declarativewidgets | Jupyter Declarative Widget Extension | Code Editor library

by jupyter-attic HTML Version: Current License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | declarativewidgets Summary

declarativewidgets is a HTML library typically used in Editor, Code Editor, Jupyter applications. declarativewidgets has no bugs, it has no vulnerabilities and it has low support. However declarativewidgets has a Non-SPDX License. You can download it from GitHub.

[RETIRED] Jupyter Declarative Widget Extension

Support

Quality

Security

License

Reuse

Support

declarativewidgets has a low active ecosystem.

It has 118 star(s) with 39 fork(s). There are 24 watchers for this library.

It had no major release in the last 6 months.

There are 38 open issues and 240 have been closed. On average issues are closed in 32 days. There are 7 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of declarativewidgets is current.

Quality

declarativewidgets has 0 bugs and 0 code smells.

Security

declarativewidgets has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

declarativewidgets code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

declarativewidgets has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

declarativewidgets releases are not available. You will need to build from source code and install.

Installation instructions, examples and code snippets are available.

It has 14830 lines of code, 310 functions and 147 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of declarativewidgets

Get all kandi verified functions for this library.

declarativewidgets Key Features

No Key Features are available at this moment for declarativewidgets.

declarativewidgets Examples and Code Snippets

No Code Snippets are available at this moment for declarativewidgets.

Community Discussions

Trending Discussions on declarativewidgets

Really confused with Jupyter Notebook, Lab, extensions, and ipywidgets

QUESTION

Really confused with Jupyter Notebook, Lab, extensions, and ipywidgets

Asked 2017-Dec-15 at 14:25

I want to create an interactive JupyterLab Notebook application, and I need to create a series of custom Widgets. So I started looking into this matter, and the more I look the more confused I become. To make things simple I will ask a bunch of simple questions:

One of the most common ways to use widgets on Jupyter Notebooks is to use the ipywidgets library. Right?
Unlike the classic Notebook, the Notebook of JupyterLab cannot render JavaScript directly. As a result, the tutorials about custom widget creation in the ipywidgets docs are impossible to run on JupyterLab. Right?
If one wants to run JavaScript on the Notebook of JupyterLab she or he will have to do it through an extension. In case of ipywidgets, one will have to install @jupyter-widgets/jupyterlab-manager. Right?
If you want to write a custom widget using the ipywidgets library, there are two GitHub projects that you could use as a starting point: widget-cookiecutter and widget-ts-cookiecutter. To my understanding, the former is based on JavaScript while the latter on TypeScript. Also, the first appears to be inactive for quite some type, while the second is more active. Is the JupyterWidgets team planning to focus on TypeScript? Which one should I follow?
The cookiecutter projects do not really have a documentation. I am really confused and struggling to understand their code. Sure, I can copy-paste them and start messing around until I figure out how the whole thing works and what are the "hooks" or "entry points" in the code, but I would really appreciate if someone could give me some additional pointers.
Is the JupyterWidgets an "official" project of the Jupyter project? Given the very small number of members in the project I wonder how safe is to base my work on ipywidgets. Keep in mind that the "DeclarativeWidgets" project has abandoned long time ago.
Are there other libraries that implement more widgets than the ones found in ipywidgets and also run on JupyterLab?
I want to create a Web application for server-side data processing. My initial goal was to create an app/service that does not expect from the user to do any coding, and performs everything through the use of html/JavaScript widgets. That could be implemented using an Angular/React front-end and a Python/Django/Flask back-end. However, later on, I realised that there are cases where the user may want to do some additional custom/arbitrary processing on the server. This is why I considered JupyterLab. I wonder if it would be best and if it is possible to just create, for example, a normal Angular/Python font/back-end, and somehow wrap this up in a JupyterLab extension that will provide a mechanism to access the data from this app/service and bring it to the notebook for further processing.

Thanks in advance

...

ANSWER

Answered 2017-Dec-15 at 10:40

First of all, remember that JupyterLab is not stable yet and internal API are still changing quite a bit. The biggest part of your frustration is trying to find information about a project that is changing every week (should stabilize early 2018 for reference).

This lead to minimal effort writing documentation and example for users, as anyway the documents will be wrong a week later. So your confusion and lack of activity is normal for now.

Once Lab stabilizes and the IPywidget team start porting everything you should see an improvement.

Source https://stackoverflow.com/questions/47826117

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install declarativewidgets

On all Jupyter versions, you will need to restart your notebook server if it was running during the enable/activate step. Also, note that you can run jupyter --paths to get a sense of where the extension files will be installed.
Run make sdist to create a pip installable archive file in the dist directory. To test the package, run 'make server'. This command will run a docker container and pip install the package. It is useful to validate the packaging and installation. You should be able to install that tarball using pip anywhere you please with one caveat: the setup.py assumes you are installing to profile_default. There's no easy way to determine that you want to install against a different user at pip install time.