semvec/pypi-packages huggingface dataset:
qtile-protonvpn 1.0.1
QTile widget to display information about ProtonVPN connection
License: MIT

# QTile ProtonVPN Widget

It is a widget to display information about the ProtonVPN connection.

## Dependencies

* [ProtonVPN/linux-cli-community](https://github.com/ProtonVPN/linux-cli-community)
* [qtile/qtile](https://github.com/qtile/qtile)

## Installation

Clone the repository from GitHub and install the package.

```bash
git clone https://github.com/qkhronos/qtile-protonvpn.git
cd qtile-protonvpn
pip install .
```

You can also install it from PyPI using pip.

```bash
pip install qtile-protonvpn
```

## Usage

Edit your configuration file (usually in `~/.config/qtile/config.py`) and add on the top:

```python
from qtile_protonvpn import ProtonVpnStatus
```

Search for the `bar` inside the configuration file and add the method: `ProtonVpnStatus()`.

```python
screens = [
    Screen(
        bottom=bar.Bar(
            [
                ProtonVpnStatus(),
            ],
            24,
        ),
    ),
]
```

## Configuring

There is two format strings, when ProtonVPN is connected (`format_connected`) and when ProtonVPN is
disconnected (`format_disconnected`). To make a custom configuration you just have to pass one of the keys inside
brackets `{Key}`. For example, the default layout:

```python
ProtonVpnStatus(format_connected="ProtonVPN: {Status} ({Server})",
                format_disconnected="ProtonVPN: {Status}"),
```

* When connected: `ProtonVPN: Connected (US-FL#23)`.


* When disconnected: `ProtonVPN: Disconnected`.

For `format_disconnected` you can use the following keys:

| Key | Description |
| --- | --- |
| Status | Returns the value `Disconnected` |
| IP | Returns your real IP address |
| ISP | Returns your real ISP name |

For `format_connected` you can use the following keys:

| Key | Description |
| --- | --- |
| Status | Returns the value `Connected`. |
| Time | Returns the active time of the current connection. |
| IP | Returns the IP of the server you are connected to. |
| Server | Returns the server you are connected to. |
| Features | Returns the features that the server has. |
| Protocol | Returns the protocol you are using to connect. |
| Kill Switch | Returns `Disabled` or `Enabled`. |
| Country | Returns the country the server is hosted on. |
| City | Returns the city the server is hosted on. |
| Load | Returns the load of the server. |
| Received | Returns the total data you received in the current connection. |
| Sent | Returns the total data you sent in the current connection. |

## Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

## License

[MIT](https://choosealicense.com/licenses/mit/)
dendrogram-ts 0.1.2
Plotting time-series graphs in scipy's dendrogram
License: MIT
Keywords: dendrogram,agglomerative clustering,timeseries

Dendrogram Timeseries
=====================

Scipy's dendrogram for agglomerative clustering requires extensive customizations
to make it more informative. This package wraps scipy's dendrogram with two customizations:

    * Timeseries graph at the side
    * Distance labels and cluster split points
 

Installation
------------

.. code:: bash
    
    pip install dendrogram-ts

Examples
--------

Plot by Maximum Clusters
************************

.. code:: python

    from dendrogram_ts import maxclust_draw

    plt.style.use('seaborn-whitegrid')
    plt.figure(figsize=(8,5));

    maxclust_draw(df, 'ward', 'euclidean', max_cluster=10, ts_hspace=2)


.. figure:: https://github.com/mapattacker/dendrogram-ts/blob/master/images/dendrogram1.png?raw=true
    :width: 650px
    :align: center

Plot by Color Threshold
***********************

.. code:: python

    from dendrogram_ts import colorclust_draw
    import matplotlib as mpl

    mpl.rcParams['lines.linewidth'] = 1
    plt.style.use('seaborn-white')
    plt.figure(figsize=(12,10))

    colorclust_draw(df, method='ward', metric='euclidean', color_threshold=5200, ts_hspace=1)

.. figure:: https://github.com/mapattacker/dendrogram-ts/blob/master/images/dendrogram3.png?raw=true
    :width: 650px
    :align: center

Plot All Clusters
*****************

.. code:: python

    from dendrogram_ts import allclust_draw

    plt.style.use('seaborn-whitegrid')
    plt.figure(figsize=(12,10))

    allclust_draw(df, 'ward', 'euclidean', ts_hspace=5)

.. figure:: https://github.com/mapattacker/dendrogram-ts/blob/master/images/dendrogram2.png?raw=true
    :width: 650px
    :align: center