semvec/pypi-packages huggingface dataset:
nicostick 0.1.0
Python package for interfacing with the Nicolaudie Stick3-DE DMX controller over Ethernet
License: MIT
Requires Python: <3.13,>=3.10
Keywords: nicolaudie, stick3, dmx, lighting, controller

# nicostick
Python package for interfacing with the Nicolaudie Stick3-DE DMX controller over Ethernet.
Other Nicolaudie controllers ( Stick5/Siudi10 ) may work, but have not been tested.
electricity-usage 0.1.1
The electricity_usage package provides a scheduler which will kick off processes only when there is a surplus in local energy production.
License: MIT
Requires Python: >=3.8

# Welcome to electricity_usage

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![GitHub Workflow Status](https://img.shields.io/github/actions/workflow/status/weyandtim/electricity_usage/ci.yml?branch=main)](https://github.com/weyandtim/electricity_usage/actions/workflows/ci.yml)
[![Documentation Status](https://readthedocs.org/projects/electricity_usage/badge/)](https://electricity_usage.readthedocs.io/)
[![codecov](https://codecov.io/gh/weyandtim/electricity_usage/branch/main/graph/badge.svg)](https://codecov.io/gh/weyandtim/electricity_usage)

The electricity_usage package provides a scheduler which will kick off processes only when there is a surplus in local energy production.
For more information see the [usage](usage.html) documentation.

## Installation

The Python package `electricity_usage` can be installed by cloning the git repository and installing it using pip install.

```
pip install electricity_usage
```
To fully utilize this package, you also need a subscription to Electricity Maps, available here `<https://api-portal.electricitymaps.com/>`.  
Upon subscription, you'll receive an authentication token. This token is used to access additional electricity production and consumption data for specific locations from Electricity Maps.  
We incorporate the token using an optional parameter `--em_auth_token`, in our `start` command.  
Please note that the majority of locations do not require an authentication token.  
More information about Electricity Maps can be found in :ref:`api-ref`.

<!-- @Tim kann sein dass das nicht reicht, deine Entscheidung -->


## Development installation

If you want to contribute to the development of `electricity_usage`, we recommend
the following editable installation from this repository:

```
git clone https://github.com/weyandtim/electricity_usage
cd electricity_usage
python -m pip install --editable .[tests]
```

Having done so, the test suite can be run using `pytest`:

```
python -m pytest
```


## Contributing

This project was done as a software practical by Tim Weyand and Nemo Glade, under supervision of Dominic Kempf.

If you wish to contribute to electricity\_usage open an issue in the issue tracker of the [GitHub project](https://github.com/weyandtim/electricity_usage/issues).


## Acknowledgments

This repository was set up using the [SSC Cookiecutter for Python Packages](https://github.com/ssciwr/cookiecutter-python-package).
The project relies on data from [Electricity Maps](https://github.com/electricitymaps/electricitymaps-contrib).
kgheartbeat 0.2.6
Library that allows to perform Knowledge Graph (Linked Open Data) quality analysis.
License: MIT

# KGHeartBeat API

1. [What is KGHeartBeat API](#what-is-kgheartbeat-api)
2. [Installation](#installation)
3. [Examples](#examples)  

# What is KGHeartBeat API
Library that allows you to perform Knowledge Graph (Linked Open Data) quality analysis.

The granularity with which KG quality can be measured is at the metric level, meaning that it is possible to combine the calculation of multiple metrics to obtain KG quality for a dimension. The [examples](#examples) section shows how you can calculate the quality of different dimensions combining together the calculation of different metrics.

For documentation on the library implementation visit here: [https://gabrielet0.github.io/KGHeartbeat-API/reference/](https://gabrielet0.github.io/KGHeartbeat-API/reference/)

For information on which metrics are supported and how they are calculated visit here: [https://isislab-unisa.github.io/KGHeartbeat/](https://isislab-unisa.github.io/KGHeartbeat/)
# Installation
```
pip install kgheartbeat
```

# Examples
1. [Calculate the Availability dimension](#calculate-the-availability-dimension)
2. [Calculate the Licensing dimension](#calculate-the-licensing-dimension)
3. [Calcuate the Versatility dimension](#calcuate-the-versatility-dimension)

### Calculate the *Availability* dimension
```Python
from kgheartbeat import KnowledgeGraph

# Instanziate a KnowledgeGraph class, passing the id of the kg to be analyzed
kg = KnowledgeGraph('dbpedia')

# Check the SPARQL endpoint availability
sparqlAv = kg.checkEndpointAv()
# Check if the links for download the dataset is up
checkDump = kg.checkDownload()
# Check if there are any inactive links
inactiveLks = kg.checkInactiveLinks()
# Calculate the URI's deferenceability (based on 5000 randomly recoverable uri). THIS COULD TAKE TIME, DEPENDS ON THE SPEED OF THE ENDPOINT (~45 min. for DBpedia)
uriDef = kg.getURIsDef()

#Print all the results
print(f"SPARQL endpoint availability: {sparqlAv}\n \
       RDF dump link availability: {checkDump}\n\
       Any inactive links: {inactiveLks}\n\
       URIs deferenceability: {uriDef}")
```

### Calculate the *Licensing* dimension

```Python
from kgheartbeat import KnowledgeGraph

# Instanziate a KnowledgeGraph class, passing the id of the kg to be analyzed
kg = KnowledgeGraph('taxref-ld')

#Search for the machine-redeable license
mr_license = kg.getLicenseMR()
#Search for a human-redeable license
hr_license = kg.getLicenseHR()

print(f"Machine redeable license: {mr_license}\nHuman-redeable license: {hr_license}")
```

### Calcuate the *Versatility* dimension
```Python
# Instanziate a KnowledgeGraph class, passing the id of the kg to be analyzed
kg = KnowledgeGraph('bncf-ns')

#Find the different serialization formats available (e.g. .rdf, .n3, .xml)
formats = kg.getSerializationFormat()
#Get languages if is indicated
languages = kg.getLanguages()
#get all the links to access the KG
link_access = kg.getAccessAtKG()

print(f"Serialization formats: {formats}\nLanguages: {languages}\n Link to access the KG:{link_access}\n")
```