semvec/pypi-packages huggingface dataset:
voidsafe 0.2.0
A null-safe-like approach to Python programming language.
License: MIT
Keywords: voidsafe,nullsafe,none-aware,python


        `VoidSafe` is a package that brings a '_null-safe-like_' approach to Python3-written 
        scripts and applications. It provides software developers with resources to apply 
        `void-safety` principles to their codebase, allowing `safe` operations to be performed 
        on `Potentially Unsafe Instances [2.1]` , which helps assuring that your software will 
        be able to handle many `memory-access` problems at runtime.
numpynet 0.1.0
Simple neural network implementation with numpy
License: MIT
Keywords: neural,network,numpy,simple,convolution,dense

# numpynet
Convolutional Neural Network written from scratch using numpy with API similar to tensorflow. Library was compared with tensorflow versions of network (`demo` directory) and achieved very close results.

## Implemented Elements

### Layers
- `InputLayer`
- `DenseLayer`
- `BiasLayer`
- `ActivationLayer (relu, leaky reLu, sigmoid, tanh, sin)`
- `DropoutLayer`
- `FlattenLayer`
- `Conv2DLayer (with bias & stride)`
- `Pool2DLayer (max, min)`
- `Padding2DLayer`
- `Crop2DLayer`
- `SoftmaxLayer`

### Losses
- `MSE`
- `CCE`

### Initializers
- `ConstantInitializer`
- `RandomNormalInitializer`
- `RandomUniformInitializer`
- `GlorotUniformInitialization`

### Metrics
- `CategoricalAccuracy`

### Callbacks
- `ModelCheckpoint`
- `EarlyStopping`

## Usage Example

### Definition
```
layers = [
    numpynet.layers.InputLayer((28, 28, 1)),
    numpynet.layers.Conv2DLayer(32, kernel_size=3, stride=1),
    numpynet.layers.ActivationLayer('relu'),
    numpynet.layers.FlattenLayer(),
    numpynet.layers.DenseLayer(128),
    numpynet.layers.BiasLayer(),
    numpynet.layers.ActivationLayer('relu'),
    numpynet.layers.DropoutLayer(0.5),
    numpynet.layers.DenseLayer(10),
    numpynet.layers.BiasLayer(),
    numpynet.layers.SoftmaxLayer(),
]

model = numpynet.network.Sequential(layers)
```

### Compilation
```
model.compile(
    loss='cce',
    metrics=['categorical_accuracy']
)
```

### Fitting
```
checkpoint_callback = numpynet.callbacks.ModelCheckpoint('checkpoint.dat')

history = model.fit(
    train_x,
    train_y,
    validation_data=(test_x, test_y),
    learning_rate=0.001,
    epochs=10,
    callbacks=[checkpoint_callback],
)
```

### Predicting
```
predictions = model.predict(test_x)
```
pytest-environment 0.0.0
Pytest Environment
License: MIT
Requires Python: >=3.9,<4.0

# Pytest Environment

[![PyPI](https://img.shields.io/pypi/v/pytest-environment.svg)][pypi status]
[![Status](https://img.shields.io/pypi/status/pytest-environment.svg)][pypi status]
[![Python Version](https://img.shields.io/pypi/pyversions/pytest-environment)][pypi status]
[![License](https://img.shields.io/pypi/l/pytest-environment)][license]

[![Read the documentation at https://pytest-environment.readthedocs.io/](https://img.shields.io/readthedocs/pytest-environment/latest.svg?label=Read%20the%20Docs)][read the docs]
[![Tests](https://github.com/56kyle/pytest-environment/workflows/Tests/badge.svg)][tests]
[![Codecov](https://codecov.io/gh/56kyle/pytest-environment/branch/main/graph/badge.svg)][codecov]

[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)][pre-commit]
[![Black](https://img.shields.io/badge/code%20style-black-000000.svg)][black]

[pypi status]: https://pypi.org/project/pytest-environment/
[read the docs]: https://pytest-environment.readthedocs.io/
[tests]: https://github.com/56kyle/pytest-environment/actions?workflow=Tests
[codecov]: https://app.codecov.io/gh/56kyle/pytest-environment
[pre-commit]: https://github.com/pre-commit/pre-commit
[black]: https://github.com/psf/black

## Features

- TODO

## Requirements

- TODO

## Installation

You can install _Pytest Environment_ via [pip] from [PyPI]:

```console
$ pip install pytest-environment
```

## Usage

Please see the [Command-line Reference] for details.

## Contributing

Contributions are very welcome.
To learn more, see the [Contributor Guide].

## License

Distributed under the terms of the [MIT license][license],
_Pytest Environment_ is free and open source software.

## Issues

If you encounter any problems,
please [file an issue] along with a detailed description.

## Credits

This project was generated from [@cjolowicz]'s [Hypermodern Python Cookiecutter] template.

[@cjolowicz]: https://github.com/cjolowicz
[pypi]: https://pypi.org/
[hypermodern python cookiecutter]: https://github.com/cjolowicz/cookiecutter-hypermodern-python
[file an issue]: https://github.com/56kyle/pytest-environment/issues
[pip]: https://pip.pypa.io/

<!-- github-only -->

[license]: https://github.com/56kyle/pytest-environment/blob/main/LICENSE
[contributor guide]: https://github.com/56kyle/pytest-environment/blob/main/CONTRIBUTING.md
[command-line reference]: https://pytest-environment.readthedocs.io/en/latest/usage.html