semvec/pypi-packages huggingface dataset:
pyva-acoustics 1.2.1
Python toolbox for vibroacoustic simulation
Requires Python: >=3.7

# pyva
Python toolbox for vibroacoustics

This toolbox is the code extension for the book 
A. Peiffer: Vibroacoustic Simulation: In Introduction to Statistical Energy Analysis and Hybrid Methods, John Wiley, 2022

[Wiley book details](https://www.wiley.com/en-us/Vibroacoustic+Simulation%3A+An+Introduction+to+Statistical+Energy+Analysis+and+Hybrid+Methods-p-9781119849841)

[Order book](http://www.wiley.com/buy/9781119849841)

This toolbox allows the reader to follow the examples in the book. People that are interested in vibroacoustic simulation with a focus on 
statistical energy analysis (SEA) and hybrid methods (hybrid FEM/SE), to perform SEA simulation without heavy licence costs.

# Documentation

Direct link to the documentation can be found on [pyva.eu](https://pyva.eu)

# Contributing to pyva

The current version is the baseline for further extensions. It was mainly driven by providing examples and test cases for the book
on [Vibroacoustic Simulation](http://www.wiley.com/buy/9781119849841). Contributions are highly welcome.
The following extensions shall be included mid-term

A major step is a GUI development! Here, suggestions would be very helpful. I am currently thinking about a combination of pyqt 
and vtk, eventually integrating cadquery, opencascade, gmesh or any other option to handle geometry and meshes. 
However, I am still scanning the options. 

## Main Module

- Engineering units contraints, e.g. setting pressure or velocity level of one SEA subsystem

## Coupling Package

- point junctions
- inclusion of beams in line junctions

## Properties Package

### Geometrical Property Module

- Further Beam Cross Sections

### Material Module

- Anisotropic materials
- Porous Absorber Models (Biot - JCA)

### Structural Property Module

- Linear Laminates
- Sandwich

## Systems Package

- Singly curved shells
- Doubly curved shells
- Infinite layers with porous Biot material
- Elastic Solid as infinite layer

## Load package

- Diffuse wave field as load
- Cross spectral density excitation
 
# Author page and contact information

If you are not sure if pyva suits your needs in the current status feel free to contact me via.
[Author Page - Alexander Peiffer](https://docpeiffer.com)
misprint 0.2.0
A logging filter that 'misprints' your secrets
Requires Python: >=3.8

# misprint

[![PyPI - Version](https://img.shields.io/pypi/v/misprint.svg)](https://pypi.org/project/misprint)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/misprint.svg)](https://pypi.org/project/misprint)

An integration with the Python standard library's [logging module](https://docs.python.org/3/library/logging.html)
that masks secrets in log messages before they are emitted. This project
was heavily inspired by an excellent [blog post](https://relaxdiego.com/2014/07/logging-in-python.html)
which has been updated/adapted for modern Python versions.

Misprint is fully type-annotated for easier integration with [mypy](https://mypy.readthedocs.io/en/stable/).

---

## **Table of Contents**

- [Installation](#installation)
- [License](#license)
- [Usage](#usage)
  - [`misprint.Misprinter`](#misprintmisprinter)
  - [standard library logging integration](#misprintmisprintfilter)

## Installation

```console
pip install misprint
```

## License

`misprint` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html)
license.

## Usage

### `misprint.Misprinter`

You can use the `Misprinter` class to redact exact string matches or regular expressions
within a string:

```python
misprinter = Misprinter(token=["my_secret_token", re.compile(r"^ghp_\w+")])

assert misprinter.mask("this is my_secret_token") == "this is ****"
assert (
    misprinter.mask("github tokens: ghp_abc123 ghp_def456")
    == "github tokens: **** ****"
)
```

If you need to add a mask for new data to an existing instance then you can use the
`add_mask_for` method:

```python
misprinter = Misprinter()
assert misprinter.mask("a secret1234") == "a secret1234"

misprinter.add_mask_for("secret1234")
assert misprinter.mask("a secret1234") == "a ****"
```

You can also initialise your `Misprinter` instance with `use_named_masks=True`
if you would like to be able to identify what data has been masked more easily:

```python
misprinter = Misprinter(use_named_masks=True)
misprinter.add_mask_for("another_secret", name="database password")

assert (
    misprinter.mask("printing another_secret")
    == "printing <'database password' (value removed)>"
)
```

### `misprint.MisprintFilter`

`misprint` also provides a `logging.Filter` subclass, which integrates with the
Python standard library's `logging` module to enable redaction of log messages.

`MisprintFilter` is a subclass of `Misprinter`, so inherits all of the methods
detailed above. This is useful, as the filter can be connected to the loggers
that are configured for a program at startup, and new secrets can be
conveniently added to the filter to be redacted in the logs:

```python
import logging
import sys

import misprint

logging.basicConfig(
    datefmt="[%X]",
    handlers=[logging.StreamHandler(sys.stderr)],  # plus others
)

misprinter = misprint.MisprintFilter()

for handler in logging.getLogger().handlers:
    handler.addFilter(misprinter)

A_TOKEN = "asdf1234"

misprinter.add_mask_for(A_TOKEN)

log.error("Bad token: %s", A_TOKEN)
```
particular 0.0.1
Extremely accurate N-Body simulator for basic physical research. The dependencies are kept at a bare minimum.
Requires Python: >=3.8

# MD-MC

Direct and MC combination simulations. Code, raw data an plots used for publishing direct simulations of Bose-Einstein-Condensates.

# How does it work? 

The workings are quite simple: 

1.) Simulate a MC simulation to obtain an equilibrium example 
2.) Simulate your trajectory