semvec/pypi-packages huggingface dataset:
runtexts 1.7
A CLI and GUI tool to send automated messages.
License: MIT
Requires Python: >=3.6
Keywords: automation, messaging, CLI, pyautogui, tkinter, GUI

# runtexts

`runtexts` is a command-line and graphical user interface (GUI) tool designed to automate the sending of messages.

## Features

- Automate the sending of messages.
- Set a custom delay between messages.
- Simulate fast "bot-like" typing or slower "human-like" typing.
- Simple CLI interface for easy use.
- Option to use a GUI for a more visual experience.
- "Infinity" mode for endless message sending.

## Installation

You can install `runtexts` using pip:

```bash
pip install runtexts
```

### Or manually,

**âœ” Use this method if having problem of installing latest version from PyPi !!!**

1. Clone this repo:

```bash
git clone https://github.com/iamovi/project_runtexts.git
```

2. Go to project directory:

```bash
cd project_runtexts
````

3. Install cli using:

```bash
pip install .
```

## Usage

Once installed, you can run the tool directly from the command line:

```bash
runtexts
```

- Simply run `runtexts` to use the program.

**Or Single use:**

```bash
runtexts cli
```

- this will show runtexts cli prompts.

- Follow the on-screen prompts to configure your message, number of repetitions, typing speed, and delay.

```bash
runtexts gui
```

- this will open a graphical user-interface.

### Upgrade CLI if available:

```bash
pip install --upgrade runtexts
```

## Example

Here is a typical usage scenario:

1. Enter the message you'd like to send.
2. Choose how many times to send the message or set it to "infinity" for endless messaging.
3. Set the delay between each message (in seconds).
4. Choose between fast (bot) or slow (human) typing modes.
5. The tool will automatically type and send the messages.

***And use runtexts GUI for easy process.***

**Type runtexts --help for details.**

## License

This project is licensed under the [MIT License](LICENSE) - see the [LICENSE](LICENSE) file for details.

## Author

Maruf Ovi

fornet.ovi@gmail.com
crypt-tool 0.1.3
A versatile and efficient cryptography library implemented in Python
License: MIT
Requires Python: >=3.6

# Crypt Tool

`crypt_tool` 提供了一个简单的加密和数据转换工具集，包含以下组件：

1. `LinearCongruentialGenerator`: 生成伪随机数，用于加密和字符串生成。
2. `XorCipher`: 基于 XOR 的简单加密解密类。
3. `BytesBitsConverter`: 将字节转换为位、位转换为字节的工具类。

## 使用示例

```shell
# (cd ./python)
# 运行示例函数
python examples/example.py

# 批量测试
python tests/tests.py --verbose
```

### 1. 生成随机数

```python
from crypt_tool import system_random, LCG

rand = system_random()
print("A random number:", rand)

seed = b"a seed"
rnd = LCG.from_seed(seed)
print("Random number from seed:", rnd.generate_u8())
print("Random string:", rnd.generate_random_string(20))
```

### 2. 加密

```python
from crypt_tool import XorCipher

cipher = XorCipher(b"password1")
data = bytes([0, 255, 128, 64, 32, 16, 8, 4, 2, 1])
encoded = cipher.encode(data)
decoded = cipher.decode(encoded)
assert data == decoded, "Decoded data does not match original"
print("Encoding and decoding successful.")
```

### 3. 二进制类型 和 Bytes 类型互相转化
```python
from crypt_tool import BytesBitsConverter

converter = BytesBitsConverter()
bytes_data = bytes([0, 1, 2, 255])

bits = [
    0, 0, 0, 0, 0, 0, 0, 0,  # 0
    0, 0, 0, 0, 0, 0, 0, 1,  # 1
    0, 0, 0, 0, 0, 0, 1, 0,  # 2
    1, 1, 1, 1, 1, 1, 1, 1,  # 255
]

assert converter.bytes_to_bits(bytes_data) == bits
assert bytes_data == converter.bits_to_bytes(bits)
```
scfocus 0.0.5
single cell reinforcement learning for focusing
License: MIT
Requires Python: >=3.9

# scFocus🔍  

## About scFocus  

💗 **scFocus** is an innovative approach that leverages reinforcement learning algorithms to conduct biologically meaningful analyses. By utilizing branch probabilities, scFocus enhances cell subtype discrimination without requiring prior knowledge of differentiation starting points or cell subtypes.  

To identify distinct lineage branches within single-cell data, we employ the **Soft Actor-Critic (SAC)** reinforcement learning framework, effectively addressing the non-differentiable challenges inherent in data-level problems. Through this methodology, we introduce a paradigm that harnesses reinforcement learning to achieve specific biological objectives in single-cell data analysis.  

## Features  

💗 We have developed an interactive website for **scFocus**, designed to help researchers easily perform data preprocessing, dimensionality reduction, and visualization. You can do the following:  

1. **Upload Your Single-Cell Data**  
   - Supports formats including `h5ad`, `10x`. 

2. **Set Parameters**  
   - Configure settings such as:  
     - Number of highly variable genes  
     - Number of neighbors  
     - Minimum distance  
     - Number of branches  

3. **Perform Preprocessing and Dimensionality Reduction Online**  
   - Processes include:  
     - Normalization  
     - Logarithmizing  
     - Highly variable genes selection  
     - Preprocessing  
     - UMAP embedding  
     - scFocus analysis  

4. **Choose Your Visualization Method**  
   - Options include:  
     - Dimensionality reduction plots  
     - Heatmaps  
   - Download the processed files for further analysis.  

<p align="center">  
  <img src="source/_static/Pattern.png" alt="Pattern Image" width="600"/>  
</p>

## **Documentation**

[![Documentation Status](https://readthedocs.org/projects/scfocus/badge/?version=latest)](https://scfocus.readthedocs.io/en/latest/?badge=latest)

[documentation](https://scfocus.readthedocs.io/en/latest/)

## **Installation**

[![PyPI](https://img.shields.io/pypi/v/scfocus.svg?color=brightgreen&style=flat)](https://pypi.org/project/scfocus/)

``` bash
pip install scfocus
```

## **Streamlit UI**

```bash
scfocus ui
```

## **License**
<p>
    <a href="https://choosealicense.com/licenses/mit/" target="_blank">
        <img alt="license" src="https://img.shields.io/github/license/PeterPonyu/scfocus?style=flat-square&color=brightgreen"/>
    </a>
</p>