semvec/pypi-packages huggingface dataset:
open-nn-python 0.3.1
A Neural Network implementation from scratch in Python
Requires Python: >=3.6

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  <img src="https://user-images.githubusercontent.com/85283622/206227131-e25b01d8-4c35-4770-a4e9-728655766858.png"></a>
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# OpenNN
A Neural Network implementation from scratch in Python.
In this repository, Artificial Neural Networks are implemented from scratch. From scratch meaning without using external machine learning libraries. The API structure is similar to the Tensorflow Keras API.

[![PyPI Latest Release](https://img.shields.io/pypi/v/open-nn-python.svg?style=flat&logo=pypi)](https://pypi.org/project/open-nn-python/)
[![v0.3.1](https://img.shields.io/badge/version-v0.3.1-red.svg?style=flat&logo=numpy)](https://github.com/NotShrirang/OpenNN)
[![License: MIT](https://img.shields.io/badge/license-MIT-brightgreen.svg?style=flat&logo=license)](https://github.com/NotShrirang/OpenNN/blob/main/LICENSE)
[![Language: Python](https://img.shields.io/badge/language-python-blue.svg?style=flat&logo=python)](https://www.python.org/)

## Installing OpenNN from PyPI :

```sh
pip install open-nn-python
```

## Importing OpenNN:

```sh
import nn
```
teext 0.1.9
Typing extensions extensions
Requires Python: >=3.8
Keywords: python,typing

# teext – typing extensions extensions

Package which provides useful types.

### [Documentation](https://wearepal.github.io/teext/)

## Examples

### Value-constraint types without runtime overhead

These types are most useful in conjunction with static type checkers like mypy.

```python
import teext as tx

def f(x: tx.PositiveInt) -> None:
    print(x)

a = 5
assert tx.is_positive_int(a)
f(a)  # OK
f(7)  # works at runtime but mypy gives error

assert tx.is_positive_int(-3)  # AssertionError
```