semvec/pypi-packages huggingface dataset:
FFPopSim 3.1.2
Library to simulate evolution of large populations that are polymorphic at many loci.
Requires Python: >=3.6
Keywords: packaging,dependency,infer,pyproject.toml

[![Build Status](https://travis-ci.org/iosonofabio/ffpopsim.svg?branch=master)](https://travis-ci.org/iosonofabio/ffpopsim)
[![Documentation Status](https://readthedocs.org/projects/ffpopsim/badge/?version=latest)](https://readthedocs.org/projects/ffpopsim/?badge=latest)
[![License](https://img.shields.io/badge/license-GPL3-blue.svg)](http://www.gnu.org/copyleft/gpl.html)

* License:	GPL3
* Author:	Richard Neher, Fabio Zanini
* Creation:	2012/09/12

Description
------------
![Genetic drift and draft](/data/drift_vs_draft.png)

**FFPopSim** is a **C++** and **Python** library to simulate large populations that are polymorphic at many loci. It allows for asexual and recombining populations and complex fitness functions, including pairwise and higher order epistasis. It is designed to study the effects of linked selection, the rare processes in large populations, and can be used to address a large variety of population genetics problems.

FFPopSim is easy to use via the Python interface and can be extended or modified both at the C++ or Python level.


Downloads
---------
The official sources and releases are online at:

https://github.com/neherlab/ffpopsim

https://github.com/iosonofabio/ffpopsim

Docs
----
Documentation and examples are online at:

http://webdav.tuebingen.mpg.de/ffpopsim/

http://ffpopsim.readthedocs.io/en/latest/

(The latter only for the Python interface.)

Install
-------
To install the library, read the INSTALL file.
The two configuration files are:

- Makefile
- setup.py (for the Python extension)

Enjoy.
django_loggers_test 1.0.3
A simple tester of Django's loggers' configuration
Requires Python: >=3.5

# Django Loggers Test

A simple tester of Django's loggers' configuration.

![Screenshot](https://raw.githubusercontent.com/vsego/django_loggers_test/master/images/screenshot.png)

## Content

1. [Installation](#installation)
2. [Usage](#usage)

## Installation

The easiest way to get this is from PyPI:

```bash
pip install django_loggers_test
```

## Usage

Run your project's shell (`python manage.py shell`), and then

```pycon
>>> from django_loggers_test import loggers_test
>>> loggers_test()
```

This will log messages to the console, using all available formatters and
levels. There isn't really much more to it, apart from minor configurability.
For details, run

```pycon
>>> help(loggers_test)
```
pkgexampledatabases 0.0.5
A simple database package example
Requires Python: >=3.7

# pkgexampledatabases

A RexBytes example package that shows you how to,

1) Create and address an sqlite3 database inside your python package.
2) Create and address an sqlite3 database at anyother location on a filesystem.
   Access to a users home directory is used as the example.


The following config files are used to describe two sqlite databases.

1) /pkgexampledatabases/data/config/packagedb.json
   This is the json description file for the database that is constructed inside your package.

2) /pkgexampledatabases/data/config/userdb.json
   This is the json desctiption file for the database that is constructed inside a users home directory.


You can have as many database entries in the above files as you like.
It is convenient to describe your databases in json format and let your package create the
end user databases.
pyclstr 0.0.2.post0.dev1
Simple clustering algorithms


.. image:: molecular.svg
   :alt: molecular
   :height: 200

a package for molecular dynamics simulations and analysis

..
   master

.. image:: https://img.shields.io/pypi/v/molecular
   :target: https://pypi.org/project/molecular/

.. image:: https://img.shields.io/travis/com/lockhartlab/molecular/master
   :target: https://travis-ci.com/github/LockhartLab/molecular

.. image:: https://img.shields.io/codecov/c/github/lockhartlab/molecular/master
   :target: https://codecov.io/gh/LockhartLab/molecular

..
   *dev:*
   <nobr><img src="https://img.shields.io/travis/com/lockhartlab/molecular/dev"  alt="build-status-dev"/></nobr>
   <nobr><img src="https://img.shields.io/codecov/c/github/lockhartlab/molecular/dev" alt="coverage-dev"/></nobr>

note that this package is **still in development**
at this stage, I'm only building thing as they come to mind  
version 1.0 will be the first major release  
until then, consider this code heavily volatile

Note: portions of this code have Fortran backends that may need to be built prior to successful use of the code. We
have it on our to-do list to compile OS-specific wheels.

yet, install simply by calling `pip install molecular` or `pip install --pre molecular` for the latest development
release.

we endeavor to follow https://scikit-learn.org/stable/developers/performance.html

similar packages:
BioSimSpace
MDAnalysis
MDTraj