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Reproducible Data Analysis in Jupyter, Part 3/10: Version Control with Git & GitHub

Sign in to your account. Debugging code does not show current line highlighted - see image. However, in panel 'source' the line is highlighted. Name Version Build Channel absl-py 0.

Make Your Jupyter Notebooks Cool

JupyterLab v2. Thanks for the update. I'm not sure what is happening because I wasn't able to reproduce it locally, but we will look into it because it appears to be a regression. I have reinstalled everything as described in the Installation section note: nodejs is missing in the installation sectionbut it still does not work on my win Now, I have the packages: attrs However, on my Ubuntu everything works fine.

Thanks alphacentauri12 for sharing the details. The dependencies looks good. Skip to content. Dismiss Join GitHub today GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together. Sign up. New issue. Jump to bottom. Labels bug question. Copy link Quote reply.By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service.

The dark mode beta is finally here. Change your preferences any time. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. My first time trying to install something from GitHub, but couldn't find a simple solution after searching here and on google.

Seems that installing git again and manually delete the path and edit myself worked for that issue, but now i'm getting:.

Sharing Jupyter Notebooks using GitHub

And check out pip issue :. In my case the problem was the way I had the path to git defined in my path environment on windows. Learn more. Asked 2 years, 9 months ago. Active 2 years, 9 months ago. Viewed 5k times. You should consider upgrading via the 'python -m pip install --upgrade pip' command.

What am I doing wrong? ValientProcess ValientProcess 2 2 gold badges 10 10 silver badges 30 30 bronze badges. You don't have git installed on your system. Install git. I have git desktop for Windows installed, but still getting that error. Active Oldest Votes. And check out pip issue : In my case the problem was the way I had the path to git defined in my path environment on windows. Then try again. VonC VonC k gold badges silver badges bronze badges. Can you type git version from the command line?

ValientProcess OK. I have edited the answer to propose an alternative for you to test. Sign up or log in Sign up using Google. Sign up using Facebook. Sign up using Email and Password. Post as a guest Name. Email Required, but never shown. The Overflow Blog.

The Overflow How many jobs can be done at home? Featured on Meta. Community and Moderator guidelines for escalating issues via new response…. Feedback on Q2 Community Roadmap.Released: Mar 2, View statistics for this project via Libraries. Tags ipython, jupyter, widgets. Mar 2, Nov 12, Feb 6, Nov 9, Oct 31, Oct 29, Oct 27, Oct 17, Oct 3, Sep 28, Sep 20, Aug 28, Jul 29, Jul 22, Jul 8, Jul 6, Jul 3, Jun 17, After a lot of research on the internet, I found no practical tutorial explaining how to embed Jupyter Notebooks in Static Websites using only free technologies.

This is a step by step guide to embed Jupyter Notebooks in a static website.

jupyter voila github

There is also an official tutorial available in the docs. I really like using Jupyter Notebooks for my experiments and I also like to show them in this blog, which is a pure static website built with Pelican.

The problem emerged when I wanted to embed some interactive content from the notebook in the website, I thought this should have been solved long ago but it wasn't or at least it wasn't as Public as it should be. Having the possibility to embed Jupyter notebooks in a static website provides lots of advantages, just to mention a few:. In order to do this, I used a set of tools. This is my personal choice but I believed is appropriate, of course, if you have any suggestions, feel free to write a comment below.

I want to write an isolated notebook that the user could run via Binder 1I want to write a blog post about what I've done in that notebook 2 and in the post, I want to insert specific cells when appropriate 3.

Additionally, I want my experiments pieces the specific cells inserted to be sharable, meaning any could embed them easily in their website 4 and I also want to track how many times they were used and from which source 5. First thing first, you need a fully working notebook. It should run all cells without errors in your local machine. In order to take full advantage of this methodology make sure you use widgets such as IPython's to give control to the user.

Besides, this way, the reader doesn't have to know programming at all!

jupyter voila github

When you have that done, you have to identify the notebook dependencies. It could be either from Conda, pip, apt or anywhere else. The most common approach to work with Binder is a combination of environment. A more detailed explanation which many other ways can be found in the official docs.

Gists are like small repositories, they have a sort of version control called "Revisions" but there are no branches, they provide simple updates one after the other. They are especially useful for cases where a repository is too much and just a few files are needed. Here I will explain how to create a Gist in Github, in case you already know it, you can skip to the next sectionwhere I explain how to set the dependencies for Binder.

Now you are in the Gist creation Template, here you have to write the Gist Name, the filename of the first file, its contents and you can additionally add files if necessary with the button below.

When everything is set up, click in create public gist. Note: You can also create private gists for free but for NBInteract and thus this guide to work, the gist should be public. Once the gist is created, it should be tested with MyBinder. Note: The first time you launch could take several minutes because it's building a docker image, this process is repeated each time you change the Gist so it is a good idea to always run your gists on Binder after you made a change.

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If the build was successful, open the notebook and run all the cells, check for errors, fix them until none appear and then continue to the next step. This step might seem to be pretty easy but there are cases especially when doing interesting things that may require additional settings, for example, setting the FFMPEG dependency correctly for creating animations and videos. With this step completed, you can add a Binder Badge in your post directly to the notebook.

Although the main objective is to embed specific parts, it doesn't imply the user wouldn't want access to the whole notebook in a more familiar environment such as the one Binder Provides. This is the most important part and where NBInteract comes in. For all the previous steps we used online tools such as Github Gists and MyBinder.Whereas jupyter-server-proxy allows you to run an arbitrary web service within a Jupyter notebook environment which can also work inside a JupyterHub singleuser notebookmy jhsingle-native-proxy package runs entirely without a dependency on Jupyter notebook.

The is no notebook server started at all.

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More details, and examples for running e. Please let me know any thoughts if this is useful to you, or if you have questions about how to get this running. Do you have an example that can be launched on mybinder. But in the first instance it seems that between them repo2docker and BinderHub are installing notebook and running that!

Or anyone else please let me know! I think mybinder and repo2docker override the CMD in the Docker image. You might be able to get around this by figuring out what command repo2docker runs and overwrite that command with your own script in the image, e. I was confused why notebook was being installed in the image at all, but it turned out to be an obscure dependency via ipywidgets in streamlit the arbitrary web service I was using as an example.

Jupyter Notebook just relies on the? So it is public other than requiring the query token, i. This now works with mybinder. So the relevant line is actually from entrypoint. It will say that --server. BUT when JupyterHub attempts to run jupyter notebook, it appends a --port argument to the very end of the command it runs. Really jhsingle-native-proxy needs to pick that up as its own argument, but it appears to be intended for the underlying streamlit command.

Thus, this will work and be equivalent to the previous one above, but --port is allowed to come at the end and still be picked up by jhsingle-native-proxy rather than passed on to the underlying command:. This tells jhsingle-native-proxy that we want a destport ofand an incoming port of So requests to will be proxied to portand the process that we hope to receive those will be run as: streamlit hello --server.

Have you been able to try it with other examples than streamlit? Wondering if that would work with a voila standalone app as well.

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Yes, definitely! I have added a standalone Voila Dockerfile example which works as part of an authenticated JupyterHub:. There is a direct link to mybinder. It would make sense to use jhsingle-native-proxy within Binder IF it implemented the?

Voilà is now a Jupyter subproject

Maybe the Binder examples have taken us off track - the point of jhsingle-native-proxy is really the OAuth wrapper for use in authenticated JupyerHub environments. JupyterHub is now a provider of arbitrary, user selected from a predefined dropdown list containerised web apps to authed multiusers, not just notebook server fronted containers.

New package to run arbitrary web service in JupyterHub jhsingle-native-proxy JupyterHub. Thank you for your thoughts. This repo now works on mybinder. Great question! So the usual solution is a double dash to signify the end of arguments and start of the command: jhsingle-native-proxy --destport --port -- streamlit hello --server. Thanks danlester for sharing, this looks great! Please let me know your thoughts!

I guess this could also be running on Binder as well?The goal of the gallery is to provide inspiration to Jupyter users who want to convert their notebooks into web applications. Most of the examples rely on widget libraries such as ipywidgetsipyleafletipyvolumebqplot and ipympland showcase how to build complex web applications entirely based on notebooks. The landing page of the gallery lists all the available examples. Each entry contains can be used to launch the example and includes a button to view the source.

All the examples shown in the gallery come from the gallery. You can contribute a new example to the gallery by following these stepswhich consist in adding a new entry to the gallery. The gallery will pick up the new example shortly after it has been added. The voila-gallery organization on GitHub already contains a few examples that you can use as a starting point.

You could even run it on a private instance. If you have authored an interesting dashboard and would like to share it with the rest of the world, feel free to open a pull request to add it to the list of examples!

Sign in. Archive Events Jupyter Website. Jeremy Tuloup Follow. Jupyter Blog The Jupyter Blog. Thanks to Maarten Breddels. Data Science Jupyter Voila.

jupyter voila github

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Voilà is now a Jupyter subproject

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Georgiana Dolocan in Jupyter Blog. Min RK in Jupyter Blog. Discover Medium. Make Medium yours. Become a member. About Help Legal.For more info about the coronavirus, see cdc. With the world coming to a standstill, thousands losing their lives and economies under free fall. Under the lockdown, I decided to go through a few data repositories and started wrangling and plotting data. After a while, I decided to create a dashboard out of my jupyter notebook. I am going to walk you through the steps I undertook with code snippets:.

The data here gets updated every 24 hours from the official sources. Countries are in alphabetical order. We have the data from the 22nd Jan up till the date you accessed it on. From the column names, you can see that there is a need for cleaning them a bit to make further analysis easy to work with.

The next step then is to prepare the data. Firstly, it is always easy to work with column names that are in lowercase. Now, with all the columns in the right format, there is a bunch of stuff that we can do with them. Analyzing the data in alphabetical order is a bad idea for countries that are struck severely. Here, I added the ipywidget interact method to provide an option for choosing the number of worst-hit countries you want to look at.

We get a text box to enter the number of rows we want along with the highlighted columns:. That was displaying the data, now plot the data that we have using the Plotly library.

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We plot the same worst-hit countries along with a slider option to change the number of countries we want on display:. Plotly renders high-quality interactive charts, here is what the data looks like now:. We can also have bar plots using plotly to visualise all the different cases using this code snippet:.

This plot displays the worst affected countries in terms of deaths using bar plots:. We are going to write a function that takes the country as input and displays the confirmed and death cases for each day. This will help us visualize the chart and the pace with which the cases are increasing. Scatter function. You can find the code of this function on my GitHub repository.

The function is then added with an interactive text box which allows you to enter your choice of the country as shown below:. Folium is a python package that helps us visualize the python manipulated data on an interactive leaflet map. It provides a number of built-in tilesets to choose from. The quickstart examples are a great help to get started.

Now creating a Map class object by passing the starting coordinates as location argument, tiles that you want to choose and the zoom levels.

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We can use the folium.


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Jupyter voila github
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