semvec/pypi-packages huggingface dataset:
httpx-rt 0.1.0
httpx randomizing transport
Requires Python: >=3.10
Keywords: python, httpx, transport

![Python >= 3.10](https://img.shields.io/badge/python->=3.10-red.svg) [![](https://badgen.net/github/release/deedy5/httpx_rt)](https://github.com/deedy5/httpx_rt/releases) [![](https://badge.fury.io/py/httpx_rt.svg)](https://pypi.org/project/httpx_rt) [![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit)](https://github.com/pre-commit/pre-commit)

# httpx-rt

The `httpx-rt` package provides randomizing transport for the httpx library.

## Installation

```bash
pip install httpx-rt
```

## Usage

```python
import httpx
from httpx_rt import RandomizingTransport

client = httpx.Client(transport=RandomizingTransport())
```

## Disclaimer

This package is for educational purposes only. Use at your own risk.
ArfLab 2.1.2
Mathematical Environment Library in Python
Requires Python: >=3.8

# ArfLab — Mathematical Environment Library in Python

  

  

**ArfLab** is a Python library that provides an abstract mathematical environment designed to represent and manipulate sets, intervals, and number systems in a symbolic and intuitive way.

  

The project is continuously growing, with new mathematical structures and operations being added every day.

  

  

Developed and maintained by a **Mathematics undergraduate student at Marmara University**, ArfLab aims to combine mathematical theory with computational representation, creating a bridge between abstract reasoning and code implementation.

  

  

---

  

  

## Features

  

  

- Abstract representation of **Sets**, **Intervals**, and **Number Systems**

  

- Support for **Vector operations** and **linear algebra concepts**

  

- Symbolic and numerical computation environment

  

- Integration with **matplotlib** for visualization

  

- Intuitive class structures and error handling for mathematical rigor

  

  

---

  

  

## Vector

  

  

- Magnitude

  

- Specific vector information

  

- Inner product

  

- Angle between two vectors

  

- Visualization with matplotlib

  

- Find unit vector

  

- Cosine value between two vectors

  

- Projection around two vectors

  

  

---

  

  

## Matrix

  

  

- Precisely defined mathematically

  

- Transpose

  

- Special matrix definitions

  

- Determinant

  

- Hadamard and classical product

  

- Symbolic Matris

  

- (3,3) Sarrus Method



- Permanent Algorithm 

  

  

---

  

  

## Combinatorics

  

  

- Permutation

  

- Combination

  

- Posibilty

  

  

---

  

  

## Calculus

  

  

- Find Supremum İnfrimum value

  

- Σ and Π operations

  

- Transformation

  

- Monotonicity of the series

  

- Symbolid sequance

  

  

---

  

## Physics

  

  

- Wave equation analysis and visualization

$$
\psi(x,y) = \frac{2}{\sqrt{L_x L_y}} \sin\left(\frac{n_x \pi x}{L_x}\right) \sin\left(\frac{n_y \pi y}{L_y}\right)
$$

-  Energy levels of a particle in a two-dimensional cubic box

$$
E = \frac{\pi^2 \hbar^2}{2m} (n_x^2 + n_y^2 + n_z^2)
$$

```bash

Wave_Equation(Lx=2.0, Ly=1.5, nx=4, ny=1, N=100)

```
  

---

  

  

## Visualization

  

  

ArfLab includes built-in vector visualization features using **matplotlib**, allowing users to plot and analyze vector relationships directly in Python. This helps bridge the gap between symbolic manipulation and geometric intuition.

  

## Installation / Download

  

  

### PyPI (Recommended)

  

```bash

pip install ArfLab

```

### Git

  

```bash

git clone https://github.com/Jolankaa/ArfLab

cd ArfLab

pip install .

```

  

### Few Examples

```bash

import ArfLab

# Example: Creating a vector

  

v = ArfLab.Vector([1,2,3])

  

print("Magnitude:", v.magnitude())

# For visualization

v.Visualization()

  

# Example: Creating a matrix

  

m = ArfLab.Matrix([[1,2],[3,4]])

print("Determinant:", m.determinant())

```