semvec/pypi-packages huggingface dataset:
pytypest 1.0.1
Type-safe and maintainable fixtures and parametrization for pytest.
Requires Python: >=3.8
Keywords: pytest,tests,testing,framework,fixtures

# pytypest

Type-safe and maintainable fixtures and parametrization for [pytest](https://github.com/pytest-dev/pytest).

Features:

+ 100% type safe.
+ Great IDE integration, go-to-definition always takes you in the right place.
+ Test parametrization that is readable even with many arguments.
+ Plug-and-play integration with pytest.
+ No vendor-lock, you can use only the features you need and don't touch the rest.
+ Fixtures can be cached, and you are in control of for how long.
+ Fixtures can accept arguments.

Check out [motivation](https://pytypest.orsinium.dev/motivation.html) if you want to know more about why this project was born.

## Installation

```bash
python3 -m pip install pytypest
```

## Usage

Fixtures are regular helper functions that `yield` their result and do teardown afterwards:

```python
from typing import Iterator
from pytypest import fixture

@fixture
def get_user(anonymous: bool) -> Iterator[User]:
    u = User(anonymous=anonymous)
    u.save()
    yield u
    u.delete()

def test_user() -> None:
    u = get_user(anonymous=False)
    assert u.anonymous is False
```

Compared to built-in pytest fixtures, these are explicit, type-safe, can accept arguments, support go-to-definition in IDE, and can be used as context managers. And like pytest fixtures, they are cached and can be scoped to the module or the whole session.

Read more in the **documentation**: [pytypest.orsinium.dev](https://pytypest.orsinium.dev/).
PyAudioFX 0.0.1
This is a python package useful for the automated audio preprocessing and feature extraction.
Requires Python: >=3.6

PyAudioFX

This is a python module for automated audio pre-processing and feature extraction. 

# Fetures
Automated auto-preprocessing effects like trim, time strech and remix

Automated calculation of statistical descriptors for audio data

Automated feature extraction for both single audio file and multiple audio files in a directory

Works on all formats of audio data



# basic_audio_processor(path,effect,hop_length=512,rate=1)

example- increase the speed of the audio by 1.5x times.

basic_audio_processor(r"C:\Users\sairam\Downloads\audio preprocessing\aah shit.mp3",'time-strech',512,1.5)

# statistical_analyser(path)

example- get statistical descriptors for audio data

statistical_analyser(r"C:\Users\sairam\Downloads\audio preprocessing\aah shit.mp3")

# AutomatedExtractor_single(path)

example- perform feature extraction on a single data

AutomatedExtractor_single(r"C:\Users\sairam\Downloads\audio preprocessing\aah shit.mp3")

# Automated Extractor_multiple(path)

example- perform feature extraction on multiple data given using glob function

path=glob.glob(r"\archive (2)\set_a\*.wav")
AutomatedExtractor_multiple(path)
square-shapez 0.0.1
This is module to calculate shapes area.
Requires Python: >=3.6
Keywords: shapes area

# Shapes square library #

## What is this? ##
The module allows you to work with shapes, calculate perimetr and area.

### Using ###


Using the library is as simple and convenient as possible:

Let's import it first:\
First, import everything from the library (use the `from `...` import *` construct).

Examples of all operations:

Create circle shape, using `radius`:

    circle = Circle(radius=radius)

Create triangle shape, using `side_1`, `side_2`, `side_3`:

    triangle = Triangle(a=side_1, b=side_2, c=side_3)


You can calculate perimetr for each shape, `using get_perimetr()`:

    shape_perimetr = shape.get_perimetr()

You can calculate are for each shape, `using get_area()`:

    shape_area = shape.get_area()

Also, you can use `calculate_area()` which takes as input a parameter of type Shape (an abstract class for all shapes)

    shape_area = calculate_area(shape=some_shape)
aws-assume-role-otp 0.3
A CLI tool to assume a role on AWS using MFA
Requires Python: >=3.7

# aws-assume-role-otp

AWS Assume Role OTP allows you to assume a role on AWS at the same time it generates the MFA token.

## Installation

```
pip install aws-assume-role-otp
```

## Usage

```bash
aws-assume-role-otp

```

### Add role
```bash
aws-assume-role-otp --add-role

```

### Remove role
```bash
aws-assume-role-otp --remove-role

```

### First time configuration

The first time you run this tool, it will ask you to inform:

* AWS Access Key ID
* AWS Secret Access Key
* Serial MFA Secret. [How to register device](https://docs.aws.amazon.com/singlesignon/latest/userguide/how-to-register-device.html)
* MFA ARN
* Roles and profiles


## Build locally

```
pip install build
python -m build
pip install dist/aws_assume_role_otp-0.3-py3-none-any.whl
```


# Changelog

## [0.3] - 2023-10-02

### Added

- Allow to add or remove roles