semvec/pypi-packages huggingface dataset:
gerador-senhas 0.0.2
Pacote para gerar senhas aleatórias contendo números, letras e caracteres especiais.
Requires Python: >=3.8

# package_name

Description. 
O pacote gerador_senha é utilizado para:
	- Gerar senhas de tamanhos variádos que podem ou não conter letras, números e caracteres especiais, de acordo com especificações prévias.
	- Verificar se na senha gerada estão presentes os itens letra, números e caracteres especiais, especificados previamente.

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install package_name

```bash
pip install gerador_senha
```

## Usage

```python
from gerador_senhas import construtor_senha
```

## Author
Rafael Rodrigues Mateus

## License
[MIT](https://choosealicense.com/licenses/mit/)
kolsol 1.0.1
Pseudospectral Kolmogorov Flow Solver
Requires Python: >=3.8.10

# KolSol

KolSol is a pseudospectral Kolmogorov flow solver, using a Fourier-Galerkin approach as described by Canuto [[1]](#R1). 
This library contains both `NumPy` and `PyTorch` implementations to allow for autograd-compatible workflows. Please note 
that the implementation of the FFT within `NumPy` is much more efficient so for general usage this version is preferable.

The solver provides numerical solutions to the divergence-free Navier-Stokes equations:

$$
\begin{aligned}
  \nabla \cdot u &= 0 \\
  \partial_t u + u \cdot \nabla u &= - \nabla p + \nu \Delta u + f
\end{aligned}
$$

As a spectral method is employed, using a larger quantity of wavenumbers will reduce the numerical error.
<br>**Note:** Highly accurate simulations can be attained even with relatively few wavenumbers.

- [x] **License:** MIT
- [x] **Python Versions:** 3.8.10+

## **Flowfield:**
<p align='center'>
<img src="media/flowfield.png"/>
</p>

## **Installation:**
You can install KolSol from PyPI as follows

```shell
$ pip install kolsol
```

## **Solver Example:**

```python
import numpy as np
from kolsol.numpy.solver import KolSol

# instantiate solver
ks = KolSol(nk=8, nf=4, re=30.0, ndim=2)
dt = 0.01

# define initial conditions
u_hat = ks.random_field(magnitude=10.0, sigma=2.0, k_offset=[0, 3])

# simulate :: run over transients
for _ in np.arange(0.0, 180.0, dt):
  u_hat += dt * ks.dynamics(u_hat)

# simulate :: generate results
for _ in np.arange(0.0, 300.0, dt):
  u_hat += dt * ks.dynamics(u_hat)

# generate physical field
u_field = ks.fourier_to_phys(u_hat, nref=256)
```

## **Data Generation:**

The given `generate.py` script can be used to generate simulation data for a Kolmogorov flow field, for example:

```bash
$ python generate.py --data-path .data/RE30/results.h5 --resolution 256 --re 30.0 --time-simulation 60.0
```

Running the above command results in the following file structure:

```
data
├── RE30
│   └── results.h5
├── README.md
└── generate.py
```

**Note:** Additional command-line arguments are available for customising simulations.

## **References:**
<a id="R1">**[1]**</a> Canuto, C. (1988) Spectral methods in fluid dynamics. New York: Springer-Verlag.
perform-draw 0.0.1
To return a lsit of randomly drawn numbers from a user defined list of numbers.

# perform_draw
A simple app that will randomly draw a given set up numbers from a list.


## Installation

Run the following to install:
```python
pip install perform_draw
```

## Usage

```command line
python3 perform_draw.py
```
Please enter the total number of balls to be placed in the bag:
You must enter a whole number (integer) greater than 0
15
 
Please enter the total number of balls to be drawn:
You must enter a whole number (integer) greater than 0
and less than 15.
5

Numbers drawn are: [12, 9, 1, 8, 4]


When the object is called, you pass the following variables:

number:     The number of items in the pool to be picked from.
            example:    number = 5 
                        will create a pool [1, 2, 3, 4, 5]

pick:       The number of items to be randomly drawn from the pool.
            example:    pick = 2
                        will return a list of the randomly drawn items, say [4, 2]

put_back:   Whether an item is put back into the pool prior to the next draw.
            Input as a boolean True or False, with a default of False.


## Install Requires

This package uses the following standard library packages:
1. math
2. random

## In Closing

This package has been built as part of my learning Python so may contain coding that is not best practice.  I am happy for more experienced Python users to feedback any areas that could be improved.  Once I get to understand uploading packages to PyPI I will set up development dependencies.
py4uview 0.0.6
Data analysis package for MAXPEEM
Requires Python: >=3.9

# Py4Uview: Tools for Uview images

## Introduction
__Py4Uview__ provides a set of tools for images saved by Uivew, which is used by SPEELEEM in MAXPEEM to save the user's data in format of .dat file. Py4Uview can read the image and metadata from the file saved by Uview software.

## Quick start
### Install
```
python -m pip install py4uview
```
### import
``` python
>>> import py4uview
```
### How to use?

1. use `read_uv_dat()` function to read the data and metadata.
``` ipython
In [1]: import py4uview as pu

In [2]: data = pu.read_uv_dat("./testfiles/LEEM.dat")

In [3]: data.metadata
Out[3]:
{'id': b'UKSOFT2001',
 'size': 104,
 'version': 8,
 'bitsperpix': 16,
 'width': 1024,
 'height': 1024,
 'noimg': 1,
 'attachedRecipeSize': 0,
 'isize': 288,
 ......

In [4]: data.data
Out[4]:
array([[3047, 2880, 2652, ..., 2716, 2630, 2562],
       [2789, 2848, 2862, ..., 2549, 2485, 2655],
       [2808, 2840, 2739, ..., 2640, 2602, 2747],
       ...,
       [3054, 2675, 2656, ..., 1926, 2017, 2021],
       [2885, 2949, 2705, ..., 1907, 1886, 1945],
       [2810, 2688, 2807, ..., 2009, 2025, 2641]], dtype=uint16)
 ```

2. Use `Uview` class method `read_dat()` to read the dat file

```ipython
In [1]: import py4uview as pu

In [2]: data = pu.Uview.read_dat("./testfiles/LEEM.dat")

In [3]: data.attrs
Out[3]:
{'id': b'UKSOFT2001',
 'size': 104,
 'version': 8,
 'bitsperpix': 16,
 'width': 1024,
 'height': 1024,
 'noimg': 1,
 'attachedRecipeSize': 0,
 'isize': 288,
 ......

In [4]: data.data
Out[4]:
array([[3047, 2880, 2652, ..., 2716, 2630, 2562],
       [2789, 2848, 2862, ..., 2549, 2485, 2655],
       [2808, 2840, 2739, ..., 2640, 2602, 2747],
       ...,
       [3054, 2675, 2656, ..., 1926, 2017, 2021],
       [2885, 2949, 2705, ..., 1907, 1886, 1945],
       [2810, 2688, 2807, ..., 2009, 2025, 2641]], dtype=uint16)
```