semvec/pypi-packages huggingface dataset:
wagtail-events 0.4.0
Event pages for Wagtail
License: MIT
Keywords: wagtail,django,events

# Wagtail Events [![Build Status](https://travis-ci.com/thclark/wagtail_events.svg?branch=master)](https://travis-ci.com/thclark/wagtail_events)

Events calendar management for wagtail, with tools for filtering by date.

This project is a hard fork of [omni-wagtail-events](http://github.com/omni-digital-omni-wagtail-events), and we owe a
debt of gratitude to those folks for getting us started. So why did I hard-fork (duplicate and start again) rather than
fork from omni-digital?

 - Well, github keeps the releases of the repo you fork from. I want to put this on pypi so it's easily available,
and have control of the release versioning (which isn't close to ready for v1.x where it started with omni-digital), so
 it needs to be here.
 - I'm basically about to break *everything* for django 2.x and wagtail 2.x, so I'd need a major version bump anyway, and
 figured that the chances of getting my changes merged into the upstream were nil.
 - The rich text fields make ``omni-wagtail-events`` a nightmare to use in headless API mode, and mean that most of the
 events data is unstructured. Here, we move to Wagtail's ``StreamField``... but that creates a 
 [migration headache](http://docs.wagtail.io/en/v2.4/topics/streamfield.html#migrating-richtextfields-to-streamfield) 
 unless we start fresh.
 - The migrations in the original project won't work with an in-memory database, so testing is slow.
 - I've majorly simplified the model structure to singleton events. I think this is all that's reqiured in 99.9% of cases.

I'm extremely open to collaboration - in fact, I really don't want to be maintaining this (it's only for one client) so
I'm open to transferring ownership or collaboration to anyone who wants to take this on and enhance it. @omni-digital,
this originated as your baby so if you'd like to take back maintenance, please reach out and I'll help you.


## Requirements

Wagtail events requires Django 2.1 or later and Wagtail 2.3 or later.

## Supported Versions

Python: 3.6

Django: 2.1

Wagtail: 2.3

## Getting started

Installing from pip:

```
pip install wagtail_events
```

Adding to `INSTALLED_APPS`:

```python
INSTALLED_APPS = [
    ...
    'wagtail_events',
    ...
]
```

Running the migrations:

```
python manage migrate wagtail_events
```

## Models

### EventIndex

An index/listing page for EventSeries instances, with optional pagination.

### Event

A detail page for an event, with start_date and optional end_date, implementing a manager which allows filtering on those dates.
pyrobust 0.1
Robust Optimizer
License: MIT
Keywords: optimization,optimisation,optimizer,optimiser,robust,genetic algorithms,evolutionary algorithms,GA,genetic

# pyrobust

Robust optimisation aims to find solutions that, given a particular measure of robustness, remain optimal in the face of perturbations within a defined disturbance neighbourhood. pyrobust is a python implementation of various robust optimisation methods developed by the University of Exeter (Prof. Jonathan E. Fieldsend's group). The core optimisation methods utilise the population's search history and resamples the best individuals for new solutions, as described in: _[On the Exploitation of Search History and Accumulative Sampling in Robust Optimisation](https://ore.exeter.ac.uk/repository/handle/10871/27155)_ by K. Alyahya, K. Doherty, O. E. Akman and J. E. Fieldsend, GECCO ’17 Companion, July 15-19, 2017.

Please reference this paper if you undertake work utilising this code.

The examples on this page can be obtained from: https://github.com/EPCCed/pyrobust-examples

Code to run benchmark problems using `pynmmso` can be found at: https://github.com/EPCCed/pyrobust-benchmarking

## Install pyrobust

The Python implementation of Robust requires Python 3, Numpy (https://www.numpy.org/), Scipy (https://www.scipy.org/), pyDOE for Latin Hypercube sampling (https://pythonhosted.org/pyDOE/) and sobol_seq for Sobol sampling (https://pypi.org/project/sobol_seq/). 

You can install the above dependencies and pyrobust using pip, e.g.:

```
pip install pyrobust
```

## Example code

The code for the examples in this documentation can be found at https://github.com/EPCCed/pyrobust-examples.


## Bugs

Bugs can be reported [via Github](https://github.com/EPCCed/pynmmso/issues). We'd also be keen for feedback on this documentation and the examples provided.

## Credits

The following people have contributed to this project:

* Professor Jonathan Fieldsend, Computer Science, University of Exeter
* Dr Ozgur Akman, Mathematics, University of Exeter
* Dr Khulood Alyahya, Computer Science, University of Exeter
* Ally Hume, EPCC, University of Edinburgh
* Dr Chris Wood, EPCC, University of Edinburgh
* Dr Neelofer Banglawala, EPCC, University of Edinburgh
* Professor Andrew J Millar, Chair of Systems Biology, The University of Edinburgh
* Dr Kevin Doherty
* Benjamin J. Wareham

Thanks to the following tools used to produce the graphs on this documentation:

* pyDOE (https://pythonhosted.org/pyDOE/)
* sobol_seq (https://pypi.org/project/sobol_seq/)

This work was supported by the Engineering and Physical Sciences Research Council (grant number [EP/N018125/1](https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/N018125/1))