Metadata-Version: 2.1
Name: diginlineprofiler
Version: 0.1.1
Summary: Inline data profiles for pandas dataframes in jupyter
Home-page: https://github.com/cmudig/ProfileInline
Author: Will Epperson
Author-email: willepp@cmu.edu
License: BSD-3-Clause
Keywords: Jupyter,JupyterLab,JupyterLab3
Platform: Linux
Platform: Mac OS X
Platform: Windows
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Framework :: Jupyter
Classifier: Framework :: Jupyter :: JupyterLab
Classifier: Framework :: Jupyter :: JupyterLab :: 3
Classifier: Framework :: Jupyter :: JupyterLab :: Extensions
Classifier: Framework :: Jupyter :: JupyterLab :: Extensions :: Prebuilt
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Other Audience
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Visualization
Requires-Python: >=3.7
Description-Content-Type: text/markdown

# ProfileInline

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Inline data profiles

## Installation

You can install using `pip`:

```bash
pip install diginlineprofiler
```

## Development Installation

Create a dev environment:

```bash
conda create -n diginlineprofiler-dev -c conda-forge nodejs yarn python jupyterlab jupyter-packaging
conda activate diginlineprofiler-dev
```

Install the python. This will also build the TS package.

```bash
pip install -e .
```

When developing your extensions, you need to manually enable your extensions with the
notebook / lab frontend. For lab, this is done by the command:

```
jupyter labextension develop --overwrite .
npm run build
```

### How to see your changes

#### Jupyter Lab:

If you use JupyterLab to develop then you can watch the source directory and run JupyterLab at the same time in different
terminals to watch for changes in the extension's source and automatically rebuild the widget.

```bash
# Watch the source directory in one terminal, automatically rebuilding when needed
npm run watch
# Run JupyterLab in another terminal
jupyter lab
```

After a change wait for the build to finish and then refresh your browser and the changes should take effect.

#### Python:

If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.
