semvec/pypi-packages huggingface dataset:
cleantextify 0.1.6
A lightweight Python package for cleaning text data.
Requires Python: >=3.6

# cleantextify 🧹✨

[![PyPI version](https://img.shields.io/pypi/v/cleantextify.svg)](https://pypi.org/project/cleantextify/)
[![Downloads](https://pepy.tech/badge/cleantextify)](https://pepy.tech/project/cleantextify)

A lightweight, customizable Python package for cleaning text data.  
Removes URLs, HTML tags, emojis, numbers, punctuation, and normalizes whitespace — perfect for text preprocessing in NLP, data cleaning, and web scraping projects.

---

## 📦 Installation

Install from PyPI:
```bash
pip install cleantextify
```

---

## ✨ Features

- 🚀 Remove URLs
- 🧼 Remove HTML tags
- 😂 Remove emojis
- 🔢 Remove numbers
- 📏 Normalize whitespace
- ! Remove punctuations

---

## 📖 Usage

### Basic Example:
```python
from cleantextify import clean_text

text = "Hello world! 🌟 Visit https://example.com <br> 123"
cleaned = clean_text(text)

print(cleaned)
# Output: Hello world Visit
```
**Output:**
```
Hello world Visit
```
---

## 🔧 Customizable Options

| Parameter         | Type    | Default | Description                                   |
|:-----------------|:--------|:----------|:------------------------------------------------|
| `remove_urls`     | `bool`  | `True`   | Remove URLs from text.                         |
| `remove_html`     | `bool`  | `True`   | Remove HTML tags and entities.                 |
| `remove_emojis`   | `bool`  | `True`   | Remove emojis.                                 |
| `remove_numbers`  | `bool`  | `True`   | Remove numbers.                                |
| `remove_punct`    | `bool`  | `True`   | Remove punctuation marks.                      |
| `normalize_spaces`| `bool`  | `True`   | Replace multiple spaces with a single space.   |

---

## 📚 Full Usage Examples:

### Remove only URLs and Emojis:
```python
from cleantextify import clean_text

text = "Check this out! 😃 https://example.com"
cleaned = clean_text(text, remove_urls=True, remove_emojis=True, remove_numbers=False, remove_punct=False, normalize_spaces=True)

print(cleaned)

```
**Output:**
```
Check this out
```

---
### Remove All but Keep Numbers:
```python
from cleantextify import clean_text

text = "Score: 99! 🎉 Visit: https://test.com"
cleaned = clean_text(text, remove_numbers=False)

print(cleaned)

```
**Output:**
```
Score 99 Visit
```
---

### Only Normalize Spaces:
```python
from cleantextify import clean_text

text = "This    is    a    test."
cleaned = clean_text(text, remove_urls=False, remove_html=False, remove_emojis=False, remove_numbers=False, remove_punct=False, normalize_spaces=True)

print(cleaned)

```
**Output:**
```
This is a test.
```
---



## 📜 License
MIT License

---

## 📞 Author
**Rajdeep Pandhere**  
[rajdeeppandhere36coc@gmail.com](mailto:rajdeeppandhere36coc@gmail.com)

---

## 📦 PyPI Link
[https://pypi.org/project/cleantextify/](https://pypi.org/project/cleantextify/)
hydra-client-python 0.0.0
Client library to communicate with hydra platform
Requires Python: >=3.10

# hydra-client-python
Hydra Platform client libraries for Python

Installation
------------

pip install hydra-client-python


Usage:
------

The hydra client can interact with both hydra-base and hydra-server. Here
we give an example of each, requesting a network from its ID.

Hydra Base
**********

```
import hydra_client as hc

hb_conn = hc.JSONConnection()

hb_conn.login(username='root', password='')

hb_conn.get_network(2)

```

Hydra Server
************

First, start hydra server:

```
hydra-server run

```

```
import hydra_client as hc

hb_conn = hc.RemoteJSONConnection(url='http://localhost:8080/json')

hb_conn.login(username='root', password='')

hb_conn.get_network({'network_id':1})

```
rnadvisor2_webserver 0.1.3
RNAdvisor is a wrapper tool for the computation of RNA 3D structural quality assessment.
Requires Python: >=3.10

<div align="center">

<!-- omit in toc -->
# RNAdvisor webserver 
<strong>Fast and easy way to compute RNA 3D structural quality</strong>

[![uv](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/uv/main/assets/badge/v0.json)](https://github.com/astral-sh/uv)
[![Python](https://img.shields.io/pypi/pyversions/tensorflow.svg)](https://badge.fury.io/py/tensorflow)
[![DOI](https://img.shields.io/badge/DOI-10.1093/bib/bbae064-green)](https://doi.org/10.1093/bib/bbae064)
[![PyPI version](https://badge.fury.io/py/rnadvisor2-webserver.svg)](https://pypi.org/project/rnadvisor2-webserver/)


</div>

RNAdvisor is a wrapper tool for the computation of RNA 3D structural quality assessment. 
It uses [docker compose](https://docs.docker.com/compose/) to run the RNAdvisor tool in a containerized environment. 

This code is a webserver that allows users to upload RNA structures and get quality scores in return.

![img](img/rnadvisor2_screen.gif)

# Installation

To install the RNAdvisor webserver, please first make sure [Docker](https://www.docker.com/) and [docker compose](https://docs.docker.com/compose/) are 
installed on you system. 

Then, you need to clone the Docker images using: 

```bash
make install_docker_images
```
or: 
```bash
source ./installations/install_metrics.sh
```

Then, you can install the webserver using pip:
```bash
pip install rnadvisor2_webserver
```

# Usage

To run the webserver, you can use the following command:

```bash
rnadvisor2_webserver
```

Then, the webserver should be accessible in your browser at ` http://0.0.0.0:8501/RNAdvisor`.