Metadata-Version: 2.1
Name: ipylivebash
Version: 0.2.0a1
Summary: Run shell script in Jupyter with live output
Home-page: https://github.com/benlau/ipylivebash
Author: Ben lau
Author-email: xbenlau@gmail.com
License: BSD
Keywords: Jupyter,Widgets,IPython
Platform: Linux
Platform: Mac OS X
Platform: Windows
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Framework :: Jupyter
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: ipywidgets (>=7.0.0)
Provides-Extra: docs
Requires-Dist: jupyter-sphinx ; extra == 'docs'
Requires-Dist: nbsphinx ; extra == 'docs'
Requires-Dist: nbsphinx-link ; extra == 'docs'
Requires-Dist: pytest-check-links ; extra == 'docs'
Requires-Dist: pypandoc ; extra == 'docs'
Requires-Dist: recommonmark ; extra == 'docs'
Requires-Dist: sphinx (>=1.5) ; extra == 'docs'
Requires-Dist: sphinx-rtd-theme ; extra == 'docs'
Provides-Extra: examples
Provides-Extra: test
Requires-Dist: pytest (>=4.6) ; extra == 'test'
Requires-Dist: pytest-cov ; extra == 'test'
Requires-Dist: nbval ; extra == 'test'

# ipylivebash

ipylivebash is a library to run shell script in Jupyter with live output.
It is designed as a utility to use Jupyter as a DevOps management tool.

**Example**

```
%%livebash --save log.txt --save-timestamp

find .
```

Run `find .` and show the output in the Jupyter notebook and also save to log-${current_timestamp}.txt

```
%%livebash --ask-confirm --notify
set -e
deploy_script
```

Before running the `deploy_script` show a panel to ask for confirmation. Once it is finished, show a notification.

**Features**

1. Run shell script in Jupyter with live output
2. The output in the notebook cell is not saved in the notebook by default
3. Support to save the output to a file. If the file already exists, it will pick another name automatically.
4. Support to show a confirmation UI before executing the script
5. Support to send a notification when the script finishes.

**Usage**

```
usage: livebash [-h] [--save OUTPUT_FILE] [--save-timestamp]
                [--line-limit LINE_LIMIT] [--height HEIGHT] [--ask-confirm]
                [--notify] [--keep-cell-output]

optional arguments:
  -h, --help
  --save OUTPUT_FILE    Save output to a file
  --save-timestamp      Add timestamp to the output file name
  --line-limit LINE_LIMIT
                        Restrict the no. of lines to be shown
  --height HEIGHT       Set the height of the output cell
  --ask-confirm         Ask for confirmation before execution
  --notify              Send a notification when the script finished
  --keep-cell-output    Keep the cell output
```

## Options

**--save OUTPUT_FILE**

Save the output to a file. 

If the file name already exists, it will add a suffix to avoid overriding the original file.

**--save-timestamp**

Add timestamp to the output file name.

**--line-limit LINE_LIMIT**

If the no. of line output exceed the limit, it may be truncated. 
It will show the last 5 lines only.

**--height HEIGHT**

Set the height of the output cell

**--ask-confirm**
 
Ask for confirmation before execution

![ask_confirm.png (392×80)](https://raw.githubusercontent.com/benlau/ipylivebash/main/docs/img/ask_confirm.png)

**--notify**
  
Send a notification when the script finished

**--keep-cell-output**

Keep the cell output such that it could be saved together with the notebook.
It can't be used with other options like --line-limit.

## Installation

You can install using `pip`:

```bash
pip install ipylivebash
```

If you are using Jupyter Notebook 5.2 or earlier, you may also need to enable
the nbextension:
```bash
jupyter nbextension enable --py [--sys-prefix|--user|--system] ipylivebash
```

## Development Installation

Create a dev environment:
```bash
conda create -n ipylivebash-dev -c conda-forge nodejs yarn python jupyterlab
conda activate ipylivebash-dev
```

Install the python. This will also build the TS package.
```bash
pip install -e ".[test, examples]"
```

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 .
yarn run build
```

For classic notebook, you need to run:

```
jupyter nbextension install --sys-prefix --symlink --overwrite --py ipylivebash
jupyter nbextension enable --sys-prefix --py ipylivebash
```

Note that the `--symlink` flag doesn't work on Windows, so you will here have to run
the `install` command every time that you rebuild your extension. For certain installations
you might also need another flag instead of `--sys-prefix`, but we won't cover the meaning
of those flags here.

### How to see your changes
#### Typescript:
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
yarn 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.
