些行来实现

import os
from subprocess import check_call

def post_save(model, os_path, contents_manager):
    """post-save hook for converting notebooks to .py scripts"""
    if model['type'] != 'notebook':
        return # only do this for notebooks
    d, fname = os.path.split(os_path)
    check_call(['ipython', 'nbconvert', '--to', 'script', fname], cwd=d)

c.FileContentsManager.post_save_hook = post_save

到ipython_notebook_config.py文件并重新启动笔记本服务器。这些句子来自github问题的答案@minrk提供和@dror包括他们在他的SO回答以及。

对于Ipython 2笔记本服务器,可以通过使用以下命令启动服务器来完成:

ipython notebook --script

或者加上这条直线

c.FileNotebookManager.save_script = True

到ipython_notebook_config.py文件并重新启动笔记本服务器。

如果您不确定在哪个目录中找到您的ipython_notebook_config.py文件,您可以键入ipython locate profile default,如果您在那里没有找到该文件,您可以键入ipython profile create来创建它。

这是我们在github上使用这种方法的项目:这是一个github上探索笔记本电脑最近变化的例子。

我们对此非常满意。

由于存在如此多的策略和工具来处理笔记本电脑的版本控制,我试图创建一个流程图来选择一个合适的策略(创建于2019年4月)

你可以使用这个jupyter扩展。它可以让你直接上传你的ipython笔记本到github。

https://github.com/sat28/githubcommit

我还制作了一个视频来演示这些步骤 youtube链接

与2019年更好的方法相比,上面这些2016年非常流行的答案是不一致的。

有几个选项,最好的答案是Jupytext。

Jupytext

在Jupytext上捕获朝向数据科学的文章

它与版本控制的工作方式是将.py和.ipynb文件放在版本控制中。如果您想要输入差异,请查看.py;如果您想要最新呈现的输出,请查看.ipynb。

值得一提的是:VS studio, nbconvert, nbdime, hydrogen

我认为再多做一些工作,VS studio和/或hydrogen(或类似的)将成为解决这个工作流程的主要参与者。