semvec/pypi-packages huggingface dataset:
vcorelib 3.6.7
A collection of core Python utilities.
Requires Python: >=3.12

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# vcorelib ([3.6.7](https://pypi.org/project/vcorelib/))

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*A collection of core Python utilities.*

Consider [sponsoring development](https://github.com/sponsors/libre-embedded).

([interface documentation](https://libre-embedded.github.io/python/vcorelib))

## Python Version Support

This package is tested with the following Python minor versions:

* [`python3.12`](https://docs.python.org/3.12/)
* [`python3.13`](https://docs.python.org/3.13/)

## Platform Support

This package is tested on the following platforms:

* `ubuntu-latest`
* `macos-latest`
* `windows-latest`

# Introduction

Core technologies shared between a number of other Python packages.

# Internal Dependency Graph

A coarse view of the internal structure and scale of
`vcorelib`'s source.
Generated using [pydeps](https://github.com/thebjorn/pydeps) (via
`mk python-deps`).

![vcorelib's Dependency Graph](im/pydeps.svg)
miding 3.2.1
A generator of midi score based on GRU.
Requires Python: >=3.9
Keywords: midi, miding, neuronal, generate, music, Jerry Skywolf

# Miding  _3.2.1_

This program names '**miding**', an abbreviation of '**Midi Neuronal Generator**', 
which aims to generate listenable midi sequences, attempting to create fair scores.

Sincerely thanks for _**keras**_, the neuronal network model we have applied.
In this program, the model construction is two GRU layer and a Dense layer with the activation Softmax.
### Download

Here is our website:
* https://github.com/JerrySkywolf/miding

This package could also be downloaded through PyPi by:

`pip install miding`

View at the webpage
* https://pypi.org/project/miding

### How to use the model?

First, **COPY** the model files (*.keras) from our package to your programme path **by calling 'resources.check()'** after importing the package,
which is extremely important!

``from miding import Predict, Seed, resources``
``resources.check(resources.absolute_path(__file__))``

And then, for example, you could use a random seed:

``s = Seed(midi_file='example_seed.mid')``
``Predict(seed=s.get_seed(),epoch=128, model_version=1751770203)``
armstrong-checker 0.1.5
Library to check if a number is Armstrong
Requires Python: >=3.6

# armstrong-checker

A Python library to check if a number is an Armstrong number.

## Usage
    
    from armstrong_checker import armstrong

    armstrong("153")

    or

    armstrong(153)



## Explanations

* The function armstrong() receives either a string or an integer containing a number.
* This number must be an integer.
* If any other parameter is passed, the function will return an error.
* The return value of this function is a Boolean.


## Tested Limit
The highest Armstrong number tested was:

**115132219018763992565095597973971522401**

So, I guarantee it will work with any number below that😃😜.

## License
This project is licensed under the MIT License.


## Instalation

```bash
pip install armstrong-checker
cyclic-crop-rotation 2025.0.1
Cyclic crop rotations labeling for crop sequences
Requires Python: >=3.8
Keywords: crop rotation, crop sequence, crop transition, cyclic rotation

Cyclic Crop Rotation
====================
Description
-----------
This package implements a method to calculate crop rotation labels from any given sequence.

Installation
------------
```pip install cyclic-crop-rotation```

Simple usage
------------
See example folder for more complex use cases.  

```python
from cyclic_crop_rotation import *

# Crop Sequence
seq = (1,  5,  1,  5,  5,  1,  5,  1)

# Valid blocks
blocks = get_valid_blocks(seq,repeat=False,max_rot_size=3)

# Select out of the valid blocks the ones to use
gr = post_selection(greedy_set_cover(blocks)) 
fo = post_selection(first_observed_cover(blocks)) 
lr = post_selection(longest_repetition_cover(blocks)) 

# Get rotation tokens
gr_tok = block2token(seq,gr)
fo_tok = block2token(seq,fo)
lr_tok = block2token(seq,lr)

print(seq)
# Print reordered tokens
print(f'Greedy:{[token2standardtoken(i) for i in gr_tok]}')
print(f'1st Obs:{[token2standardtoken(i) for i in fo_tok]}')
print(f'Long Rep:{[token2standardtoken(i) for i in lr_tok]}')
```
hplog 0.15.0
Add your description here
Requires Python: >=3.13

# HPLOG

## About HPLOG

HPLOG (short for High Performance Logging) enables the user to log their pydantic models in a mongo DB.

> Info
> This project is a small library which is designed for exactly what it says. It is used for logging Pydantic models. In case you have questions about the library or anything else, feel free to contact me