semvec/pypi-packages huggingface dataset:
hanifx 26.0.0
Advanced Security & Utility Toolkit for Python
License: MIT
Requires Python: >=3.7

# hanifx

Advanced Security & Utility Toolkit for Python  
Powerful module for web crawling, numeric parameter detection, and security analysis.

---

## Features

- Crawl websites to detect numeric parameters in URLs and forms  
- Detect hidden input fields with numeric values  
- Extract numeric parameters from links and query strings  
- Threaded crawling for faster scanning  
- Clean, duplicate-free output  
- Optional colored output  

---

## Installation

```bash
pip install hanifx



Usage:

import hanifx

# Scan a website for numeric parameters
params = hanifx.crawl_params("https://example.com", max_depth=2)

# Print results
for url, key, val in params:
    print(f"{key}={val} found at {url}")
otp-toolkit 0.1.1
Simple OTP generation and verification toolkit
License: MIT
Keywords: otp security authentication python

# otp-toolkit

A lightweight Python utility for generating and verifying OTPs (One-Time Passwords).

## Features
- Secure OTP generation
- Expiry handling
- SHA256 hashing
- Framework independent (works with Django, Flask, FastAPI)

## Installation
```bash
pip install otp-toolkit

## Example

from otp_toolkit import generate_otp, hash_otp, verify_otp

# Step 1: Generate OTP
otp, expires_at = generate_otp(length=6, expires_in=300)
hashed_otp = hash_otp(otp)

# Send `otp` to user via email/SMS (not shown here)

# Step 2: Verify OTP entered by user
user_input = "123456"

if verify_otp(user_input, hashed_otp, expires_at):
    print("Login successful")
else:
    print("Invalid or expired OTP")


Change Log
=============

0.1.1 (02/02/2026)
------------------
- Improved README with detailed usage examples
- Added real-world OTP flow examples

0.1.0 (02/02/2026)
------------------
- First release
- Secure OTP generation
- OTP expiry handling
- OTP hashing and verification
KDExpress 1.0.1
Fast Kernel Density Estimation with FFT and JAX
License: MIT
Requires Python: >=3.10

<p align="center">
  <img src="KDExpress_logo.png" alt="KDExpress Logo" style="max-width:100%; width:320px; min-width:200px;" />
</p>

<p align="center">
  Kernel Density Estimation accelerated with Fast Fourier Transform and JAX (JIT+GPU support+AD).
</p>

<p align="center">
  <a href="https://opensource.org/licenses/MIT"><img src="https://img.shields.io/badge/License-MIT-yellow.svg" alt="License: MIT"></a>
  <a href="https://www.python.org/"><img src="https://img.shields.io/badge/Python-3.10%2B-blue" alt="Python"></a>
  <a href="https://github.com/google/jax"><img src="https://img.shields.io/badge/JAX-compatible-red" alt="JAX"></a>
</p>


## Features
- **FFT-accelerated KDE** (inspired by [KernelDensity.jl](https://github.com/JuliaStats/KernelDensity.jl)):
  - `fft_kde1d`: 1D KDE with FFT convolution (requires regular grid)
  - `fft_kde2d`: 2D KDE with FFT convolution (requires regular grid)
  - `fft_kde3d`: 3D KDE with FFT convolution (requires regular grid)

  The KDE can be evaluated on non-regular grid by interpolation, such as `jax.numpy.interp` or `jax.scipy.interpolate.RegularGridInterpolator`

- **Binned-accelerated implementation**:
  - `binned_kde1d`: 1D KDE with data binning

- **Bandwidth estimators**:
  - Scott's rule (`scott_bw1d/2d/3d`)
  - Silverman's rule (`silverman_bw1d/2d/3d`)

## Installation

1. Install **JAX** following the instructions at: [https://github.com/jax-ml/jax](https://github.com/jax-ml/jax), e.g

    ```bash
    pip install "jax[cpu]" # For CPU-only version
    ```
    or
    ```bash
    pip install "jax[cuda12]" # For GPU support (CUDA)
    ```
2. Install with `pip`
   ```bash
   pip install KDExpress
   ```

3. Alternative way:
    - Clone the `KDExpress` repo
      ```bash
      git clone https://github.com/mtagliazucchi/KDExpress
      ```
    - Install the code

      a. Editable install:
      ```bash
      cd KDExpress
      pip install -e .
      ```
  
      b. Or use it ad-hoc:
      ```python
      import sys; sys.path.append("/path/to/KDExpress")
      from KDExpress import fft_kde1d
      ```

## Usage and benchmarks
See the [examples](https://github.com/mtagliazucchi/KDExpress/examples) folder.

## License
MIT © [Matteo Tagliazucchi](https://github.com/mtagliazucchi)