semvec/pypi-packages huggingface dataset:
Genetic-Algorithm-VEDA 0.0.3
Algoritmo Genético para estudo da evolução de circuitos lógicos combinacionais na presença de falhas.
License: MIT
Keywords: Genetic Algorithm

Algoritmo GenÃ©tico para estudo da evoluÃ§Ã£o de circuitos lÃ³gicos combinacionais na presenÃ§a de falhas.
myslides 0.0.5
A tool for generating slides from markdown files using different backends.
License: MIT
Requires Python: >=3.8,<4.0

# Description

`mdSlides` is a small utility for creating slideshows from markdown files. It is a wrapper around other tools
that actually generate the slides (currently only Pandoc) and handles setting up and passing the correct
command options to each tool.

Given a small Pandoc markdown file named simple.md,
```markdown
---
title  : Example Presentation
---

# First Slide

Text

# Second Slide

$\nabla \cdot \vec{E} = \frac{\rho}{\epsilon_0}$
```
and running `mdSlides` on it
```bash
$ mdSlides simple.md
```
will produce a directory named `simple` that contains a file named `index.html`. You can open the file
in a web browser to start the slide show.

`mdSlides` will also copy files that are needed for the slideshow, for example css files, images, etc, and
configure the slideshow to use the local files so that you can copy the directory to another computer (like
a web server) and it will still work.

Multiple "engines" are supported. The default engine uses [Pandoc](https://pandoc.org/) to output
a [slidy](https://github.com/slideshow-templates/slideshow-slidy) presentation. To see a list of
supported engines, run
```
$ mdSlides --list-engines
```
Only a few engines are currently supported, but others will be added in the future.

## Installing

You can install mdSlides with `pip`

```
pip install mdSlides
```
zema-emc-annotated 0.7.1
API to the annotated ZeMA dataset about an electro-mechanical cylinder
License: MIT
Requires Python: >=3.10,<4.0
Keywords: FAIR data,measurement uncertainty

# zema_emc_annotated

[![pipeline status](https://gitlab1.ptb.de/m4d/zema_emc_annotated/badges/main/pipeline.svg)](https://gitlab1.ptb.de/m4d/zema_emc_annotated/-/commits/main)
[![Documentation Status](https://readthedocs.org/projects/zema-emc-annotated/badge/?version=v0.7.1)](https://zema-emc-annotated.readthedocs.io/en/v0.7.1/)
[![codecov](https://codecov.io/gh/PTB-M4D/zema_emc_annotated/branch/main/graph/badge.svg?token=HQZE3FXL7N)](https://app.codecov.io/gh/PTB-M4D/zema_emc_annotated?search=&displayType=list&trend=7%20days)
[![Latest Release](https://img.shields.io/github/v/release/PTB-M4D/zema_emc_annotated?label=Latest%20Release)](https://github.com/PTB-M4D/zema_emc_annotated/releases/latest)
[![DOI](https://zenodo.org/badge/591514193.svg)](https://doi.org/10.5281/zenodo.7556142)

This software provides a convenient API to access the [annotated ZeMA dataset about 
remaining useful life of an electro-mechanical cylinder on
Zenodo](https://doi.org/10.5281/zenodo.5185953). The code was written for _Python 3.10_.

## Getting started

The [INSTALL guide](INSTALL.md) assists in installing the required packages. 
Afterwards please visit our
[example page](https://zema-emc-annotated.readthedocs.io/en/latest/examples.html).

## Documentation

The documentation can be found on
[ReadTheDocs](https://zema-emc-annotated.readthedocs.io/en/v0.7.1/).

## Disclaimer

This software is developed at Physikalisch-Technische Bundesanstalt (PTB). The software
is made available "as is" free of cost. PTB assumes no responsibility whatsoever for
its use by other parties, and makes no guarantees, expressed or implied, about its
quality, reliability, safety, suitability or any other characteristic. In no event
will PTB be liable for any direct, indirect or consequential damage arising in
connection with the use of this software.

## License

zema_emc_annotated is distributed under the [MIT
license](https://github.com/PTB-M4D/zema_emc_annotated/blob/main/LICENSE).
geostream 0.0.1
Python tool to interact with OGC APIs with ease.
License: MIT
Requires Python: >=3.7

# Geostream

**Geostream** is a Python tool to interact with OGC APIs with ease and download geospatial data to Geopandas GeoDataFrames. 

**Status**: Currently only works with WFS API and is very experimental by nature. Use at own risk. 

## Installation

`geostream` is available via PyPi and can be installed with:

- `pip install geostream`

## Basic usage

```python
from geostream import WFS

# Endpoint for WFS API of the City of Helsinki
endpoint = "https://kartta.hel.fi/ws/geoserver/avoindata/wfs"

# Initialize WFS reader 
# Note: API version can vary between data providers (by default 1.0.0 is used) 
wfs = WFS(endpoint, version="2.0.0")

# See all available layers
wfs.get_layers()

# Store the id of the first layer
first_layer = wfs.get_layers()[0]

# Find info for specific layer
wfs.get_layer_info(first_layer)

# Download a GeoDataFrame with Helsinki as the extent
helsinki_gdf = wfs.get_gdf_from_place("Helsinki")

# Download the data into GeoDataFrame from the Helsinki Region
data = wfs.load_wfs(layer_id=first_layer, bounding_box=helsinki_gdf)
```