Metadata-Version: 2.1
Name: prolothar-common
Version: 5.9.10
Summary: algorithms for process mining and data mining on event sequences
Home-page: https://gitlab.dillinger.de/KI/DataScience/processmining/prolothar-common
Author: Boris Wiegand
Author-email: boris.wiegand@dillinger.biz
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Process Mining
Description-Content-Type: text/markdown

# Prolothar

Algorithms for data mining on sequential data like process logs

## Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

### Prerequisites

Python 3.7+

### Installing

```
python -m pip install
       -i http://nexus.int.shsservices.de/repository/ki-python-releases/simple
       --trusted-host nexus.int.shsservices.de prolothar-common
```

If pip is already configured to use the nexus repository:

```
pip install prolothar-common
```

## Running the tests

```
make test
```

## Deployment

When changes are pushed into the master branch, the project is bundled and
uploaded to our Nexus automatically.

A Docker-Image is also created and pushed into the Gitlab docker registry

## Versioning

We use [SemVer](http://semver.org/) for versioning.

## Authors

* **Boris Wiegand** - boris.wiegand@dillinger.biz

See also the list of [contributors](https://gitlab.dillinger.de/KI/DataScience/processmining/prolothar-common/-/graphs/master) who participated in this project.



