semvec/pypi-packages huggingface dataset:
pyloess 0.1.0
A fast implementation of the LOESS algorithm in Python
Requires Python: >=3.8

# PyLOESS

This is a vectorized implementation of LOESS that supports polynomial models.
It is fast enough for bootstrap resampling for computing prediction intervals.

## Installation

```bash
pip install pyloess
```

## Usage

```python
from pyloess import loess

# Generate some data
import numpy as np
np.random.seed(0)

x = np.random.uniform(0, 10, 100)
y = np.sin(x) + np.random.normal(0, 0.1, 100)
x_new = np.linspace(0, 10, 1000)

# Evaluate the loess model
y_new = loess(x, y, eval_x=x_new, span=0.33, degree=2)
```
pyUTSAlgorithms 0.1.3
pyUTSAlgorithms (Unevenly Spaced Time Series Algorithms) Python package computes rolling statistics for uneven time series data.
Requires Python: >=3.8

# pyUTSAlgorithms (Unevenly Spaced Time Series Algorithms)

Unevenly Spaced Time Series: Moving Averages and Other Rolling Operators
This repository started as a conversion of the code from this [one](https://github.com/andreas50/utsAlgorithms).
Right now the library contains more algorithms that help while dealing with Unevenly Spaced Time Series, for more details check the [here](#documentation).

## Running unit tests

Several unit tests were written to validate some corner cases.
The unit tests were written in [unittest](https://docs.python.org/3/library/unittest.html).
Run the following commands to execute the unit tests.

```bash
python -m unittest
```

## Documentation

This library was documented using the google style docstring, it can be accessed [here](https://mariolpantunes.github.io/pyUTSAlgorithms/).
Run the following commands to produce the documentation for this library.

```bash
pip install pdoc
pdoc --math -d google -o docs src/uts
```

## Instalation

To install the library locally, simple execute the following commands:

```bash
python3 -m venv venv
source venv/bin/activate
python -m pip install --upgrade pip
pip install .
```
You can also use the PyPI repository for easy access to the library:

```txt
pyUTSAlgorithms>=0.1.3
```

## Authors

* **Mário Antunes** - [mariolpantunes](https://github.com/mariolpantunes)

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details

## Status

![Python CI](https://github.com/mariolpantunes/uts/workflows/Python%20CI/badge.svg)

MIT License

Copyright (c) 2020 Mário Antunes

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
prrr 0.1.2
A simple CLI tool to help you write better PRs.
Requires Python: <4.0.0,>=3.9.8

# prr

This is a simple tool to help you manage your pull requests.

## Requirements

This project requires and OpenAPI token to exist in your environment variables.

```shell
OPENAI_API_KEY=your_api_key
``` 

## Installation

```bash
poetry install && poetry update
```

## Usage

```shell
prr pr gen
```

## Help

```bash
 Usage: prr [OPTIONS] COMMAND [ARGS]...                                                                                                                                         
                                                                                                                                                                                
╭─ Options ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ --help                                                       Show this message and exit.                                                                                     │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─ Commands ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ init                                                                                                                                                                         │
│ pr                             Generate a Pull Request                                                                                                                       │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
```
listslinked 0.0.2
A simple package for linked lists
Requires Python: >=3.8

# Linked Lists Python Module

## Overview

The listslinked Python Module provides implementations for various types of linked lists in Python. Linked lists are fundamental data structures commonly used in computer science and programming.

This module includes implementations for the following types of linked lists:
- Singly Linked List
- Doubly Linked List
- Circular Singly Linked List
- Circular Doubly Linked List

Each type of linked list offers different capabilities and can be used for various applications.

## Installation

You can install the module using pip:

```
pip install listslinked
```

## Usage

To use the linked lists in your Python code, import the desired type of linked list from the module. For example, to use the Singly Linked List:

```python
from listslinked import SinglyLinkedList

# Create a new singly linked list
linked_list = SinglyLinkedList()

# Insert elements
linked_list.insert_at_beginning(5)
linked_list.insert_at_end(10)

# Print the linked list
current = linked_list.get_head()
while current:
    print(current.data)
    current = current.next
```

Similarly, you can use the other types of linked lists provided by the module.

## Contributing

Contributions are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request on [GitHub](https://github.com/SpyderRex/linked-lists).

## License

This project is licensed under the MIT License - LICENSE file for details.