semvec/pypi-packages huggingface dataset:
mac-formatter-gui 0.1.2
A simple Tkinter GUI to format MAC addresses into common styles and copy them to clipboard.
Requires Python: >=3.8
Keywords: mac, mac address, formatter, gui, tkinter

# MAC Formatter GUI

A simple Tkinter GUI to normalize and display MAC addresses in three common formats:

- Colon: `XX:XX:XX:XX:XX:XX`
- Dash: `XX-XX-XX-XX-XX-XX`
- Dotted: `XXXX.XXXX.XXXX`

It also lets you choose UPPERCASE or lowercase and copy the results to your clipboard.

## Installation

You can install from PyPI once published:

```
pip install mac-formatter-gui
```

For local development (from this repository root):

```
pip install -e .
```

## Usage

After installation, launch the app with the console command:

```
mac-formatter
```

Or via Python:

```
python -m mac_formatter.app
```

## Requirements

- Python 3.8+
- Tkinter (comes with standard CPython on most platforms)

## Development

Build and test the distribution locally:

```
python -m build
```

Upload to TestPyPI:

```
python -m twine upload -r testpypi dist/*
```

Upload to PyPI:

```
python -m twine upload dist/*
```
listdiff 1.0.5
Diff 2 python lists using a given key
Requires Python: >=3.8

# Overview

Diff 2 python lists using a given key

[![image](https://codecov.io/gh/rkhwaja/pylistdiff/branch/master/graph/badge.svg)](https://codecov.io/gh/rkhwaja/pylistdiff)

# Usage

``` python
listA = [3, 2, 1]
listB = [5, 4, 3]
inA, inBoth, inB = DiffUnsortedLists(listA=listA, listB=listB, keyA=lambda x: x, keyB=lambda x: x)
assert inA == [1, 2]
assert inBoth == [(3, 3)]
assert inB == [4, 5]

listA = [1, 2, 3]
listB = [3, 4, 5]
resultB = DiffListsByKey(iterA=iter(listA), iterB=iter(listB), keyA=lambda x: x, keyB=lambda x: x)
assert inA == [1, 2]
assert inBoth == [(3, 3)]
assert inB == [4, 5]
```
pumpia 0.5.16
A simple to use framework for making user interfaces for image analysis.
Requires Python: >=3.12

Introduction
------------

PumpIA is a python framework designed to allow users to visualise the analysis of images through a user interface.
It does not do any image analysis itself, but rather provides a platform for users to write their own analysis code and view the results.
This means that the full power of python and its libraries are available to the user.

See documentation at [PumpIA](https://principle-five.github.io/pumpia/).

Please note there isn't a stable version (v1.0.0) yet, backwards compatibility breaks are instead denoted by the minor version.

Requirements
------------
PumpIA has been designed to use the minimum number of dependencies, so the user interface relies on tkinter.
PumpIA has the following dependencies:

* numpy
* scipy
* pillow
* pydicom
* matplotlib

Installation
------------

PumpIA requires python 3.12 or greater.
To use PumpIA, install from [PyPI](https://pypi.org/project/pumpia/) it using pip:

    pip install pumpia