semvec/pypi-packages huggingface dataset:
robotframework-androiduiautomation 0.2.0
Robot Framework library for Android automation using uiautomator2
Requires Python: >=3.8

# android_ui_automation

Python library for Android UI automation using **uiautomator2**, fully compatible with **Robot Framework**.

## Installation

Install from PyPI:

```bash
pip install robotframework-androiduiautomation
```

Or install locally for development:

```bash
git clone https://github.com/ValterIversen/android_ui_automation
cd android_ui_automation
pip install -e .
```

`uiautomator2` will be installed automatically as a dependency.

---

## Usage in Robot Framework

### ***Settings***

```robot
*** Settings ***
Library    AndroidUiAutomation
```

### ***Variables***

```robot
*** Variables ***
${DEVICE}    emulator-5554
${APP}       com.example.app
```

### ***Test Case Example***

```robot
*** Test Cases ***
Open App And Click Button
    [Documentation]    Example test to open an app, click a button, type keys, and use system buttons
    Connect Device    ${DEVICE}
    Open App    ${APP}
    Type Keys    INPUT
    Click By Text    Confirm
    Press Back Button
    Close App    ${APP}
```

---

## Features

- Connect to Android devices/emulators  
- Launch and close apps  
- Wait for elements (Text or XPath) to appear/disappear  
- Click by text or XPath  
- Get and set text  
- Type keys  
- Press Android system buttons (Home, Back, Menu)  
- Fully compatible with Robot Framework keyword-style usage  
- All public Python methods automatically become RF keywords  

---

## Notes

- System buttons have friendly aliases:  
  - `Press Home Button`  
  - `Press Back Button`  
  - `Press Menu Button`  

---

# Example Project (Base Template)

To see a **complete working example** using this library, check out the base project:

**https://github.com/ValterIversen/RobotFramework-UiAutomatorLibrary**
scpviz 0.5.2a0
A package to visualize single cell proteomics (and more to come!) data
Requires Python: >=3.8

# scpviz
<img src="https://raw.githubusercontent.com/gnaprs/scpviz/refs/heads/main/docs/assets/300ppi/logo_white_label@300x.png"
 align="right" width="256"/>
 [![DOI](https://zenodo.org/badge/762480088.svg)](https://doi.org/10.5281/zenodo.17362532)

**Build & Tests:**  
[![Build Status](https://github.com/gnaprs/scpviz/actions/workflows/python-package.yml/badge.svg)](https://github.com/gnaprs/scpviz/actions/workflows/python-package.yml)
[![codecov](https://codecov.io/gh/gnaprs/scpviz/branch/main/graph/badge.svg)](https://codecov.io/gh/gnaprs/scpviz)

**Documentation:**  
[![Docs CI](https://github.com/gnaprs/scpviz/actions/workflows/ci.yml/badge.svg)](https://github.com/gnaprs/scpviz/actions/workflows/ci.yml)
[![Docs](https://img.shields.io/badge/docs-v0.5.2a-brightgreen.svg)](https://gnaprs.github.io/scpviz)


**scpviz** is a Python package for single-cell and spatial proteomics data analysis, built around a custom `pAnnData` object.  
It extends the [AnnData](https://anndata.readthedocs.io/) ecosystem with proteomics-specific functionality, enabling seamless integration of proteins, peptides, and relational data.

* **Documentation**: https://gnaprs.github.io/scpviz/
* **Python Package Index (PyPI)**: https://pypi.org/project/scpviz/

## Getting started
### Installation

`scpviz` requires Python 3.8 or later. It is distributed as a Python package and can be installed with `pip`.

    python3 -m pip install scpviz

This will install all required dependencies, including `scanpy`, `anndata`, `pandas`, and common plotting libraries.

For the most up-to-date version of scpviz, clone the repository and
install the package using pip:

    conda create -n scpviz python=3.8 numpy pandas pip
    conda activate scpviz
    pip install git+https://github.com/gnaprs/scpviz.git@development

### Quickstart

Check out the [quickstart](https://gnaprs.github.io/scpviz/tutorials/quickstart/) guide for a run through import, basic preprocessing and quick visualization

### In-depth Tutorials
For more in-depth guides on importing, filtering, plotting, and running enrichment, see the [tutorials](https://gnaprs.github.io/scpviz/tutorials/).

### API Reference

Full function documentation for the `pAnnData` class and utility modules can be found on our [documentation page](https://gnaprs.github.io/scpviz/reference/).

## Contributing

If you'll like to contribute to `scpviz`, please see the [contributing guidelines](https://gnaprs.github.io/scpviz/dev/contributing/). We welcome contributions from the community to help improve, expand, and document the functionality of scpviz.

## License
`scpviz` was created by Marion Pang. It is licensed under the terms of the MIT license.
django-include-bootstrap 5.3.8.1
Includes bootstrap css/js and a default template to make it easier to use Bootstrap with Django
Requires Python: >=3.9
Keywords: bootstrap, django

# Minimal Django Bootstrap5


Includes the Bootstrap javascript and css files, along with a minimal bootstrap template to make it easier to use bootstrap with Django.


Defined blocks

- title
- styles
- head
- container
- content
- subnav
- footer
- javascript

Defined includes

- head.inc.html
- navbar.inc.html
- messages.inc.html
- footer.inc.html