semvec/pypi-packages huggingface dataset:
autodiffpy-package 0.0.1
An Automatic Differentiation Package
Requires Python: >=3.7

[![.github/workflows/coverage.yml](https://code.harvard.edu/CS107/team12/actions/workflows/coverage.yml/badge.svg)](https://code.harvard.edu/CS107/team12/actions/workflows/coverage.yml)
[![.github/workflows/tests.yml](https://code.harvard.edu/CS107/team12/actions/workflows/tests.yml/badge.svg)](https://code.harvard.edu/CS107/team12/actions/workflows/tests.yml)
# team12
Team 12's private repository for CS107's final project. 

## Broader Impact
Our software provides a tool for users to efficiently compute derivatives and jacobian values. As a public package lisenced under the MIT License, this tool may be used in a number of areas ranging from scientific research, personal projects, and industry applications. While our package provides similar functionality to pre-existing AutoDiff software, releasing our own version still contributes to the public domain by providing a unique implementation and framework that others may find particularly suitable to their use case. 

As the authors of this package, there are a few consequences important to note. Firstly, while our library has undergone unit and integration testing, we cannot guarantee full correctness in all cases, especially under the conditions of large-scale usage. As with most software, this package may be subject to further iteration & fixes. There may be significant consequences if this AutoDiff library is used without user-written tests; therefore we expect any users to take responsibility for ensuring that their applications meet their expectations and that integrating this AutoDiff package does not make them susceptible to incorrect or unexpected results.

## Software Inclusivity
The aim of this package is to increase access to Autodifferentiation capabilities, for students, researchers, programmers, and others who find it applicable. Additionally, our code is released on Github to improve visibility of the internal implementation of such libraries. We welcome open-source contributions or suggestions, which can be submitted by forking this repository and creating a pull-request (this pull request can contain a simple txt file for suggestions). Pull requests will be reviewed and approved by the original authors, who may reach out to you for collaboration. As an international team, we are happy to work with individuals of any background including non-native English speakers, and will provide language accomodation if needed. For those who are visually-impaired, an audio recording of this README can be accessed in the below Google Drive link.
synesthesiaer 0.1.1
Assigns light and sound frequencies to prime numbers and mixes them using pygame.
Requires Python: >=3.7

#pygame virtual keyboard which assigns a prime number, light frequency, and sound frequency
#to keys. it mixes the light frequencies to corresponding RGB colors, mixes
#the pure tones to sounds, and multiplies the primes to get unique numbers.

This code assigns a color and sound to a range of positive integers in a natural
way.

Input: n

1) Factor n into a product of primes n = p_1^s_1 * ... * p_r ^s_r

2) Map every prime to a wavelength into the visible range which is roughly 380nm (800Thz, violet) - 700nm (400Thz, red). Use f_red*(f_violet/f_red)^((i-1)/(num_keys-1)) in analogy to the keyboard mapping of sound frequencies 440Hz*2^((i-49)/12).

3) For example, the number 197 is p_45. Its light frequency is 492 THz ->  608nm wavelength, so red. 563 is p_103, so 649 THz -> 462nm, so blue. Combining them we get the number 110911 which has a bright purple color. 

4) To convert this spectrum to the appropriate color of light we use the CIE color matching functions (https://www.cs.rit.edu/~ncs/color/t_spectr.html). This can be implemented in almost any language. (https://mathematica.stackexchange.com/questions/57389/convert-spectral-distribution-to-rgb-color/57457#57457).

Output: An RBG color specification.

A similar method can be used for sound, in which case we just scale into the audible range of 20Hz - 20kHz. We then need to mix the tones to get a sound using a synthesizer package, in this case tones.

Importantly, *spectra* of colors and sounds combine additively. Combining natural numbers via multiplication is straightforward.

This could be used to make a *keyboard whose keys are appropriately colored and labeled by prime numbers.
wsblib 1.2.0
Base library for other web servers.
Keywords: www,http,server,internet,socket

# WSBLib

![BADGE](https://img.shields.io/static/v1?label=status&message=development&color=orange)
![BADGE](https://img.shields.io/static/v1?label=license&message=BSD%203-Clause&color=blue)

Web Server Base Library (WSBLib), a library that serves as a basis for creating other web server frameworks in Python. The goal is to be simple, fast and secure.

To create server frameworks, you need to use this library and the [HTTPPyParser](https://github.com/jaedsonpys/http-pyparser) library to get data from the request, as it is your framework that will manage the entire request cycle, the `WSBLib` library just makes it easier for you.

## Installation

You can use the PIP package manager to install `WSBLib`...

```
pip install wsblib
```

Or install manually, cloning the repository and running the command below:

```
python3 setup.py install
```

## Examples

You can see [WSBLib Usage Examples](https://github.com/firlast/wsblib/tree/master/examples) to get an idea of how this library works or get inspired to create your own project using `WSBLib`.

## License

```text
BSD 3-Clause
Copyright (c) 2022, Jaedson Silva
All rights reserved.
```

This project use the `BSD 3-Clause` license. Please [see LICENSE file](https://github.com/firlast/wsblib/blob/master/LICENSE) to **more information** about license.