semvec/pypi-packages huggingface dataset:
handshakes 0.10.2
A service that's keen to process your test results
License: MIT
Requires Python: <3.14,>=3.11

# Handshake 🫱🏾‍🫲🏼
_A Modern Test Reporter_

Processes the data collected from the test execution and then generates a modern Dashboard.

## Getting Started

### WebdriverIO

[WebdriverIO](https://webdriver.io/) is a Next-gen browser and mobile automation test framework for Node.js

1. Install Packages: `npm install wdio-handshake-reporter`
2. Install Dashboard: `npm install handshake`
3. Once done you can configure the reporter in your configuration.

## Plans
below are the things I would like to implement sooner or later.

* [X] Add support for `webdriverio`
* [ ] Add Reporter for `jest`
* [ ] Work on documentation
* [ ] Support for `mocha`
* [ ] Listen to `cypress` results
* [ ] Add Support for `playwright`

## Sample Shots
AiologySimilarity 0.0.2
Subset of Aiology package
License: MIT

# AiologySimilarity

This is an easy to use similarity detection package which you can easily setting it up and start working with it !!

To download ,and use this package : `pip install AiologySimilarity`

This package is subset package of Aiology ,and it works offline without any AI token !!

Have a look at [Aiology Website](https://Aiology.pythonanywhere.com)

# Similarity

This package only includes this module ,and this module includes two functions :

`check_words` -> To check for similarity between words

`check_frames` -> To check for similarity between two frames

> [!NOTE]
>All of this methods introduced in the package guide


# Used Algorithms

This package is used two algorithms ,one for words similarity detection ,and one for frames similarity detection.

I wrote all this algorithms based on my math knowledge ,and I like to call them IMA-SAME-ALGORITHM (used for images) ,and WORD-SAME-ALGORITHM (used for words) :D


# What's new ?

fix some bugs


# Conclusion

This is a powerful ,but small ai package which provide you useful tools

I hope this will be useful for you


### Single Star

### Seyed Moied Seyedi
xlsxlean 0.1.0
Minimal memory XLSX reader with safe preview and full content options
License: MIT
Requires Python: >=3.6

# xlsxlean

`xlsxlean` is a lightweight Python package that reads `.xlsx` (Excel) files using minimal memory. It is ideal for memory-constrained environments or scenarios where Excel files might be large or potentially malformed.

---

## 🚀 Features

- **Memory-safe** `.xlsx` reading
- Read **entire content** or just a **preview (e.g., 3000 characters)**
- Automatically parses shared strings and inline values
- Graceful fallback when memory usage exceeds a threshold
- No need for pandas or openpyxl
- Fast and portable — perfect for backend scripts and CLI tools

---

## 📦 Installation

```bash
pip install xlsxlean
```

---

## 🧪 Usage

### Import the Reader

```python
from xlsxlean.reader import read_xlsx_full_content, read_xlsx_preview_3000_chars
```

### Read Entire XLSX File

```python
content = read_xlsx_full_content("example.xlsx", max_memory_mb=2048)
print(content)
```

### Read First 3000 Characters

```python
preview = read_xlsx_preview_3000_chars("example.xlsx")
print(preview)
```

---

## ⚙️ Parameters

- `filepath`: Path to `.xlsx` file
- `max_memory_mb`: (Optional) Max memory in MB. If exceeded, function returns whatever is collected so far
- `char_limit`: (Optional) For preview function — default is 3000

---

## 📂 How It Works

- Unzips `.xlsx` files using Python's `zipfile`
- Parses XML content with `ElementTree`
- Looks for:
  - `xl/sharedStrings.xml` for global text
  - `xl/worksheets/sheet*.xml` for cell values

---

## 🛡️ Memory Safety

- Uses `psutil` to monitor memory usage
- If memory exceeds `max_memory_mb`, function stops and returns collected content

---

## 🔧 Requirements

- Python 3.6+
- `psutil` (installed automatically)

---

## 📄 License

MIT License. See `LICENSE` file for details.

---

## ✍️ Author

**Animesh Ranjan**