semvec/pypi-packages huggingface dataset:
SwarAnuvad 0.0.0
Speech translation assistant
Keywords: voice translate,voice to text translate,multiple language voice translate,translate,text to voice translate

The code uses speech recognition to capture user input through a microphone. It then recognizes the speech using Google's Speech-to-Text API. 
    The user is prompted to specify a language, and their subsequent speech is translated into multiple languages. The translations are displayed in the console.
    The speech translation assistant allows users to communicate in different languages by converting their spoken input into written text and providing translations in various supported languages.
    
    https://github.com/Tejass0/SwarAnuvad


# Make sure you have upgraded version of pip
Windows
```
py -m pip install --upgrade pip
```

Linux/MAC OS
```
python3 -m pip install --upgrade pip
```


# Requirements
Python 3.9+


# Installation
Install using pip...
```
pip install SwarAnuvad
pip3 install SwarAnuvad
```

# Example
```
from SwarAnuvad import SwarAnuvad

s = SwarAnuvad()
pop = s.lantrans()
print(pop, "++++")
```

# Output
```
['GREEK: Πώς είσαι', 'ESPERANTO: kiel vi fartas', 'ENGLISH: how are you', 'AFRIKAANS: Hoe gaan dit', 'SWAHILI: habari yako', 'CATALAN: Com estàs', 'ITALIAN: Come stai', 'HEBREW: מה שלומך', 'SWEDISH: Hur mår du', 'CZECH: jak se máte', 'WELSH: Sut wyt ti', 'ARABIC: كيف حالك', 'URDU: آپ کیسے ہو', 'IRISH: Conas tá tú', 'BASQUE: zelan zaude', 'ESTONIAN: kuidas sul läheb', 'AZERBAIJANI: necəsən', 'INDONESIAN: Apa kabarmu', 'SPANISH: Cómo estás', 'RUSSIAN: Как вы', 'GALICIAN: como estás', 'DUTCH: Hoe is het', 'PORTUGUESE: como vai', 'LATIN: quid agis', 'TURKISH: Nasılsın', 'FILIPINO: Kamusta ka', 'LATVIAN: kā tev iet', 'LITHUANIAN: kaip laikaisi', 'THAI: คุณเป็นอย่างไร', 'VIETNAMESE: Bạn khỏe không', 'ROMANIAN: ce mai faci', 'ICELANDIC: hvernig hefurðu það', 'POLISH: Jak się masz', 'TAMIL: எப்படி இருக்கிறீர்கள்', 'YIDDISH: וואס מאכסטו', 'BELARUSIAN: як ты', 'FRENCH: comment allez-vous', 'BULGARIAN: Как си', 'UKRAINIAN: як справи', 'CROATIAN: kako si', 'BENGALI: আপনি কেমন আছেন', 'SLOVENIAN: Kako si', 'HAITIAN CREOLE: koman ou ye', 'DANISH: Hvordan har du det', 'PERSIAN: چطور هستید', 'HINDI: आप कैसे हैं', 'FINNISH: mitä kuuluu', 'HUNGARIAN: hogy vagy', 'JAPANESE: 元気ですか', 'GEORGIAN: როგორ ხარ', 'TELUGU: మీరు ఎలా ఉన్నారు', 'CHINESE TRADITIONAL: 你好嗎', 'ALBANIAN: si jeni', 'NORWEGIAN: hvordan har du det', 'KOREAN: 어떻게 지내세요', 'KANNADA: ನೀವು ಹೇಗಿದ್ದೀರಿ', 'MACEDONIAN: како си', 'CHINESE SIMPLIFIED: 你好吗', 'SLOVAK: ako sa máš', 'MALTESE: kif int', 'MARATHI: तू कसा आहेस', 'GERMAN: Wie geht es dir', 'MALAY: apa khabar', 'SERBIAN: како си'] ++++
```

# Please wait at-least 20 seconds to see the output.
# Currently, this package is on upgrade.
#
django-twilio-access-token 0.0.5
A Django app to generate Twilio access token for particular Twilio services.
Keywords: django,twilio,access,token


# django-twilio-access-token

This is a Django application that can be used to generate Twilio access token for particular services, such as Voice, Chat, and Video.

## Prerequisite

### Twilio

We use Twilio client for [python](https://www.twilio.com/docs/libraries/python#install-the-library) to generate an access token for Twilio services. To make the package works on your project, you need to install Twilio client either through [pip](https://pip.pypa.io/en/stable/) command;

```
pip install twilio
```

or simply add Twilio on your `requirements.txt`

```
twilio~=6.32.0
```

### Twilio keys

In order to make the package works with your django project, you need to define the Twilio keys inside your project `settings.py`, for example:
```
TWILIO_ACCOUNT_SID = 'PUT_YOUR_TWILIO_ACCOUNT_SID_HERE'  # You can find Twilio Account SID at the top right section of this page https://www.twilio.com/console/

TWILIO_VIDEO_API_KEY_SID = 'PUT_YOUR_TWILIO_VIDEO_API_KEY_SID_HERE'  # You can obtain these keys by creating it through https://www.twilio.com/console/video/project/api-keys/
TWILIO_VIDEO_API_KEY_SECRET = 'PUT_YOUR_TWILIO_VIDEO_API_KEY_SECRET_HERE'
```

Or see the `test_project/test_app/settings.py` if you need to know more.

## How to run the test project

To try out the package, you can run our test application by following these steps:
1. Ensure pip installed on your local machine. If you don't have it, you can follow the installation guide [here](https://pip.pypa.io/en/stable/installing/).
2. Open terminal and go to the root directory of where the package live, for instance: `$ cd Documents/py-projects/django-twilio-access-token`.
3. Run `$ ./scripts/requirement-install.sh` from your command line.
4. Run `$ source venv/bin/activate`.
5. Run `$ python manage.py runserver 0.0.0.0:8000` and enjoy the token API's.

## Get involved!

We are happy to receive bug reports, fixes, documentation enhancements, and other improvements.

Please report bugs via the github [issue tracker](https://github.com/senseobservationsystems/django-twilio-access-token/issues).

Master git repository [django-twilio-access-token](https://github.com/senseobservationsystems/django-twilio-access-token).
pyreference 0.7.5
Library for working with reference genomes and gene GTF/GFFs
Requires Python: >=2.7, >=3.5
Keywords: genomics,gtf,gff,genome,genes

## PyReference ##

[![PyPi version](https://img.shields.io/pypi/v/pyreference.svg)](https://pypi.org/project/pyreference/) [![Python versions](https://img.shields.io/pypi/pyversions/pyreference.svg)](https://pypi.org/project/pyreference/)

A Python library for working with reference gene annotations. For RefSeq/Ensembl GRCh37/GRCh38 and other species

A GTF/GFF3 can take minutes to load. We pre-process it into JSON, so it can be loaded extremely rapidly.  

PyReference makes it easy to write genomics code, which is easily run across different genomes or annotation versions.

## Example ##

    import numpy as np
    from pyreference import Reference 
    
    reference = Reference()  # uses ~/pyreference.cfg default_build

    my_gene_symbols = ["MSN", "GATA2", "ZEB1"]
    for gene in reference[my_gene_symbols]:
        average_length = np.mean([t.length for t in gene.transcripts])
        print("%s average length = %.2f" % (gene, average_length))
        print(gene.iv)
        for transcript in gene.transcripts:
            if transcript.is_coding:
                threep_utr = transcript.get_3putr_sequence()
                print("%s end of 3putr: %s" % (transcript.get_id(), threep_utr[-20:]))

Outputs:

	MSN (MSN) 1 transcripts average length = 3970.00
	chrX:[64887510,64961793)/+
	NM_002444 end of 3putr: TAAAATTTAGGAAGACTTCA

	GATA2 (GATA2) 3 transcripts average length = 3367.67
	chr3:[128198264,128212030)/-
	NM_001145662 end of 3putr: AATACTTTTTGTGAATGCCC
	NM_001145661 end of 3putr: AATACTTTTTGTGAATGCCC
	NM_032638 end of 3putr: AATACTTTTTGTGAATGCCC

	ZEB1 (ZEB1) 6 transcripts average length = 6037.83
	chr10:[31608100,31818742)/+
	NM_001174093 end of 3putr: CTTCTTTTTCTATTGCCTTA
	NM_001174094 end of 3putr: CTTCTTTTTCTATTGCCTTA
	NM_030751 end of 3putr: CTTCTTTTTCTATTGCCTTA
	NM_001174096 end of 3putr: CTTCTTTTTCTATTGCCTTA
	NM_001174095 end of 3putr: CTTCTTTTTCTATTGCCTTA
	NM_001128128 end of 3putr: CTTCTTTTTCTATTGCCTTA

This takes 4 seconds to load on my machine.

## pyreference biotype ##

Also included is a command line tool (pyreference_biotype.py) which shows which biotypes small RNA fragments map to.

![](https://i.stack.imgur.com/Tsjr3.jpg)

## Installation ##

    sudo pip install pyreference

Then you will need to:

* [Download / Create gene annotations](https://github.com/SACGF/pyreference/wiki/genes_json_file)
* Create a [pyreference config files](https://github.com/SACGF/pyreference/wiki/pyreference_config_file)
flake8-module-docstring-import 0.0.1
Very simple flake8 plugin checking if there is exactly one new line between module docstring and imports

Very simple flake8 plugin to check if there is one new line between module docstring and imports at the top of the file.

## Installation:
```python
pip install flake8-module-docstring-import
```

## List of warnings
**MDL001**: There is no one new line between module docstring and imports at the top of the file.

## Examples
These examples will trigger problem:
```python
"Very important docstring"
import sys
```
```python
"Very important docstring"


import sys
```
This is correct:
```python
"Very important docstring"

import sys
```
MetaGen-datalabupo 0.0.3
A Python Package for Hyperparameter Tuning in Machine and Deep Learning Models Based on the Coronavirus Optimization Algorithm
Requires Python: >=3.10

![](https://img.shields.io/badge/python-3.12-orange) 
# Metagen 

## Introduction
Metagen is a simple python library for solving optimization problems by metaheuristics algorithms. The project provides a set of already defined metaheristics and provide the basic tools to allow the user redefine/build its own algorithms in a simple way.

This project is currently maintained by the David Gutierrez Áviles and Manuel Jesús Jiménez Navarro.

https://datalab.upo.es/

Link to the original paper: [Metagen](https://example.com)

## Instalation

Metagen only requires python (>=3.12) as the library has been built completely on python.

For the instalation, the easiest way is to use pip:

    pip install metagen


## Tutorial

In orfer to work metagen we first need to import the [Domain]() definition and an available [metaheuristic]().  

    from metagen.framework import Domain, Solution
    from metagen.metaheuristics import RandomSearch

Every problem in metagen is defined by two elements: a **domain** and a **fitness**.

The **domain** of the problem is constructed by using the [Domain]() imported previously . In this case we defined a simple domain with one integer variable in range [-10, 10].

    domain: Domain = Domain()
    domain.define_integer("x", -10, 10)

The fitness is a callable which receives a [Solution]() as parameter and returns a float value.

    def p1_fitness(solution: Solution) -> float:
        x = solution["x"] # The variable represents a potential solution instance which can be used as an map returning the builtin value.
        return x + 5

Finally, we only need to instantiate our metaherustic (in this case a simple random search) indicating the **domain** and **fitness** and run it returning the best solution.

    random_search: RandomSearch = RandomSearch(domain, fitness)
    solution: Solution = random_search.run()


## Development

New contributors from all experience levels are welcomed. To contribute, you can open an issue or sending a pull request.

For testing the repository you just need to execute the following command:

    pytest test

## API reference

The official documentation is available in: https://metagen.readthedocs.com.

## References

* cvoa: https://www.liebertpub.com/doi/10.1089/big.2020.0051
pynometrics 0.1.5
Includes functions for performing econometrics tasks


# pynometrics package
 pynometricss is a package for performing econometric modeling and diagnostic task. 

 # Installation

 Use the package manager [pip](https://pip.pypa.io/en/stable/) to install pynometrics

 ```bash
pip install pynometrics
```

# Usage
 ```python
 import pynometrics as ec
  ```

 ## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License
[MIT](https://choosealicense.com/licenses/mit/)