semvec/pypi-packages huggingface dataset:
galgopy 0.1.1
Basic implementation of a genetic algorithm (GA).
Requires Python: >=3.11
Keywords: algorithm, ga, genetic-algorithm, optimization

# galgopy

![PyPI - Status](https://img.shields.io/pypi/status/galgopy)
![PyPI - Version](https://img.shields.io/pypi/v/galgopy)
![PyPI - Python Version](https://img.shields.io/pypi/pyversions/galgopy)


<p align="center">
<img src="https://raw.githubusercontent.com/vec2pt/galgopy/master/doc/galgopy-00.png" alt="galgopy title image."/>
</p>


A lightweight Python package providing a basic but flexible implementation of the Genetic Algorithm (GA) for optimization tasks.
It can be easily integrated into other projects or extended with custom selection, crossover, and mutation strategies.


## Installation

`galgopy` is available on PyPI:

```bash
pip install galgopy
```

## Usage

### [Sphere Function](https://www.sfu.ca/~ssurjano/spheref.html) Optimization example

```python

import numpy as np

from galgopy.crossover import IntermediateRecombination
from galgopy.ga import GA
from galgopy.mutation import UniformMutation
from galgopy.selection import TournamentSelection

ga = GA(
    population_size=100,
    chromosome_size=2,
    gene_bounds=(-5.12, 5.12),
    fitness_func=lambda x: -np.sum(np.square(x)),
    mutation=UniformMutation(individual_rate=0.1, gene_bounds=(-5.12, 5.12)),
    crossover=IntermediateRecombination(),
    selection=TournamentSelection(),
)

# The course of 50 generations.
for _ in range(50):
    next(ga)

# Result
best_chromosome, _ = ga.best_chromosome()
print(
    f"Result:\t{best_chromosome}",
    "Global minimum:\t[0. 0.]",
    sep="\n",
)
```

### More examples

More examples can be found in the [examples](https://github.com/vec2pt/galgopy/tree/main/examples) directory.

- [Booth Function Optimization](https://www.sfu.ca/~ssurjano/booth.html)
- [One Max Problem](https://github.com/Oddsor/EvolAlgo/wiki/Max-One-Problem)
- String generation
- [Travelling salesman problem (TSP)](https://en.wikipedia.org/wiki/Travelling_salesman_problem)


## License

This project is licensed under the MIT License.
srcignore 0.0.3
Generates a list of files that matches .gitignore-like files
Requires Python: >=3.12

= srcignore

`srcignore` is a Typer-based CLI that reports which files inside a project match
one or more `.gitignore`-style files.

== Installation

[source,console]
----
pip install .
----

Running the tool from source without installing works too:

[source,console]
----
PYTHONPATH=src python -m srcignore --help
----

== Usage

[source,console]
----
srcignore ls PROJECT_ROOT IGNORE_FILE... [--reverse]
----

* `PROJECT_ROOT` — directory to traverse recursively.
* `IGNORE_FILE` — one or more files containing `.gitignore`-style patterns.

By default the command prints each path, relative to `PROJECT_ROOT`, that is
matched by any provided ignore file.

Pass `--reverse` to instead print paths that are *not* matched by at least one
provided ignore file. This is handy for spotting files that would be kept by
your ignore rules.

== Examples

List everything that would be ignored by `.gitignore`:

[source,console]
----
srcignore ls . .gitignore
----

Review files that are *not* matched by `.gitignore` and `.srcignore`:

[source,console]
----
srcignore ls . .gitignore .srcignore --reverse
----
flax-weightwatcher 0.1.1
A smaller, faster, cleaner WeightWatcher for FLAX/JAX with XLA
Requires Python: >=3.12

# Flax-WeightWatcher

Unfortunately, <a href="https://github.com/CalculatedContent/WeightWatcher">CalculatedContent's WeightWatcher</a> does not support FLAX models, and could use accelerated linear algebra (XLA) frameworks for greater speed.

Since I found the process of making a PR to the original WeightWatcher repository too tedious, I just wrote my own one for FLAX models, because that's what I'm working with at the moment. It also helps that JAX uses XLA.

Flax-WeightWatcher is not meant to be a one-one match with the original, yet it is designed to be extensible. I welcome any interest in contributing to it to extend its functionality to perhaps match or exceed the original.

## Installation

A simple `pip install flax-weightwatcher` will install this tool as a Python library. It will also install the following dependancies:

```
jax
flax
numpy
pandas
powerlaw
jaxtyping
```

## Usage

The usage is intended to match that of the original WeightWatcher but has some minor changes.

```python
from flax_weightwatcher import FlaxWeightWatcher

model = nnx.Sequential(*[nnx.Linear(28*28, 128, rngs=nnx.Rngs(0)), nnx.Linear(128, 10, rngs=nnx.Rngs(0))])
watcher = FlaxWeightWatcher(model=model, details_format="df") # can also be "dict" to return the details in a dictionary instead of a pandas DataFrame
details = watcher.analyze()
details.head()
```

This should print something like this:

```
   layer_index layer_name weight_shape     alpha  num_eigenvals_fit  num_eigenvals  stable_ranks  effective_ranks  ranks
0           13   layers.0      784,128  6.143005                 38            128      8.157706       117.944939    128
1           25   layers.1       128,10  5.302257                  8             10      2.552803         9.536791     10
```

## Features to be added

- metrics computed in WeightWatcher
- ESD plotting utilities
MinimalLLMAgent 0.1.5
A minimal LLM agent with memory management.

- [Homepage](https://yuelin301.github.io/posts/Minimal-LLM-Agent): https://yuelin301.github.io/posts/Minimal-LLM-Agent
- [PyPI Page](https://pypi.org/project/MinimalLLMAgent/): https://pypi.org/project/MinimalLLMAgent/
- [GitHub Page](https://github.com/YueLin301/min_llm_agent): https://github.com/YueLin301/min_llm_agent
boring-math-integer-math 1.2.0
Integer Mathematics
Requires Python: >=3.13
Keywords: gcd, lcm, number-theory, primes

Boring Math - Integer Math
==========================

DEPRECATED!!!
-------------

**Effort has been divided between the boring-math-combinatorics
and boring-math-number-theory PyPI projects.**

PyPI project
`boring-math-integer-math
<https://pypi.org/project/boring-math-integer-math>`_.

Python module implementing two integer oriented math libraries.

- number theory module: boring_math.integer_math.number_theory
- combinatorics module: boring_math.integer_math.combinatorics

This PyPI project is part of the
`Boring Math
<https://github.com/grscheller/boring-math/blob/main/README.md>`_ projects.

Documentation
-------------

Documentation for this project is hosted on
`GitHub Pages
<https://grscheller.github.io/boring-math/integer-math/development/build/html>`_.

Copyright and License
---------------------

Copyright (c) 2023-2025 Geoffrey R. Scheller. Licensed under the Apache
License, Version 2.0. See the LICENSE file for details.
youtube-indirici-atilla 4
Komut satırından YouTube videolarını MP4 olarak indirmek için basit ama güçlü bir Python paketi.
Requires Python: >=3.13
Keywords: youtube, indirici, yt-dlp, gui


# YouTube İndirici Atilla

Bununla YouTube'daki videoları son kalitede kolayca indirebilirsiniz (MP4 (Sesli) ve MP3 (Tek Seçenek)).


## Özellikler

- GUI
- Kolay Kullanım
- MP4 ve MP3
- Versiyon Kontrolü (Kaldırıldı)

  
## Nasıl Kullanılır?

İndirildikten Sonra Konsola Şunu Yazarak Başlatabilirsiniz.
```bash
ytvi
```
### veya
```bash
py -3.13 -m ytvi
```
## Lisans

[MIT](https://choosealicense.com/licenses/mit/)