semvec/pypi-packages huggingface dataset:
typed-trie 0.1.0
A pure Python implementation of a trie with typing.
License: MIT
Requires Python: >=3.11,<4.0
Keywords: trie

# typed-trie

A pure Python implementation of [trie](https://en.wikipedia.org/wiki/Trie) with typing.

## Usage

```
>>> from typed_trie import Trie
>>>
>>> trie = Trie()
>>> trie["how to cook"] = 1
>>> trie["how to swim"] = 2
>>> trie["who is john doe"] = 3
>>> list(trie.items_by_prefix("how to"))
[('how to cook', 1), ('how to swim', 2)]
>>> del trie["how to cook"]
```

## License

`typed-trie` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
pymediatracker 0.1.3
Asynchronous python client for MediaTracker.
License: MIT
Requires Python: >=3.8,<4.0
Keywords: mediatracker,api,async,client

# PyMediaTracker

Asynchronous python client for MediaTracker.
This package allows you to interact with MediaTracker API

## Installation

```bash
pip install pymediatracker
```

## Attributions
- [@timmo001](https://github.com/timmo001) for source of inspiration with his [aiolyric package](https://github.com/timmo001/aiolyric).
- [@ludeeus](https://github.com/ludeeus) for his generator class.

#

⭐️ this repository if you found it useful ❤️

<a href="https://www.buymeacoffee.com/jonkristian" target="_blank"><img src="https://bmc-cdn.nyc3.digitaloceanspaces.com/BMC-button-images/custom_images/white_img.png" alt="Buy Me A Coffee" style="height: auto !important;width: auto !important;" ></a>
tspydistributions 0.1.3
Location Scale Family Statistical Distributions
License: MIT
Requires Python: >=3.10,<3.13

# Welcome!

The tspydistributions package implements a number of location-scale based statistical distributions parameterized in terms of their mean and standard deviation, in addition to the skew and shape parameters.

# Installation

Currently, due to certain version requirements of the dependencies, it's best to create a new virtual environment with Python >=3.10 and <3.13, after which:

`
pip install tspydistributions
`

# Documentation

Full documentation available [here](https://tspydistributions.readthedocs.io/en/latest/).

MIT License

Copyright (c) 2023 tspydistributions

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.
PMYning 0.1.1
A process mining tool
License: MIT
Requires Python: >=3.11,<4.0
Keywords: process,mining

# Welcome to PMYning

This package aims to lower the barier for data scientist to get started with process mining.

## Installation
Install via PyPI
```shell
pip install pmyning
```

Install via Poetry
```shell
poetry add pmyning
```

Install via Conda
```shell
conda install -c conda-forge pmyning
```