semvec/pypi-packages huggingface dataset:
ntier-aiohttp 1.0.1
Adapt N-Tier to aiohttp
License: MIT

# Connector for N-Tier to aiohttp

N-Tier is a framework agnostic library for building out N-Tier web applications. This module
defines methods for adapting N-Tier to the aiohttp web framework.

Please note: documentation on this project is currently not provided

## Interacting With the Project

`make` is the best way to interact with the project.

### Setting Up:

    make install

### Running Tests:

    make test

### Running Coverage

    make coverage
reg-sieves 0.0.2
The regression approach with sieves.
License: MIT
Keywords: sieves

The function regression_sieves give us the option to generate ATE with a Treatment, dependent and Latitude vectors.
It has the option for polynomial, gaussian, linear spline and quadratic spline sieves. The result returns Omega, Delta, Alpha, ate and the Sieve generated.

Change Log
==========

0.0.1 (21/09/2020)
-------------------
- First Release


0.0.2 (22/09/2020)
-------------------
- First Release
pengu 0.2.0
WIP
License: MIT
Requires Python: >=3.7.6,<4.0.0


# Pengu: a Library for Deep Learning in Computer Vision
Work In Progress！

![Test](https://github.com/peachanG/pengu/workflows/Test/badge.svg?branch=master)
![Python](https://img.shields.io/badge/python-3.7%20%7C%203.8-blue?logo=python)
[![GitHub Issues](https://img.shields.io/github/issues/peachanG/pengu.svg?cacheSeconds=60&color=yellow)](https://github.com/peachanG/pengu/issues)
[![GitHub Pull Requests](https://img.shields.io/github/issues-pr/peachanG/pengu.svg?cacheSeconds=60&color=yellow)](https://github.com/peachanG/pengu/issues)
[![GitHub Release](https://img.shields.io/github/release/peachanG/pengu.svg?cacheSeconds=60&color=red)](https://github.com/peachanG/pengu/releases)

# command
```
$ tensorboard --logdir=./logs
```
```
$ python -m pengu.main.crawler -config config/crawler.yaml -csv data/v2/crawler/crawler_result.csv -i data/v2/crawler/images -n 50
$ python -m pengu.main.preprocess_images -config config/preprocess.yaml -csv data/preprocessed
$ python -m pengu.main.train -config config/train.yaml -i data/train/inputs -m data/train/models -t ./logs
```
dsdce 0.0.2
A simple library to get the code for all Data Structure tutorials for dce department PSG Polytechnic College. Developed by Mohamed Fazil, DCE Student, PSG Polytechnic College.
License: MIT
Keywords: fazil,data structures,psg,dce

A simple library to get the code for all Data Structure tutorials for dce department PSG Polytechnic College. Developed by Mohamed Fazil, DCE Student, PSG Polytechnic College.

Change Log
=========

0.0.1 (22/09/2020)
-------------------
- First Release
offpele 0.3.1
Open Force Field to PELE
License: MIT
Keywords: molecular mechanics,forcefield,potential energy

| **About** | [![License](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE) [![Python](https://img.shields.io/badge/python-3.6%2C%203.7-blue.svg)](https://martimunicoy.github.io/offpele) [![Release](https://img.shields.io/github/release/martimunicoy/offpele.svg?include_prereleases)](https://github.com/martimunicoy/offpele/releases/) |
| :------ | :------- |
| **Status** | [![Language grade: Python](https://img.shields.io/lgtm/grade/python/g/martimunicoy/offpele.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/martimunicoy/offpele/context:python) [![Test](https://github.com/martimunicoy/offpele/workflows/Test/badge.svg)](https://github.com/martimunicoy/offpele/actions?query=workflow%3ATest) [![codecov](https://codecov.io/gh/martimunicoy/offpele/branch/master/graph/badge.svg)](https://codecov.io/gh/martimunicoy/offpele) |
| **Installation** | [![Conda](https://img.shields.io/conda/v/martimunicoy/offpele.svg)](https://anaconda.org/martimunicoy/offpele) [![PyPI](https://img.shields.io/pypi/v/offpele)](https://pypi.org/project/offpele/) |

# Open Force Field to PELE
The `offpele` (Open Force Field to PELE) is a Python package that builds [PELE](https://pele.bsc.es/pele.wt)-compatible force field templates using the [Open Force Field toolkit](https://github.com/openforcefield/openforcefield).

## Documentation
The documentation for the `offpele` package is available at [GitHub Pages](https://martimunicoy.github.io/offpele).