semvec/pypi-packages huggingface dataset:
georaptor 3.0.0
A Python Geohash Compression Tool
License: MIT
Keywords: geohash, optimizer, compression, location

GeoRaptor: Python Geohash Compression Tool
===========================================

Geohash is a geocoding system invented by Gustavo Niemeyer and placed into the public domain. It is a hierarchical spatial data structure which subdivides space into buckets of grid shape, which is one of the many applications of what is known as a Z-order curve, and generally space-filling curves.

Geohash creation for a polygon at a given precision level could result in a huge set of geohashes.

**GeoRaptor** creates the best combination of geohashes across various levels to represent a polygon, by starting from the highest level and iterating till the optimal blend is brewed. Result accuracy remains the same as that of the starting geohash level, but data size reduces considerably for large polygons, thereby improving speed and performance.

Following is a sample of what georaptor does

.. image:: https://raw.github.com/ashwin711/georaptor/master/images/sgp_input.png
   :width: 480
   :height: 320
.. image:: https://raw.github.com/ashwin711/georaptor/master/images/sgp_output.png
   :width: 480
   :height: 320


*Input:* 1096 geohashes at precision 6 for Singapore.

*Output:* 414 geohashes with a mix of precision 5 and 6.

Performance
-----------

**Input sample size:** 18,992,425

**Output:** 220,375

**Total execution time:** 35.8013219833 seconds

Usage
-----

$ georaptor <input> --output <output> --minlevel <minlevel> --maxlevel <maxlevel>


Example
-------

$ georaptor sample.csv

OR

$ georaptor sample.csv --output sample_out.csv --minlevel 3 --maxlevel 4


Installation
------------

To install georaptor, simply: ::

    $ pip install georaptor


License:
--------


Licensed under the Apache License, Version 2.0. ::

    Copyright 2024 Ashwin Nair <https://www.linkedin.com/in/ashwin-nair7>

   Licensed under the Apache License, Version 2.0 (the "License");
   you may not use this file except in compliance with the License.
   You may obtain a copy of the License at

       http://www.apache.org/licenses/LICENSE-2.0

   Unless required by applicable law or agreed to in writing, software
   distributed under the License is distributed on an "AS IS" BASIS,
   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   See the License for the specific language governing permissions and
   limitations under the License.
sentence-store 0.4.2
Tool to extract and store sentence embeddings to a fast and scalable vector db
License: MIT

# sentence_store
### A tool to extract and store sentence embeddings to a fast and scalable vector db

#### Install:

pip3 install sentence_store

#### Usage:

```
from sentence_store.main import Embedder
 e = Embedder(cache_name='embedder_test')
    sents = [
        "The dog barks to the moon",
        "The cat sits on the mat",
        "The phone rings",
        "The rocket explodes",
        "The cat and the dog sleep"
    ]
    e.store(sents)
    q = 'Who sleeps on the mat?'
    rs = e(q, 2)
    for r in rs: print(r)

    print('TIMES:', e.times)
    return True
```

Enjoy,
Paul Tarau
openapi-lookup 0.1.1
A command-line interface to for the open api listings from public-apis/public-apis.
License: MIT
Requires Python: <4.0,>=3.8

<div align="center">

# OpenAPI Lookup

A collection of tools and scripts for making the life of security analysts
easier, faster, and more efficient.

  <img src="https://raw.githubusercontent.com/xransum/openapi-lookup/main/docs/images/logo.png" width="20%" style="border-radius: 10%">

  <br />

[![Tests](https://github.com/xransum/openapi-lookup/workflows/Tests/badge.svg)][tests]
[![Codecov](https://codecov.io/gh/xransum/openapi-lookup/branch/main/graph/badge.svg)][codecov]
[![PyPI](https://img.shields.io/pypi/v/openapi-lookup.svg)][pypi_]
[![Python Version](https://img.shields.io/pypi/pyversions/openapi-lookup)][python version]

[![Python Black](https://img.shields.io/badge/code%20style-black-000000.svg?label=Style)](https://github.com/xransum/openapi-lookup)
[![Read the documentation at https://openapi-lookup.readthedocs.io/](https://img.shields.io/readthedocs/openapi-lookup/latest.svg?label=Read%20the%20Docs)][read the docs]
[![Downloads](https://pepy.tech/badge/openapi-lookup)](https://pepy.tech/project/openapi-lookup)
[![License](https://img.shields.io/pypi/l/openapi-lookup)][license]

</div>

## Installation

Install `openapi-lookup` from the Python Package Index:

```bash
$ pip install openapi-lookup
```

## Usage

```bash
$ openapis --help
```

## Contributing

Contributions are welcome! Please see [CONTRIBUTING.md][contributing] for more
information.

## License

Distributed under the terms of the [MIT][license] license, `openapi-lookup` is
free and open source software.

## Issues

If you encounter any problems, please [file an issue][issues] along with a
detailed description.

<!-- github-only -->

[pypi_]: https://pypi.org/project/openapi-lookup/
[python version]: https://pypi.org/project/openapi-lookup
[read the docs]: https://openapi-lookup.readthedocs.io/
[tests]: https://github.com/xransum/openapi-lookup/actions?workflow=Tests
[codecov]: https://app.codecov.io/gh/xransum/openapi-lookup
[@xransum]: https://github.com/xransum
[nox]: https://nox.thea.codes/
[poetry]: https://python-poetry.org/
[constraints file]: https://pip.pypa.io/en/stable/user_guide/#constraints-files
[file an issue]: https://github.com/xransum/openapi-lookup/issues
[keyword-only parameter]: https://docs.python.org/3/glossary.html#keyword-only-parameter
[nox.sessions.session.install]: https://nox.thea.codes/en/stable/config.html#nox.sessions.Session.install
[nox.sessions.session.run]: https://nox.thea.codes/en/stable/config.html#nox.sessions.Session.run
[pip install]: https://pip.pypa.io/en/stable/reference/pip_install/
[pip]: https://pip.pypa.io/
[pipx]: https://pipxproject.github.io/pipx/
[license]: https://github.com/xransum/openapi-lookup/blob/main/LICENSE
[contributor guide]: https://github.com/xransum/openapi-lookup/blob/main/CONTRIBUTING.md
cleanvoice 0.0.2
A Fast Speech Enhancement toolkit using Conv-TasNet
License: MIT
Requires Python: >3.5

## CleanVoice

A Fast Speech Enhancement toolkit using [Conv-TasNet (Yi Luo, Nima Mesgarani)](https://arxiv.org/abs/1809.07454)

> Only works with 16kHz audio.

## Install

```shell
pip install cleanvoice
```

## Usage


Audio file

```python
from cleanvoice import cleanvoice
from scipy.io.wavfile import write as write_wav

audio_data = cleanvoice("audio.wav")
write_wav("audio-cleaned.wav", 16000, audio_data)
```

NumPy Array as input

```python
from cleanvoice import cleanvoice
from scipy.io.wavfile import write as write_wav
import librosa

y, _ = librosa.load("audio.wav", mono=True, sr=16000)
audio_data = cleanvoice(y)
write_wav("audio-cleaned.wav", 16000, audio_data)
```

## License

`Apache-2.0`
screenshotct 0.11
Screenshots - ctypes
License: MIT
Keywords: screenshots


# Screenshot with ctypes

## Tested against Windows 10 / Python 3.11 / Anaconda

### pip install screenshotct

```PY
import cv2
from screenshotct import take_screenshot
import time
from ctypes_window_info import get_window_infos

for q in get_window_infos():
    print(q)

# hwnd
ir = take_screenshot(
    hwnd=2100816,
    crop=(0, 0, 0, 100),
    show_fps=True,
    brg_to_rgb=False,
    ignore_exceptions=True,
    client=True,
)

# first screen
# ir = take_screenshot(
#     hwnd='0',
#     crop=(0, 0, 0, 100),
#     show_fps=True,
#     brg_to_rgb=False,
#     ignore_exceptions=True,
#     client=True,
# )

# all screens
# ir = take_screenshot(
#     hwnd="all",
#     crop=(0, 0, 0, 100),
#     show_fps=True,
#     brg_to_rgb=False,
#     ignore_exceptions=True,
#     client=True,
# )

fps = 0
last_time = time.time()
for _ in range(1000):
    try:
        pic = next(ir)
        fps += 1
        cv2.imshow("pic", pic[0])
        if cv2.waitKey(1) & 0xFF == ord("q"):
            break
    except Exception as e:
        print(e)
print(f"\n\n\n{fps / (time.time() - last_time)}\n")
cv2.destroyAllWindows()
```
py3office 0.3.0
提供python3版本的自动化办公常用处理方法
License: MIT
Keywords: pdf, office, python3

<img src="./logo.jpeg" />

# [py3office](https://github.com/zxl20070701/py3office)
⏰ 提供python3版本的自动化办公常用处理方法

<p>
    <a href="https://github.com/zxl20070701/py3office" target='_blank'>
        <img alt="GitHub repo stars" src="https://img.shields.io/github/stars/zxl20070701/py3office?style=social">
    </a>
</p>

## 使用

首先需要进行安装：

```
pip3 install py3office
```

然后就可以使用了，下面列出所有可用内容：

- [handler 基本辅助相关](https://github.com/zxl20070701/py3office/blob/master/docs/handler.md)
- [PDF文件相关操作](https://github.com/zxl20070701/py3office/blob/master/docs/pdf.md)
- [OCR相关操作](https://github.com/zxl20070701/py3office/blob/master/docs/ocr.md)

## 版权

MIT License

Copyright (c) [zxl20070701](https://zxl20070701.github.io/notebook/home.html) 走一步，再走一步