semvec/pypi-packages huggingface dataset:
sophoscentral 1.1.1
Tosch Automatisering Sophos Central libary
Requires Python: >=3.8

# Introduction 
TODO: Give a short introduction of your project. Let this section explain the objectives or the motivation behind this project. 

# Getting Started
TODO: Guide users through getting your code up and running on their own system. In this section you can talk about:
1.	Installation process
2.	Software dependencies
3.	Latest releases
4.	API references

# Build and Test
TODO: Describe and show how to build your code and run the tests. 

# Contribute
TODO: Explain how other users and developers can contribute to make your code better. 

If you want to learn more about creating good readme files then refer the following [guidelines](https://docs.microsoft.com/en-us/azure/devops/repos/git/create-a-readme?view=azure-devops). You can also seek inspiration from the below readme files:
- [ASP.NET Core](https://github.com/aspnet/Home)
- [Visual Studio Code](https://github.com/Microsoft/vscode)
- [Chakra Core](https://github.com/Microsoft/ChakraCore)
qalita 2.11.0
QALITA Platform Command Line Interface
Requires Python: >=3.10

# QALITA Command Line Interface (CLI)

<div style="text-align:center;">
<img width="250px" height="auto" src="https://app.platform.qalita.io/logo.svg" style="max-width:250px;"/>
</div>

QALITA Command Line Interface (CLI) is a tool intended to be used by Data Engineers who setup's QALITA Platform's workers, sources and assets.

It gives easy to use command to help them make an up & running qalita platform's environment in no time.

Find the full documentation [in the online documentation](https://doc.qalita.io/docs/cli)
shmarql 0.68
A Linked Data publishing platform for semantic web professionals in a hurry.
Requires Python: >=3.10
Keywords: SPARQL, search, RDF, Linked Data

# SHMARQL

A Linked Data publishing platform for semantic web professionals in a hurry. Make compelling queries and documentation of your RDF data, using an open-source, simple platform.

Documentation here: https://shmarql.com/

## TL;DR

SHMARQL also has a built-in triplestore which you can use to share your RDF data over a SPARQL interface. To use it, you need to specify the path from which to load the datafiles at startup, using an environment variable: `DATA_LOAD_PATHS`.
This also means that the path in which the data is stored is "visible" to the docker container via for example a mounted volume.

Here is an example, where you have some .ttl files stored in your current directory:

```shell
docker run --rm -p 8000:8000 -it -v $(pwd):/data -e DATA_LOAD_PATHS=/data  ghcr.io/epoz/shmarql:latest
```

This will load all .ttl files found in the specified directory, and make it available under a /sparql endpoint, eg. http://localhost:8000/sparql

## Development instructions

If you would like to run and modify the code in this repo, there is a [Dockerfile](Dockerfile) which includes the necessary versions of the required libraries.

First, build the Docker image like so:

```shell
docker build -t shmarql .
```

Now you can run a local copy with:

```shell
docker run -it --rm -p 8000:8000 shmarql
```