semvec/pypi-packages huggingface dataset:
lib-version-remla 0.0.9
A small package which returns its own version.
Requires Python: <4.0,>=3.11

# lib-version
This is a package that returns the version of itself. 

### Building the package locally
You need to have poetry installed before running this: ```pip install poetry```.
1. ```poetry install```
2. ```poetry shell```
3. ```poetry build```

#### Uploading to PyPi manually
This can be done after building the package locally. Please don't upload manually if not necessary, the GitHub workflow will take care of this. But if you need to do it manually, input this command. The API key is shared in the team channel.
1. ```python3 -m twine upload --repository pypi dist/*```  

### Updating the package via workflow
After pushing an update you can tag it with the following command to trigger the workflow.
1. ```git tag 0.0.1```, where 0.0.1 can be any version. This tags the latest commit. 
2. ```git push origin --tags ```

### Importing the package from PyPi
To use the package in your project you can install it from PyPi. 
PyPi link is: https://pypi.org/project/lib-version-remla/
1. Install with: ```pip install lib-version-remla```

### Using the functionality
```
from lib_version_remla import return_version
version = return_version.VersionUtil.get_version()
```
bec-widgets 0.52.1
BEC Widgets
Requires Python: >=3.10

# BEC Widgets

BEC Widgets is a GUI framework designed for interaction with [BEC (Beamline Experiment Control)](https://gitlab.psi.ch/bec/bec).
## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install BEC Widgets:

```bash
pip install bec_widgets
```

For development purposes, you can clone the repository and install the package locally in editable mode:

```bash
git clone https://gitlab.psi.ch/bec/bec-widgets
cd bec_widgets
pip install -e .[dev]
```

BEC Widgets currently supports both PyQt5 and PyQt6. By default, PyQt6 is installed.

To select a specific Python Qt distribution, install the package with an additional tag:

```bash
pip install bec_widgets[pyqt6]
```
or 

```bash
pip install bec_widgets[pyqt5]
```
## Documentation

Documentation of BEC Widgets can be found [here](https://bec-widgets.readthedocs.io/en/latest/). The documentation of the BEC can be found [here](https://beamline-experiment-control.readthedocs.io/en/latest/).

## Contributing

All commits should use the Angular commit scheme:

> #### <a name="commit-header"></a>Angular Commit Message Header
> 
> ```
> <type>(<scope>): <short summary>
>   │       │             │
>   │       │             └─⫸ Summary in present tense. Not capitalized. No period at the end.
>   │       │
>   │       └─⫸ Commit Scope: animations|bazel|benchpress|common|compiler|compiler-cli|core|
>   │                          elements|forms|http|language-service|localize|platform-browser|
>   │                          platform-browser-dynamic|platform-server|router|service-worker|
>   │                          upgrade|zone.js|packaging|changelog|docs-infra|migrations|ngcc|ve|
>   │                          devtools
>   │
>   └─⫸ Commit Type: build|ci|docs|feat|fix|perf|refactor|test
> ```
> 
> The `<type>` and `<summary>` fields are mandatory, the `(<scope>)` field is optional.

> ##### Type
> 
> Must be one of the following:
> 
> * **build**: Changes that affect the build system or external dependencies (example scopes: gulp, broccoli, npm)
> * **ci**: Changes to our CI configuration files and scripts (examples: CircleCi, SauceLabs)
> * **docs**: Documentation only changes
> * **feat**: A new feature
> * **fix**: A bug fix
> * **perf**: A code change that improves performance
> * **refactor**: A code change that neither fixes a bug nor adds a feature
> * **test**: Adding missing tests or correcting existing tests

## License

[BSD-3-Clause](https://choosealicense.com/licenses/bsd-3-clause/)
kid-ppg 0.0.4
A library for performing probabilistic heart rate extraction from photoplehysmography signals.
Requires Python: ==3.10.8

# KID-PPG: Knowledge-Informed Deep Learning for Extracting Heart Rate from Photoplethysmography Signals 

KID-PPG is the first ever publicly available pre-trained deep learning model for PPG Heart Rate inference, proposed [here](https://infoscience.epfl.ch/record/310896?ln=en&v=pdf).

# Installation
KID-PPG is readily available in pip. 

### Install from pip
Install KID-PPG from pip \
`pip install kid-ppg`

### Install from source
Clone this directory \
`git clone https://github.com/esl-epfl/KID-PPG.git`

Install the cloned repository \
`pip install ./KID-PPG`

# Usage

For an introductory demo on how to use KID-PPG for heart rate extraction check this [Google Colab Demo](https://colab.research.google.com/drive/1I7lP_elVuzf3sn2Tlm0QsgarUR0_9z-l?usp=share_link). The ```matplotlib``` python package is
required to run the demo.

# Reference

Please use the following Bibtext entry to cite KID-PPG.

```
@article{kechris2024kid,
  title={KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch},
  author={Kechris, Christodoulos and Dan, Jonathan and Miranda Calero, Jos{\'e} Angel and Atienza Alonso, David},
  year={2024}
}
```