jppype


Namejppype JSON
Version 0.1.1.1 PyPI version JSON
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home_page
SummaryJupyterLab extension adding data visualisation widgets.
upload_time2023-05-24 20:00:58
maintainer
docs_urlNone
author
requires_python>=3.10
licenseMIT License Copyright (c) 2023 Gabriel Lepetit-Aimon Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
keywords ipython jupyter jupyterlab widgets
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requirements No requirements were recorded.
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coveralls test coverage No coveralls.
            # Jupyter ProtoPype: jppype
[![PyPI version](https://badge.fury.io/py/jppype.svg)](https://badge.fury.io/py/jppype)

Jupyter extensions adding ipywidgets specialized for data-view. It is designed as a frontend for ProtoPype (to be released) but can be used as a standalone.

The widgets work both with Jupyter Notebook and Jupyter Lab.

## Installation

To install use pip:

```bash
pip install jppype
```

## Usage
Import jppype in your notebook and use the widgets:
```python
import jppype as jpp
```

### 2D image viewer
```python
viewer = jpp.View2D()

# Supported image formats: numpy array, torch tensor
image = np.random.rand(100, 100) 
viewer.add_image(image)
viewer
```

## Features coming...

- __Widgets__
  - [x] 2D image viewer
    - [x] Color images layer
    - [x] Label layer
    - [x] Graph layer
    - [ ] Vector Field layer
  - [ ] Table viewer


- __Python interactivity__
  - [x] Add/Update/Remove layers
  - [x] Callback on click
  - [ ] Async request of user selection (point, area, node, edge...) 

## Development Installation

Pull the latest version of the repository
```bash
git clone https://github.com/gabriel-lepetitaimon/jppype.git
cd jppype
````

For a development installation (requires [Node.js](https://nodejs.org) and [Yarn version 1](https://classic.yarnpkg.com/)):
```bash
conda create -n jppype python=3.10
conda install -c conda-forge yarn nodejs
```

Download the npm dependencies:
```bash
cd ts-src
npm install
cd ...
```

Upgrade jupyter-lab to version 4.0.0 if necessary:
```bash
pip install -U jupyterlab
```

Install the python package and the extensions in development mode (this stage may take a while as it will build the jupyterlab extension):
```bash
pip install -e .[dev]
jupyter nbextension install --py --symlink --overwrite --sys-prefix jppype
jupyter nbextension enable --py --sys-prefix jppype
```
If you which to develop for JupyterLab, also run the command:
```bash
jupyter labextension develop --overwrite jppype
```

Then you need to rebuild the JS when you make a code change:
```bash
cd ts-src
jlpm clean
jlpm build
```
or automatically rebuild when a file changes:
```bash
cd ts-src
npm watch
```

You then need to refresh the JupyterLab page when your javascript changes.

            

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