semvec/pypi-packages huggingface dataset:
voxypy 0.2.3
Data structures for Voxel operations.
License: MIT

# VoxyPy    
 A data structure for Voxel operations.     
    
- Uses [NumPy](https://pypi.org/project/numpy/) for speed and efficiency.     
- Uses a modified version of [numpy-vox-io](https://github.com/alexhunsley/numpy-vox-io) for IO operations.    
    
## Quickstart 
```python  
from voxypy.models import Entity, Voxel
dense = np.zeros((10, 10, 10), dtype=int)
entity = Entity(data=dense)

entity.set(x=1, y=2, z=3, 42)
voxel = entity.get(1, 2, 3) # Voxel object with value 42

voxel.add(1) # Voxel object with value 43
new_voxel = Voxel(255)
new_voxel.add(1) # Returns Voxel object with value 1
entity.set(5, 5, 5, new_voxel)
entity.set(5, 5, 5, 69)

entity = Entity().from_file('old_entity.vox')
# optional
entity.set_palette_from_file('palette.png')
entity.save('new_entity.vox')
```

Full documentation can be found [here](https://voxypy.readthedocs.io/en/latest/)

## Helpful Links

- **[VoxyPy Full Documentation](https://voxypy.readthedocs.io/en/latest/#)**
- [VoxyPy GitLab repo](https://gitlab.com/Claytone/voxypy)
- [Claytone's blog for development commentary](https://claytonwells.com/)
- [NumPy](https://pypi.org/project/numpy/)
- [MagicaVoxel voxel editor](https://ephtracy.github.io/)
servicenowpy 0.1.0
ServiceNow Table API, easily
License: MIT
Requires Python: >=3.8
Keywords: servicenow

servicenowpy
============

[![PyPI version](https://badge.fury.io/py/servicenowpy.svg)](http://badge.fury.io/py/servicenowpy)
[![License](https://img.shields.io/github/license/mashape/apistatus.svg)](https://pypi.python.org/pypi/servicenowpy/)
[![Downloads](https://pepy.tech/badge/servicenowpy)](https://pepy.tech/project/servicenowpy)

A library that helps you to get data from ServiceNow's Table API.

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

```shell
pip install servicenowpy
```

Simple usage
------------

How to retrieve records from incident table with this lib:

```python
>>> from servicenowpy import Client
>>> sn_client = Client('<instance>.service-now.com', '<user>', '<pwd>')
>>> inc_table = sn_client.table('incident')
>>> records = inc_table.get(sysparm_fields='number,short_description')
>>> for record in records:
...     print(record)
{'number': 'INC0000060', 'short_description': 'Unable to connect to email'}
{'number': 'INC0000009', 'short_description': 'Reset my password'}
{'number': 'INC0009005', 'short_description': 'Need access to the common drive'}
```
_________________

[Further Documentation](https://servicenowpy.readthedocs.io/) | [Github Repository](https://github.com/henriquencmt/servicenowpy/) | [Contributing](https://github.com/henriquencmt/servicenowpy/blob/main/CONTRIBUTING.md)
PyAbSort 0.0.1
A Very Powerful and fully documented package to perform different types of Sorting techniques on the list Data Structure.
License: MIT
Keywords: SortingAlgo

AbSort
=======

Absort is Powerful Python package that performs 8 different types of stable and unstable Sorting algorithms on List Data Structure with full of documentation. 
This package will be more beneficial(Usefull) for competitive programmers and developers. So based on your requirement choose your sorting algorithm.

USAGE
======

importing Library
-----------------

- from SortingAlgos import *

Creating the  Object
sortObj = AbSort.SortingAlgo()


awsort
======

myList = [490, 395, 388, 496, 497, 350, 469, 435, 310, 1, 3, 2, 7, 4]

#Genearting the Sort Result 

sortedResult = sortObj.awsort(myList)

#Science know the SortedResult variable contains the Sorted List we can print the sorted list saying

print(sortedResult)



SelectionSort
=============

myList = [490, 395, 388, 496, 497, 350, 469, 435, 310, 1, 3, 2, 7, 4]

- Genearting the Sort Result 

sortedResult = sortObj.selectionSort(myList)

- Science know the SortedResult variable contains the Sorted List we can print the sorted list saying

print(sortedResult)



mergeSort
=========

myList = [490, 395, 388, 496, 497, 350, 469, 435, 310, 1, 3, 2, 7, 4]

- Genearting the Sort Result 

sortedResult = sortObj.mergeSort(myList)

- Science know the SortedResult variable contains the Sorted List we can print the sorted list saying

print(sortedResult)



quickSort
=========

myList = [490, 395, 388, 496, 497, 350, 469, 435, 310, 1, 3, 2, 7, 4]

- Genearting the Sort Result 

sortedResult = sortObj.quickSort(myList)

- Science know the SortedResult variable contains the Sorted List we can print the sorted list saying

print(sortedResult)



bogoSort
========

myList = [490, 395, 388, 496, 497, 350, 469, 435, 310, 1, 3, 2, 7, 4]

- Genearting the Sort Result 

sortedResult = sortObj.bogoSort(myList)

- Science know the SortedResult variable contains the Sorted List we can print the sorted list saying

print(sortedResult)



insertionSort
=============

myList = [490, 395, 388, 496, 497, 350, 469, 435, 310, 1, 3, 2, 7, 4]

- Genearting the Sort Result 

sortedResult = sortObj.insertionSort(myList)

- Science know the SortedResult variable contains the Sorted List we can print the sorted list saying

print(sortedResult)



binaryInsertionSort
===================

myList = [490, 395, 388, 496, 497, 350, 469, 435, 310, 1, 3, 2, 7, 4]

- Genearting the Sort Result 

sortedResult = sortObj.binaryInsertionSort(myList)

- Science know the SortedResult variable contains the Sorted List we can print the sorted list saying

print(sortedResult)



bubbleSort
==========

myList = [490, 395, 388, 496, 497, 350, 469, 435, 310, 1, 3, 2, 7, 4]

- Genearting the Sort Result 

sortedResult = sortObj.bubbleSort(myList)

- Science know the SortedResult variable contains the Sorted List we can print the sorted list saying

print(sortedResult)


Dependencies
============

- Python v3.x is Required.



Change Log
==========


0.0.1 (11/14/2021)
-------------------

- First Release
atom3-py3 0.2.1
3D Atomic Data Processing (Python 3 version)
License: MIT

atom3-py3
=========

Processing of 3D atomic data (Python 3 version).

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

.. code-block:: console

    $ pip3 install atom3-py3

Usage
-----

Process a PDB file to a pickled pandas dataframe.

.. code-block:: console

    $ atom3 parse sample/11as.pdb1.gz sample/parsed

Derive subunits of a parsed dataframe.

.. code-block:: console

    $ atom3 complex sample/parsed sample/complexes.dill

Split subunits into interacting pairs.

.. code-block:: console

    $ atom3 pairs sample/complexes.dill sample/pairs

For help on commands.

.. code-block:: console

    $ atom3 -h
    $ atom3 parse -h