semvec/pypi-packages huggingface dataset:
sgp 0.3.6
Sparse gaussian process regression

# SGP

Simple gaussian process regression

## Installation

`pip install sgp`

## Getting started

```python
from sgp.variational import VariationalGP as VGP
import numpy as np

X_train = np.linspace(0, 5, 1000)
y_train = np.sin(X_train) * X_train

model = VGP().fit(X_train.reshape(-1, 1), y_train)
X_test = np.linspace(0, 10, 100)
y_test, std_test = model.predict(X_test.reshape(-1, 1), return_std=True)
```
py-timeout 0.0.1
Process based timeout context decorator

# py-timeout

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![PyPI](https://img.shields.io/pypi/v/py-timeout.svg)
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----
py-timeout - pure Python process based decorator that provides execution timeout for Python functions and methods. Since it is not based on signals, py-timeout works fine outside the main thread.

### Prerequisites

py-timeout requires python 3.6 or newer versions to run.

### Installing

Cloning project from git repository

```bash
git clone https://github.com/YADRO-KNS/py-timeout.git
```

Installing from PyPi

```bash
pip3 install py-timeout
```

## Examples

```python
import timeout

@timeout.timeout(duration=0.5)
def foo(value: int) -> None:
    ...

...

@timeout.timeout(duration=0.5)
def bar(self, value: str) -> str:
    ...

```

Decorated function or method will be executed as a sub-process with expected life-time of passed duration value.

```python
import timeout
import time

@timeout.timeout(duration=5)
def foo() -> None:
    while True:
        time.sleep(1)
    
try:
    foo()
except timeout.TimeoutException:
    pass
```

In case if for some reason execution will take longer than expected the process will be terminated and TimeoutException will be raised.

## Versioning

We use [SemVer](http://semver.org/) for versioning.

## Authors

* **[Andrey Abramenko](https://github.com/Strady)**
* **[Sergey Parshin](https://github.com/shooshp)**

See also the list of [contributors](https://github.com/YADRO-KNS/py-timeout/graphs/contributors) who participated in this project.

## License

The code is available as open source under the terms of the [MIT License](LICENSE).