semvec/pypi-packages huggingface dataset:
wheezy.validation 3.2.1
A lightweight object validation library
Requires Python: >=3.10
Keywords: validation, rules, model

# wheezy.validation

[![tests](https://github.com/akornatskyy/wheezy.validation/actions/workflows/tests.yml/badge.svg)](https://github.com/akornatskyy/wheezy.validation/actions/workflows/tests.yml)
[![Coverage Status](https://coveralls.io/repos/github/akornatskyy/wheezy.validation/badge.svg?branch=master)](https://coveralls.io/github/akornatskyy/wheezy.validation?branch=master)
[![Documentation Status](https://readthedocs.org/projects/wheezyvalidation/badge/?version=latest)](https://wheezyvalidation.readthedocs.io/en/latest/?badge=latest)
[![pypi version](https://badge.fury.io/py/wheezy.validation.svg)](https://badge.fury.io/py/wheezy.validation)

[wheezy.validation](https://pypi.org/project/wheezy.validation/) is a
[python](https://www.python.org) package written in pure Python code. It
provides python object validation.

It is optimized for performance, well tested and documented.

Resources:

- [source code](https://github.com/akornatskyy/wheezy.validation)
  and [issues](https://github.com/akornatskyy/wheezy.validation/issues)
  tracker are available on
  [github](https://github.com/akornatskyy/wheezy.validation)
- [documentation](https://wheezyvalidation.readthedocs.io/en/latest/)

## Install

[wheezy.validation](https://pypi.org/project/wheezy.validation/)
requires [python](https://www.python.org) version 3.10+. It is independent of
operating system. You can install it from
[pypi](https://pypi.org/project/wheezy.validation/):

```sh
pip install -U wheezy.validation
```

If you run into any issue or have comments, go ahead and add on
[github](https://github.com/akornatskyy/wheezy.validation).
openocd-python 2026.2.17
Typed, async-first Python bindings for the full OpenOCD command surface
Requires Python: >=3.11
Keywords: debugging, embedded, hardware, jtag, openocd, swd

# openocd-python

Typed, async-first Python bindings for the full OpenOCD command surface.

## Install

```bash
pip install openocd-python
```

## Quick Start

```python
from openocd import Session

# Connect to a running OpenOCD instance
async with Session.connect() as ocd:
    state = await ocd.target.halt()
    pc = await ocd.registers.pc()
    mem = await ocd.memory.read_u32(0x08000000, 4)
    print(f"PC: {pc:#x}")

# Or spawn OpenOCD and connect
async with Session.start("interface/cmsis-dap.cfg -f target/stm32f1x.cfg") as ocd:
    await ocd.target.halt()
    regs = await ocd.registers.read_all()

# Synchronous API available too
with Session.start_sync("interface/cmsis-dap.cfg") as ocd:
    ocd.target.halt()
    print(f"PC: {ocd.registers.pc():#x}")
```

## Features

- **Async-first** with sync wrappers for every method
- **Typed returns** — dataclasses, not raw strings
- **Full OpenOCD surface**: target control, memory, registers, flash, JTAG, breakpoints, RTT
- **SVD decoding** — read a peripheral register and get named bitfields
- **Process management** — spawn and manage OpenOCD subprocesses
- **Dual transport** — TCL RPC (primary) and telnet (fallback)

## Requirements

- Python 3.11+
- OpenOCD installed and on PATH (or pass `openocd_bin=`)
visualens 0.1.5
A visual interface to explore and manipulate astronomical images, catalogs, and lens models created using Lenstool.
Requires Python: >=3.8

# visualens

### A visual, fast interface to explore and manipulate astronomical images, catalogs, and lens models created using Lenstool.

`visualens` uses `PyQt` for fast handling of large astronomical images. Main lensing functionalities include:
- Fast, easy-to-run lensing calculations using `Lenstool`'s engine,
- Visual forward modeling based on `lenstronomy`.

---

### Installation:

Many `visualens` functions rely on `Lenstool`, which is easy to install through conda (highly recommended). We also recommend installing `lenstronomy` through conda rather than pip, before installing `visualens`.

Some IDEs like Spyder may cause conflicts with PyQt. We suggest installing your favorite IDE in your conda virtual environment before visualens.

**Installation steps:**

> `conda create -n visualens_env -c conda-forge lenstool lenstronomy python==3.12.2`

> `conda activate visualens_env`

Install your favorite python GUI

> `pip install visualens`

---

### Starting guide:

https://github.com/tomresseguier/Lenstool_GUI/tree/main/examples