semvec/pypi-packages huggingface dataset:
thinhpf 0.1.2
A thin Python wrapper for the Hochbaum Pseudo Flow (HPF) fast s-t min-cut/max-flow algorithm

# Thin wrapper for HPF
Thin Python wrapper for the non-parametric Hochbaum Pseudoflow (HPF) min-cut/max-flow algorithm. The original source code by Bala Chandran and Dorit S. Hochbaum is availbable [here](https://riot.ieor.berkeley.edu/Applications/Pseudoflow/maxflow.html). The C++ code used in this wrapper has been refractored by Patrick M. Jensen and published [here](https://github.com/patmjen/maxflow_algorithms).

## Installation
```
pip install thinhpf
```
## Tiny example
```python
import thinhpf

hpf = thinhpf.hpf()

# Add s and t.
next_node_id = hpf.add_node(2)

def offset(n):
    return 2 + n

s = 0
t = 1

hpf.set_source(0)
hpf.set_sink(1)

# Number of nodes to add.
nodes_to_add = 2

# Add two nodes.
next_node_id = hpf.add_node(nodes_to_add)

# Add edges.
hpf.add_edge(s, offset(0), 5)  # s     --5->   n(0)
hpf.add_edge(offset(0), t, 1)  # n(0)  --1->   t
hpf.add_edge(offset(1), t, 3)  # n(1)  --3->   t
hpf.add_edge(offset(0), offset(1), 2)  # n(0)  --2->   n(1)
hpf.add_edge(offset(1), offset(0), 1)  # n(1)  --1->   n(0)
# Find maxflow/cut hpf.
hpf.mincut()
flow = hpf.compute_maxflow()

for n in range(nodes_to_add):
    segment = hpf.what_label(n)
    print('Node %d has label %d.' % (n, segment))
# Node 0 has label 0.
# Node 1 has label 1.

print('Flow: %s' % flow)
# Maximum flow: 3
```

## Related repositories
- [Hochbaum Group](https://github.com/hochbaumGroup) on GitHub
- [Original source](https://riot.ieor.berkeley.edu/Applications/Pseudoflow/maxflow.html) website
- [slgbuilder](https://github.com/Skielex/slgbuilder) Python package (CVPR 2020)
- [shrdr](https://github.com/Skielex/shrdr) Python package (ICCV 2021)
- [thinqpbo](https://github.com/Skielex/thinqpbo) Python package
- [thinmaxflow](https://github.com/Skielex/thinmaxflow) Python package
- [C++ implementations](https://github.com/patmjen/maxflow_algorithms) of max-flow/min-cut algorithms

## License
The original C code by Bala Chandran and Dorit S. Hochbaum and thereby the content of `hpf.h` (previously `pseudo.c`) is published under an academic license (see LICENSE file). More information on the [original website](https://riot.ieor.berkeley.edu/Applications/Pseudoflow/maxflow.html).
OSDetect 1.2.1
A simple helper module to get details on the current operating system platorm.
Requires Python: >=3.8

OSDetect [![Build Status](https://travis-ci.org/malte70/OSDetect.svg?branch=master)](https://travis-ci.org/malte70/OSDetect)
========

What is OSDetect?
-----------------

OSDetect is a small python module which is able to get some information
about your system and python implementation, like the Operating System
or the hardware platform.

Supported operating systems
---------------------------

As of now, only GNU/Linux, Mac OS X, Windows NT and Windows NT/Cygwin are supported. At the
moment, I'm working on support for a wider range of operating systems.

Since version 1.1.0, Python 2 and Python 3 are both supported.

Note that the information available on the different platforms may differ.

Installation instructions
-------------------------

You can install OSDetect from PyPI using pip:

```
pip install OSDetect
```

Alternatively clone this repository and install directly from the source code:

```
git clone https://github.com/malte70/OSDetect
cd OSDetect
pip install .
```

Command Line Usage
------------------

OSDetect includes a function which is executed if the module is directly called. So give it
a try and run:

	python -m OSDetect

Example uses of the module
--------------------------

```python
# Get a dict containing all gathered information
from OSDetect import info as os_info
print(os_info.getInfo())

# Get a specific value
print(os_info.getDistribution())
# or using the dict key (a dot means a dict containing a dict)
print(os_info.get("Python.Version"))
```

On a ArchLinux system, it looks like this:

```python
{
	'Python': {
		'Version': '3.6.0',
		'Implementation': 'CPython'
	},
	'Machine': 'i686',
	'OS': 'Linux',
	'OSVersion': '4.10.6-1-ARCH',
	'Distribution': 'Arch Linux'
}

'ArchLinux'
'3.6.0'
```
tarp3-nuggets 1.0.3
A package of nuggets found on the web
Requires Python: >=3.13

# tarp3-nuggets

-----

## Table of Contents

- [License](#license)

## Installation

```console
pip install tarp3-nuggets
```

## License

`tarp3-nuggets` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
custom-helpers 0.1.0
A set of helper functions

# Custom Helpers

A small Python utility package providing helper functions for configuration management and import utilities.

## Installation

```bash
pip install custom_helpers
```

## Features

### Configuration Management

Load configuration from YAML files with `omegaconf`:

```python
from custom_helpers import get_config

# Load configuration file with automatic root_dir setting
config = get_config("path/to/conf.yaml")

# Or specify a custom root directory
config = get_config("path/to/conf.yaml", root="/custom/root/path")
```

### Python Path Utilities

Add the project root directory to the Python path:

```python
from custom_helpers import add_root_to_pythonpath

# Add the current directory to Python path
add_root_to_pythonpath()

# Add a parent directory to Python path (go up n levels)
add_root_to_pythonpath(n_up=1)

# Get the root directory path
root_dir = add_root_to_pythonpath(return_root=True)

# Print the added directory
add_root_to_pythonpath(verbose=True)
```

> **Note**: `add_root_to_pythonpath` is designed for script use and will raise an error if used in Jupyter/IPython environments.

## Requirements

- Python 3.10+
- omegaconf