semvec/pypi-packages huggingface dataset:
voiceinvoiceout 0.0.1
A module which helps you take voice input, voice output and many more...
Keywords: python,speech,speech-recognition,voice,audio,speak,sprint,text to speech,speech to text


# voiceinvoiceout


```cmd
pip install voiceinvoiceout
```

Developed by Vedant Barhate (c) 2022

This package is useful when you want to take audio input through mic from user, give audio output, give audio+text output and audio repeating feature (like talking tom).

## Example
```python
from voiceinvoiceout import *

vin = voiceIn("Say something...")    # to take audio input 
print(vin)

vout = voiceOut("Hello world")    # to give audio output

sp = sprint("Welcome")      # to give text+audio output (sprint=speak+print)

speakOut()      # to repeat your words (like talking tom)
```
derivationtree 0.4.3
An efficient derivation tree implementation for grammar fuzzing and other applications.
Requires Python: >=3.10

DerivationTree: An Efficient, Trie-Based Derivation Tree Implementation
=======================================================================

[![Python](https://img.shields.io/pypi/pyversions/derivationtree.svg)](https://pypi.python.org/pypi/derivationtree/)
[![Version](http://img.shields.io/pypi/v/derivationtree.svg)](https://pypi.python.org/pypi/derivationtree/)
[![Build Status](https://img.shields.io/github/workflow/status/rindPHI/derivationtree/Test%20DerivationTree)](https://github.com/rindPHI/derivationtree/actions/workflows/test-derivationtree.yml)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

**TODO**

## Build, Run, Install

DerivationTree requires **Python 3.10**.

### Install

Usually, a simple `pip install derivationtree` should suffice.
We recommend installing DerivationTree inside a virtual environment (virtualenv):

```shell
python3.10 -m venv venv
source venv/bin/activate
pip install --upgrade pip
pip install derivationtree
```

### Build 

DerivationTree is built locally as follows:

```shell
git clone https://github.com/rindPHI/derivationtree.git
cd derivationtree/

python3.10 -m venv venv
source venv/bin/activate

pip install --upgrade pip
pip install --upgrade build
python3 -m build
```

Then, you will find the built wheel (`*.whl`) in the `dist/` directory.

### Testing & Development

For development, we recommend using DerivationTree inside a virtual environment (
virtualenv). By thing the following steps in a standard shell (bash), one can run the
ISLa tests:

```shell
git clone https://github.com/rindPHI/derivationtree.git
cd derivationtree/

python3.10 -m venv venv
source venv/bin/activate

pip install --upgrade pip
pip install -r requirements_test.txt

# Run tests
pip install -e .[dev,test]
python3 -m pytest tests
```

## Changelog

See [CHANGELOG.md](CHANGELOG.md).

## Copyright, Authors and License

Copyright © 2022 [CISPA Helmholtz Center for Information Security](https://cispa.de/en).

The DerivationTree code and documentation was, unless otherwise indicated, authored by
[Dominic Steinhöfel](https://www.dominic-steinhoefel.de).

DerivationTree is released under the GNU General Public License v3.0 (
see [COPYING](COPYING)).
tms-django-log 1.0.2
Shortcut to manage logs from Django Admin
Requires Python: >=3.6, <4

# Django Log Shortcut

Install the package

```bash
pip install tms_django_log
```

Add the application in the `INSTALLE_APPS`:

```python
INSTALLED_APPS = [
    ...
    'django.contrib.admin',
    'django.contrib.contenttypes',
    'tms_django_log',
    ...
]
```

Apply migrations

```python
python manage.py migrate
```

Then use the shortcut
```python
from tms_django_log.models import add_log

add_log("Something happened", detail="More details here", level=3)
```
wrgl 0.13.4
Data matching utilities
Requires Python: >=3.7

# Wrgl Python SDK

[![pypi](https://img.shields.io/pypi/v/wrgl)](https://pypi.org/project/wrgl/)
[![docs](https://readthedocs.org/projects/wrgl/badge/)](https://wrgl.readthedocs.io/en/latest/)
[![release-workflow](https://github.com/wrgl/python-sdk/actions/workflows/taggedrelease.yml/badge.svg)](https://github.com/wrgl/python-sdk/actions/workflows/taggedrelease.yml)

This library wraps [Wrgl HTTP API](https://www.wrgl.co/doc/http-api).

## Installation

```
pip install wrgl
```

## Documentation

- [Quickstart](https://wrgl.readthedocs.io/en/latest/quickstart.html)
Learning-to-rank-package 0.0.1
A small package for learning to rank
Requires Python: >=3.6

# ReadMe

This repository is used to share some L2R algorithms implemted by **Python**.

So far, this repository contains **RankNet** , **LambdaRank** and **LambdaMART**



## RankNet

I utilize **Pytorch** to implement the network structure.

In order to use the interface, you should input following parameters:

- `n_feaure`: int, features numble
- `h1_units`: int,  the unit numbers of hidden layer1
- `h2_units`: int, the unit numbers of hidden layer2
- `epoch`: int, iteration times
- `learning_rate`: float, learning rate
- `plot`: boolean, whether plot the loss.

## LambdaRank

The usage is similar with RankNet.



## LambdaMart

This is a Python version of LambdaMART.

I implement it based on the code of [lezzago](https://github.com/lezzago/LambdaMart)

‼️I have made some modification because I think there is a mistake on calculating $\lambda$ in lezzago's code.

## Dataset

The dataset is the same as that of  [lezzago](https://github.com/lezzago/LambdaMart). I have preprocessed it and store in `train.npy` and `test.npy`.

You can directly used `np.load()` to import dataset.



The first column is `label`, the second column is `qid`, and the following columns are features (total 46 features).
pybehance 0.2.5
pybehance package

# behance-py
> Free download of pictures from behance.net

[![PyPI Version][pypi-image]][pypi-url]
[![Build Status][build-image]][build-url]
[![Code Coverage][coverage-image]][coverage-url]
[![Code Quality][quality-image]][quality-url]
[![Downloads](https://static.pepy.tech/personalized-badge/pybehance?period=total&units=international_system&left_color=yellow&right_color=blue&left_text=Downloads)](https://pepy.tech/project/pybehance)
[![Downloads](https://static.pepy.tech/personalized-badge/pybehance?period=month&units=international_system&left_color=green&right_color=red&left_text=Downloads/month)](https://pepy.tech/project/pybehance)
<!-- Badges -->

[pypi-image]: https://img.shields.io/pypi/v/pybehance
[pypi-url]: https://pypi.org/project/pybehance/
[build-image]: https://github.com/meanother/behance-py/actions/workflows/build.yml/badge.svg
[build-url]: https://github.com/meanother/behance-py/actions/workflows/build.yml
[coverage-image]: https://codecov.io/gh/meanother/behance-py/branch/main/graph/badge.svg
[coverage-url]: https://codecov.io/gh/meanother/behance-py
[quality-image]: https://api.codeclimate.com/v1/badges/f4db74d41103b03e0025/maintainability
[quality-url]: https://codeclimate.com/github/meanother/behance-py/maintainability


## Installation
```shell
pip install pybehance
```

## Use

```python
from pybehance import Behance

EXAMPLE_URL = "https://www.behance.net/gallery/157806987/Folio-Reader-Types"

behance = Behance()  # without special path to save pics
behance = Behance(path_to_save="/path/to/save/example_dir")
data = behance.get_pictures_list(EXAMPLE_URL)  # return list

behance.download_pictures()  # download all pictures
```