semvec/pypi-packages huggingface dataset:
qudra 0.1.1
Quantum Energy Management
License: MIT
Requires Python: >=3.7
Keywords: qubo energy vqe quantum computing

# qudra
*Quantum Energy Management*

[![License](https://img.shields.io/github/license/Q-Energy-2022/qudra.svg?style=popout-square)](https://opensource.org/licenses/Apache-2.0)
[![](https://img.shields.io/github/release/Q-Energy-2022/qudra.svg?style=popout-square)](https://github.com/Q-Energy-2022/qudra/releases)
[![](https://img.shields.io/pypi/dm/qudra.svg?style=popout-square)](https://pypi.org/project/qudra/)


## Motivation

Leveraging quantum advantage to distributed grids for energy security and sustainability.

*Please check out these slides for more [information](https://www.canva.com/design/DAE8pdmu5A0/F-bEPUubsNa9QMclkktCsg/view).*
## Installation

Our team's contribution is supposed to go into the `qudra` folder. So move there
```console
cd qudra
```

*Conda users, please make sure to `conda install pip` before running any pip installation if you want to install `qudra` into your conda environment.*

`qudra` is published on PyPI. So, to install, simply run:

```bash
pip install qudra
```
If you also want to download the dependencies needed to run optional tutorials, please use `pip install qudra[dev]` or `pip install 'qudra[dev]'` (for `zsh` users).


To check if the installation was successful, run:

```python
>>> import qudra
```

## Building from source

To build `qudra` from source, pip install using:

```bash
git clone https://github.com/Q-Energy-2022/qudra.git
cd qudra
pip install --upgrade .
```

If you also want to download the dependencies needed to run optional tutorials, please use `pip install --upgrade .[dev]` or `pip install --upgrade '.[dev]'` (for `zsh` users).


#### Installation for Devs

If you intend to contribute to this project, please install `qudra` in editable mode as follows:
```bash
git clone https://github.com/Q-Energy-2022/qudra.git
cd qudra
pip install -e .[dev]
```

python3 -m venv venv
. venv/bin/activate
Please use `pip install -e '.[dev]'` if you are a `zsh` user.

#### Building documentation locally

Set yourself up to use the `[dev]` dependencies. Then, from the command line run:
```bash
mkdocs build
```

Then, when you're ready to deploy, run:
```bash
mkdocs gh-deploy
```

## Acknowledgements

**Core Devs:** [Asil Qraini](https://github.com/AsilQ), [Fouad Afiouni](https://github.com/fo-ui), [Gargi Chandrakar](https://github.com/gargi2718), [Nurgazy Seidaliev](https://github.com/nursei7), [Sahar Ben Rached](https://github.com/saharbenrached), [Salem Al Haddad](https://github.com/salemalhaddad), [Sarthak Prasad Malla](https://github.com/SarthakMalla1154)

**Mentors:** [Akash Kant](https://github.com/akashkthkr), [Shantanu Jha](https://github.com/Phionx)

This project was created at the [2022 NYUAD Hackathon](https://nyuad.nyu.edu/en/events/2022/march/nyuad-hackathon-event.html) for Social Good in the Arab World: Focusing on Quantum Computing (QC).
pysound 0.2
Sound and music synthesiser
License: MIT

# PySound

A Python library for creating digital sound and music.

PySound uses numpy arrays to store and process sound.

Features:

* Oscillators - sine, saw, square, wave table and noise
* Envelopes - ramp, attack-decay, generic envelope
* Effects - echo
* Mixers - add, multiply
* Sequencers - join sounds, basic sound sequencer
* Output - WAV file
* Graph - plot sound waves

[Tutorial](http://www.martinmcbride.org/pysound_tutorial)

[Reference](http://www.martinmcbride.org/pysound-reference)
grab-convert-from-libgen 2.0.0
An easy API for searching and downloading books from Libgen.
License: MIT
Requires Python: >=3.9,<4.0
Keywords: libgen,ebooks,books,api,scraper

# grab-convert-from-libgen
An easy API for searching and downloading books from Libgen.

## Before Installing

**Be sure that you have installed Calibre and have added the necessary `ebook-convert` command to your path!**

[calibre](https://calibre-ebook.com/) is "a powerful and easy to use e-book manager". It's also free, open-source, and super easy to use.

You can install an calibre executable, through MacOS Homebrew, compile from source... pick your poison. They only thing you need to be sure of 
is the command `ebook-convert` is in your PATH.

## Install

Install by 

```
pip install grab-convert-from-libgen
```

## Quickstart

The example below shows to grab the first book returned from a search and save it to your current working directory as a pdf.

```python
from grab_from_libgen import LibgenSearch

res = LibgenSearch('sci-tech', q='test')

res.first(convert_to='pdf')
```

This is an example the gets and downloads a book that matches a given title.

```python
from grab_from_libgen import LibgenSearch

res = LibgenSearch('fiction', q='test')

res.get(title='a title', save_to='.')
```

You must specify a `topic` when creating a search instance. Choices are `fiction` or `sci-tech`.

## Documentation

Only search parameters marked as required are needed when searching.

### Libgen Non-fiction/Sci-tech
#### Search Parameters

`q`: The search query (required)

`sort`: Sort results. Choices are `def` (default), `id`, `title`, `author`, `publisher`, `year`

`sortmode`: Ascending or decending. Choices are `ASC` or `DESC`

`column`: The column to search against. Choices are `def` (default), `title`, `author`, `publisher`, `year`, `series`, `ISBN`, `Language`, or `md5`.

`phrase`: Search with mask (word*). Choices are `0` or `1`.

`res`: Results per page. Choices are `25`, `50`, or `100`.

`page`: Page number

### Libgen Fiction
#### Search Parameters

`q`: The search query (required)

`criteria`: The column to search against. Choices are `title`, `authors`, or `series`.

`language`: Language code

`format`: File format

`wildcard`: Wildcarded words (word*). Set to `1`.

`page`: Page number

### LibgenSearch
#### get_results

`get_results(self) -> OrderedDict`

Caches and returns results based on the search parameters the `LibgenSearch` objects was initialized with. Results are ordered
in the same order as they would be displayed on libgen itself with the book's id serving as the key.

#### first

`first(save_to: str = None, convert_to: str = None) -> Dict`

Returns a the first book (as a dictionary) from the cached or obtained results.

#### get

`get(save_to: str = None, convert_to: str = None, **filters) -> Dict`

Returns the first book (as a dictionary) from the cached or obtained results that match the given filter parameters.

The filter parameters must be pulled from the keys that the book dictionary object returns.