semvec/pypi-packages huggingface dataset:
piah 0.1.1
automatically parse PDF's and texts to dataclasses
Requires Python: >=3.10
Keywords: ai, dataclass, parser, piah

# piah

[![PyPI - Version](https://img.shields.io/pypi/v/piah.svg)](https://pypi.org/project/piah)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/piah.svg)](https://pypi.org/project/piah)

-----

Piah automatically parse the data from PDF's or texts based only in the [dataclass](https://docs.python.org/3/library/dataclasses.html#module-dataclasses) that you provide and return the same [dataclass](https://docs.python.org/3/library/dataclasses.html#module-dataclasses) fullfilled with the values.
Piah is based in the [OxyParser](https://github.com/oxylabs/OxyParser/)

**Table of Contents**

- [Installation](#installation)
- [Example](#example)
- [TODO](#todo)
- [Know Issues](#know-issues)
- [License](#license)

## Installation

```console
pip install piah
```

## Example
```python
from piah import Piah
from dataclasses import dataclass

@dataclass
class Person:
  name: str
  age: int

parser = Piah("gpt-3.5-turbo")
result = parser.parse("Hello Iam python and I have 33 years old", Person)
```
to parse PDF's:
```python
result = parser.parse("example.pdf", Person)
#or
result = parser.parse(Path("example.pdf"), Person)
```

## TODO
- [ ] Write docstrings
- [ ] Improve allowed types
- [ ] Improve system prompt

## Know Issues
Seems that `piah` don't pass every time in the test, because the LLM don't parse
correctly every time large PDF's

## License

`piah` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
compare-meshes 0.1.0
Compare meshes and polydata for regression testing.
Requires Python: >=3.8
Keywords: emscripten, itkwasm, wasi, webassembly

# compare-meshes

[![PyPI version](https://badge.fury.io/py/compare-meshes.svg)](https://badge.fury.io/py/compare-meshes)

Compare meshes and polydata for regression testing.

## Installation

```sh
pip install compare-meshes
```
compare-meshes-emscripten 0.1.0
Compare meshes and polydata for regression testing.
Requires Python: >=3.8
Keywords: emscripten, itkwasm, webassembly

# compare-meshes-emscripten

[![PyPI version](https://badge.fury.io/py/compare-meshes-emscripten.svg)](https://badge.fury.io/py/compare-meshes-emscripten)

Compare meshes and polydata for regression testing. Emscripten implementation.

This package provides the Emscripten WebAssembly implementation. It is usually not called directly. Please use the [`compare-meshes`](https://pypi.org/project/compare-meshes/) instead.


## Installation

```sh
import micropip
await micropip.install('compare-meshes-emscripten')
```

## Development

```sh
pip install hatch
hatch run download-pyodide
hatch run test
```
compare-meshes-wasi 0.1.0
Compare meshes and polydata for regression testing.
Requires Python: >=3.8
Keywords: itkwasm, wasi, webassembly

# compare-meshes-wasi

[![PyPI version](https://badge.fury.io/py/compare-meshes-wasi.svg)](https://badge.fury.io/py/compare-meshes-wasi)

Compare meshes and polydata for regression testing. WASI implementation.

This package provides the WASI WebAssembly implementation. It is usually not called directly. Please use [`compare-meshes`](https://pypi.org/project/compare-meshes/) instead.


## Installation

```sh
pip install compare-meshes-wasi
```

## Development

```sh
pip install pytest
pip install -e .
pytest

# or
pip install hatch
hatch run test
```
robotic-lib 0.0.1
A small example package
Requires Python: >=3.8

## OPTIMA ROBOTICS LIBRARY
    You can install this library for control Android-Arduino
## Installation
    You can install this package via Pip install robotic-lib
## Copyright
    This library is the intellectual property of Optima Robotics. All rights reserved. No one is allowed to violate the policies of Optima Robotics.
## About
    Developed by Dark.
svg.charts 7.3.1
Python SVG Charting Library
Requires Python: >=3.8

.. image:: https://img.shields.io/pypi/v/svg.charts.svg
   :target: https://pypi.org/project/svg.charts

.. image:: https://img.shields.io/pypi/pyversions/svg.charts.svg

.. image:: https://github.com/jaraco/svg.charts/actions/workflows/main.yml/badge.svg
   :target: https://github.com/jaraco/svg.charts/actions?query=workflow%3A%22tests%22
   :alt: tests

.. image:: https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/charliermarsh/ruff/main/assets/badge/v2.json
    :target: https://github.com/astral-sh/ruff
    :alt: Ruff

.. image:: https://readthedocs.org/projects/svgcharts/badge/?version=latest
   :target: https://svgcharts.readthedocs.io/en/latest/?badge=latest

.. image:: https://img.shields.io/badge/skeleton-2024-informational
   :target: https://blog.jaraco.com/skeleton

``svg.charts`` is a pure-python library for generating charts
and graphs using Scalable Vector Graphics.

Acknowledgements
================

``svg.charts`` depends heavily on lxml and cssutils. Thanks to the
contributors of those projects for stable, performant, standards-based
packages.

Thanks to Sean E. Russel for creating the SVG::Graph Ruby
package from which this Python port was originally derived.

Thanks to Leo Lapworth for creating the SVG::TT::Graph
package which the Ruby port was based on.

Thanks to Stephen Morgan for creating the TT template and SVG.

Getting Started
===============

``svg.charts`` has some examples (taken directly from the reference implementation)
in `tests/samples.py
<https://github.com/jaraco/svg.charts/blob/master/tests/samples.py>`_.
These examples show sample usage of the various chart types. They should provide a
good starting point for learning the usage of the library.

An example of using ``svg.charts`` in a `CherryPy
<http://www.cherrypy.org/>`_ web app can be found in `jaraco.site.charts
<https://github.com/jaraco/jaraco.site/blob/master/jaraco/site/charts.py>`_.
If the site is working, you can see the `rendered output here
<https://www.jaraco.com/charts/plot>`_.

``svg.charts`` also provides `API documentation
<http://svgcharts.readthedocs.io/en/latest>`_.

Contributing
============

This project is `hosted at Github
<https://github.com/jaraco/svg.charts>`_.

Please use that site for
reporting bugs and requesting help. Patches and contributions
of any kind are encouraged.
jaraco.nxt 2.2.1
Logo Mindstorms NXT Routines
Requires Python: >=3.8

.. image:: https://img.shields.io/pypi/v/jaraco.nxt.svg
   :target: https://pypi.org/project/jaraco.nxt

.. image:: https://img.shields.io/pypi/pyversions/jaraco.nxt.svg

.. image:: https://github.com/jaraco/jaraco.nxt/actions/workflows/main.yml/badge.svg
   :target: https://github.com/jaraco/jaraco.nxt/actions?query=workflow%3A%22tests%22
   :alt: tests

.. image:: https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/charliermarsh/ruff/main/assets/badge/v2.json
    :target: https://github.com/astral-sh/ruff
    :alt: Ruff

.. .. image:: https://readthedocs.org/projects/PROJECT_RTD/badge/?version=latest
..    :target: https://PROJECT_RTD.readthedocs.io/en/latest/?badge=latest

.. image:: https://img.shields.io/badge/skeleton-2024-informational
   :target: https://blog.jaraco.com/skeleton

LEGO Mindstorms NXT Bluetooth API in Python

Overview
--------

``jaraco.nxt`` implements the LEGO Mindstorms NXT Bluetooth API in Python.

The ``jaraco.nxt`` library also can take advantage of the `jaraco input
<https://pypi.org/project/jaraco.input>`_
package.  To include it as part of the install, use the command
``pip install jaraco.nxt[input]``.

Getting Started
---------------

``jaraco.nxt`` provides a message class for sending and receiving messages
with the Lego NXT device.  First pair the device with your PC by following
the instructions included with the device.  Then, determine the COM port
to which it is connected.  The `hello world example
<https://github.com/jaraco/jaraco.nxt/tree/main/examples/get_battery_voltage.py>`_
is to retrieve the battery
voltage.  `Browse the other examples
<https://github.com/jaraco/jaraco.nxt/tree/main/examples/>`_ for
more inspiration.

For more information, read the docstrings of the modules in the packages.

Modules of interest are

* jaraco.nxt.messages: implements the messages defined by
  the NXT Bluetooth protocol.
* jaraco.nxt.controller: demonstrates how to link input from
  a joystick to messages controlling the motors.  Uses jaraco.input.
vet 0.1.1.post4
A poetry plugin for establishing chain of trust
Requires Python: <4.0,>=3.10

<div align="center">

# `vet`

A poetry plugin for establishing chain of trust  
Inspired by [cargo-vet](https://github.com/mozilla/cargo-vet)

</div>

## Installation

Depending on how you installed poetry, you may need to install `vet` in a different way.

If you used the self-installer:
    
```bash
poetry self add vet
```

If you used pipx:

```bash
pipx inject poetry vet
```

If you used pip:

```bash
pip install vet
```

For more information and troubleshooting, see the [poetry plugin installation docs](https://python-poetry.org/docs/plugins/#using-plugins).

## Usage

### Initialization

Initialize `vet` in your project:

```bash
poetry vet init
```

This will create a [`chain-of-trust` directory](chain-of-trust/) in your project.
See the [generated README](chain-of-trust/README.md) for more information on how to configure `vet`.


### Running checks

To audit your project dependencies, run:

```bash
poetry vet
```

Dependencies are trusted to be either **safe to run** or **safe to deploy**. 
Upon initialization, all dependencies in the `poetry.lock` file are exempt, deemed **safe to run**.

To vet dependencies as **safe to deploy**, run:

```bash
poetry vet --safe-to-deploy
```

For an example of how to run `vet` in GitHub CI, see [the `ci.yml` file in this repository](https://github.com/irgolic/vet/blob/main/.github/workflows/ci.yml#L15).

### Importing Audits

Modify the `config.toml` file as per the example in [the generated README](chain-of-trust/README.md#imports).

Then run:

```bash
poetry vet lock
```

This will download the audits from the trusted sources specified in the `config.toml` file and store them in the `import.lock` file.

### Auditing

Audit dependencies manually by adding entries in the `audits.toml` file as per the example in [the generated README](chain-of-trust/README.md#audit-file-auditstoml).

## Background

This was thrown together in an afternoon; after the [xz backdoor](https://boehs.org/node/everything-i-know-about-the-xz-backdoor) I thought we need better visibility into our dependency trees.