semvec/pypi-packages huggingface dataset:
automlst.engine 0.5.2
A library to rapidly fetch fetch MLST profiles given sequences for various diseases.
Requires Python: >=3.11

# autoMLST.Engine

A python library implementing common BIGSdb MLST schemes and databases. Implementation follows the RESTful API outlined by the official [BIGSdb documentation](https://bigsdb.readthedocs.io/en/latest/rest.html) up to `V1.50.0`.

## Features

Briefly, this library can:
- Import multiple `FASTA` files
- Fetch the available BIGSdb databases that is currently live and available
- Fetch the available BIGSdb database schemas for a given MLST database
- Retrieve exact/non-exact MLST allele variant IDs based off a sequence
- Retrieve MLST sequence type IDs based off a sequence
- Output all results to a single CSV

Furthermore, this library is highly asynchronous where any potentially blocking operation, ranging from parsing FASTAs to performing HTTP requests are at least asynchronous, if not fully multithreaded.

## Usage

This library can be installed through pip. Learn how to [setup and install pip first](https://pip.pypa.io/en/stable/installation/).

Then, it's as easy as running `pip install automlst-engine` in any terminal that has pip in it's path (any terminal where `pip --version` returns a valid version and install path).

### CLI usage

This is a independent python library and thus does not have any form of direct user interface. One way of using it could be to create your own Python script that makes calls to this libraries functions. Alternatively, you may use `automlst-cli`, a `Python` package that implements a CLI for calling this library.
GovGPT-denoise 0.1.0
A simple and short denoising algorithm to denoise maximum amount of noise from an audio
Requires Python: >=3.7

## Usage Example

Here's how you can use the `mydenoise` library:

```python
from mydenoise.denoise import dnoise

# Input and output paths
input_audio = "path_to_noisy_audio.wav"
output_audio = "denoised_output.wav"

# Denoise the audio
dnoise(input_audio, output_audio)
print(f"Denoised audio saved to {output_audio}")