semvec/pypi-packages huggingface dataset:
pymemuc 0.6.0
A Python API for MEmu Android Emulator.
License: MIT
Requires Python: <4.0,>=3.9
Keywords: memu, memuc, android-emulator, api

# pymemuc

[![GitHub](https://img.shields.io/github/license/pyclashbot/pymemuc)](LICENSE) [![Documentation Status](https://readthedocs.org/projects/pymemuc/badge/?version=latest)][full_doc] [![PyPI](https://img.shields.io/pypi/v/pymemuc) ![PyPI - Downloads](https://img.shields.io/pypi/dm/pymemuc)][pypi_link] [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/pymemuc)][python_link] [![CodeFactor](https://www.codefactor.io/repository/github/pyclashbot/pymemuc/badge)][codefactor_link]

A Python API for MEmu Android Emulator.
The API exposes [MEmu Command (MEMUC)][memuc_docs] functionality in Python.

Allows for easy interaction with MEmu VMs, including VM image management, VM control, running VM commands and ADB interaction.

## Installation

```bash
pip install pymemuc
```

## Example usage

```python
# import the PyMemuc class
from pymemuc import PyMemuc

# create a PyMemuc instance, doing so will automatically link to the MEMUC executable
memuc = PyMemuc()

# create a new vm, saving the index
index = memuc.create_vm()

# list out all vms
print(memuc.list_vm_info())

# start the vm
memuc.start_vm(index)

# stop the vm
memuc.stop_vm(index)
```

See [the demo notebook][demo_notebook] for more examples.

## Documentation

See the [API documentation][full_doc].

[python_link]: https://www.python.org/
[pypi_link]: https://pypi.org/project/pymemuc/
[codefactor_link]: https://www.codefactor.io/repository/github/pyclashbot/pymemuc
[memuc_docs]: https://www.memuplay.com/blog/memucommand-reference-manual.html
[demo_notebook]: demo/demo.ipynb
[full_doc]: https://pymemuc.pyclashbot.app/
tcra 1.1.3
A Python package for estimating cyclone hazard parameters and calculating wind speeds at structure sites.
License: MIT
Requires Python: >=3.6

# tcra

Tropical Cyclone Risk Analysis [tcra] is a Python package that allows for the development of scenario-based tropical cyclone risk analysis of buildings and Electrical Power Network (EPN). This tool performs scenario-hazard analysis based on historical or simulated cyclone tracks, fragility-based damage analysis, damage ratio analysis, loss estimation, recovery simulation of damaged structures, and social impact assessments on the community. It also enables decision-makers to make rehabilitation decisions and perform rehabilitation scenario analysis.

# Libraries
Pandas, Numpy, Matplotlib, Folium

## Installation

```bash
pip install tcra