semvec/pypi-packages huggingface dataset:
pyRandomWalk 0.0.1
Functions for the generation of random walks.
Requires Python: >=3.6

[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)
[![build](https://github.com/AlexanderSouthan/pyRandomWalk/actions/workflows/main.yml/badge.svg)](https://github.com/AlexanderSouthan/pyRandomWalk/actions/workflows/main.yml)
[![codecov](https://codecov.io/gh/AlexanderSouthan/pyRandomWalk/branch/master/graph/badge.svg?token=X0M18SSK8S)](https://codecov.io/gh/AlexanderSouthan/pyRandomWalk)
[![Reliability Rating](https://sonarcloud.io/api/project_badges/measure?project=AlexanderSouthan_pyRandomWalk&metric=reliability_rating)](https://sonarcloud.io/summary/new_code?id=AlexanderSouthan_pyRandomWalk)

# pyRandomWalk
Functions for the generation of random walks.


## Installation

Download repository and run:
```
pip install -e .
```
zimmauth 0.1.0
Authentication encryption and storage
Requires Python: >=3.8

# zimmauth

[![codeclimate](https://img.shields.io/codeclimate/maintainability/endremborza/zimmauth.svg)](https://codeclimate.com/github/endremborza/zimmauth)
[![codecov](https://img.shields.io/codecov/c/github/endremborza/zimmauth)](https://codecov.io/gh/endremborza/zimmauth)
[![pypi](https://img.shields.io/pypi/v/zimmauth.svg)](https://pypi.org/project/zimmauth/)

Encrypt and store authentication data for s3 and ssh.
frispy 2.0.2
Frisbee simulation.
Requires Python: >=3.9,<4.0

.. |TRAVIS| image:: https://github.com/tmcclintock/FrisPy/workflows/Build%20Status/badge.svg?branch=master
	    :target: https://github.com/tmcclintock/FrisPy/actions
.. |COVERALLS| image:: https://coveralls.io/repos/github/tmcclintock/FrisPy/badge.svg?branch=master
	       :target: https://coveralls.io/github/tmcclintock/FrisPy?branch=master
.. |LICENSE| image:: https://img.shields.io/badge/License-MIT-yellow.svg
	     :target: https://opensource.org/licenses/MIT

|TRAVIS| |COVERALLS| |LICENSE|

FrisPy
======

Documentation for ``FrisPy`` package can be `found here on RTD
<https://frispy.readthedocs.io/en/latest/>`_.

This repository contains a physical model for a flying disc. Using this code,
one can simulate trajectories of discs with varying initial conditions, while
also changing the underlying physical model. This is useful for analyzing
the mechanics of a disc in terms of its design, as well as creating simulated
throws for things like disc launchers or other helpful tools.

This is a pure Python rebuild of the old FrisPy code, which included a version
of the integrator written in C for speed. Find the fast C simulation in the
`Frisbee_Simulator <https://github.com/tmcclintock/Frisbee_Simulator>`_
repository.

The earliest implementation of this model that I could find was by Sara Ann Hummel
for their 2003 Masters thesis for UC Davis.  You can find the document in full
`on this page <https://morleyfielddgc.files.wordpress.com/2009/04/hummelthesis.pdf>`_.

Installation
------------

The easiest way to install this package is with ``pip``. The PyPI package can
be viewed `here <https://pypi.org/project/frispy/>`_. 

.. code-block:: bash

   pip install frispy


For developers
--------------

Development should be performed using `poetry <https://python-poetry.org/>`_ to handle
the development environment. Once poetry is installed, you can install the environment,
which will include ``frispy``:

.. code-block:: bash

   poetry install

All proceeding instructions assume you entered your virtual environment using ``poetry shell``,
otherwise prepend ``poetry run`` to all instructions.

If you intend to open a pull request, please make sure ``pre-commit`` is installed
before committing to your branch:

.. code-block:: bash

   pre-commit install

This will ensure that the code you submit is PEP8 compliant. Otherwise, CI checks will
fail before merging can be completed.

Verify your installation by running:

.. code-block:: bash

   pytest

Please report any problems you encounter on the `issues page
<https://github.com/tmcclintock/FrisPy/issues>`_. Thank you!
scicom 0.1.2
Simulating various aspects of scientific communication via Agent-based models.
Requires Python: >=3.8

## SciCom

Simulating various aspects of scientific communication via Agent-based models.

In this first version, we introduce an agent-based modelling approach to reconstruct communication in
the Republic of Letters.

Documentation is available on [ReadTheDocs](https://scientificcommunication.readthedocs.io).

## Installation

tl;dr Use pip

~~~bash
pip install scicom
~~~

Consider using a clean virtual environment to keep your main packages separated.
Create a new virtual environment and install the package

~~~bash
python3 -m venv env
source env/bin/activate
pip install scicom
~~~

## Examples

You can find an example Jupyter Notebook showing the use of the LetterSpace model in the [examples folder](./examples/RunModel.ipynb). 

Alternatively, you can use the mesa server framework to create an local browser interface with changeable parameters, 
see screenshot below and [documentation on running mesa](./docs/usingmesa.rst).
<img src="./docs/letterModel.png" alt= “MesaInterface” width="800" height="400">


## Testing

Tests can be run by installing the _dev_ requirements and running `tox`.

~~~bash
pip install scicom[dev]
tox
~~~

## Building documentation

The documentation is build using _sphinx_. Install with the _dev_ option and run

~~~bash
pip install scicom[dev]
tox -e docs
~~~

## Funding information

The development is part of the research project [ModelSEN](https://modelsen.mpiwg-berlin.mpg.de)

> Socio-epistemic networks: Modelling Historical Knowledge Processes,

in Department I of the Max Planck Institute for the History of Science
and funded by the Federal Ministry of Education and Research, Germany (Grant No. 01 UG2131).