semvec/pypi-packages huggingface dataset:
btpy 2.0.4
bluetooth library for beacons, classic and low-energy devices
Keywords: bluetooth library

## btpy
this is a wrapper around
- [bleak](https://github.com/hbldh/bleak) for low-energy support
- [beacontools](https://github.com/citruz/beacontools) for beacon support
- [bluez](http://www.bluez.org/) for classic support

### how to ...
#### .. install
```shell
pip3 install btpy
# or (this is not guaranteed to be stable)
pip3 install git+https://github.com/nbdy/btpy
```

#### ... to use it
```python
from btpy import LEDevice, Beacon, ClassicDevice

le_results = LEDevice.scan(4)

beacon_results = Beacon.scan(5)

classic_results = ClassicDevice.scan(6)
```

##### TODO
- [ ] Tests
csv-excel-matcher 1.6
Allows users to select and compare columns from two files (either CSV or Excel). The application matches records between the two selected columns and provides both matched and unmatched records, which can then be saved to an Excel file

# CSV and Excel Matcher

CSV and Excel Matcher is a GUI application built with Tkinter that allows users to select and compare columns from two files (either CSV or Excel). The application matches records between the two selected columns and provides both matched and unmatched records, which can then be saved to an Excel file.

## Features

- Load and select columns from CSV or Excel files
- Match records between selected columns
- Display the total number of matched and unmatched records
- Save results to an Excel file with separate sheets for matched and unmatched records

## Installation

To install CSV and Excel Matcher, you can use pip:

```bash
pip install csv-excel-matcher==1.6
```

## To run as an application.
```bash
csv_excel_matcher
```
or
```bash
python -m csv_excel_matcher
```
if above command did not start your application then try these, 

Create *.py file at desired directory.
```python
from csv_excel_matcher import CSVExcelMatcherApp
CSVExcelMatcherApp()
```
These line of code will help to execute the program. 

## In the GUI:
- Click "Browse" to select the first file (CSV or Excel).
- Select the column from the first file that need to be compared
- Click "Browse" to select the second file (CSV or Excel).
- Select the column from the second file that need to be compared
- Click "Match Records" to find common and unmatched records.
- Click "Save Results" to save the results to an Excel file.

## Support
If you encounter any issues or have any questions, feel free to contact me at hari.nikesh.r.cce@gmail.com.

## License
This project is licensed under the MIT License.
Flask-TUI-Editor 1.0.0
Toast UI Markdown Editor Integration for Flask-WTF.

# Flask-TUI-Editor

[Toast UI Markdown Editor](https://ui.toast.com/tui-editor) Integration for Flask-WTF.

## Installation
To install Flask-TUI-Editor:

```
pip install flask-tui-editor
```
### Usage

Check [example](example/) project and [documentation](https://flask-tui-editor.readthedocs.io/en/latest/).

## Licenses

Both Flask-TUI-Editor and [Toast UI Editor](https://github.com/nhn/tui.editor) licensed with MIT License.
fob 0.0.5
a library for building configurable, repeatable experiments
Requires Python: >=3.9

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Worfklow](https://github.com/andrewyates/fob/workflows/pytest/badge.svg)](https://github.com/andrewyates/fob/actions)
[![PyPI version fury.io](https://badge.fury.io/py/fob.svg)](https://pypi.python.org/pypi/fob/)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) 
# fob
*fob* is a library for building configurable, repeatable experiments. It comes with a `fob` command for running and inspecting experiment pipelines, which are built from configurable *ingredients*.

## Ingredient
An ingredient is the basic building block of a pipeline. Ingredients are configured using their `__init__`method, which allows unified Python and CLI APIs. They need to:

- Subclass the `Ingredient`class, which allows the ingredient to be recognized (and provides many convenience methods) 
- Decorate their `__init__` function with `@configurable`, which makes the arguments passed to `__init__` accessible from the `self.cfg` dict. This allows the arguments to be configured from the CLI and tracked for artifact provenance
- Decorate select methods with `@cacheable`, which saves the method's output based on (1) the method's arguments and (2) the configuration in `self.cfg`. When possible, decorated methods load output from disk rather than recomputing it. The `@cacheable` decorator takes an output type as an argument, such as `@cacheable(NumpyOutput)`. Other valid types include `PathOutput`, `PickleOutput`, `StringOutput`, etc.

## Command
The `fob` command can run arbitrary methods within a pipeline. It uses the syntax:
```
fob <class> [method] [method-args] [--output DIR] [--search-path DIR] [--config config-args]
```
where
- `method`can be a `method` of `class` or of an object in `class.cfg`
- `method-args` is a space-separated list of `key=val`arguments to pass to method 
- `--output`specifies a directory to store *@cacheable* output (and to find it in)
- `--search-path` specifies directories to look for `@cacheable` output in
- `config-args` is a space-separated list of `key=val`arguments to initialize `class`
example-package-ryanjob42 0.0.2
A small example package
Requires Python: >=3.8

# Packaging Tutorial
Working through Python's packaging tutorials for uploading to PyPI.
The specific tutorials I'm working through are linked below.

- https://packaging.python.org/en/latest/tutorials/packaging-projects/
- https://packaging.python.org/en/latest/guides/publishing-package-distribution-releases-using-github-actions-ci-cd-workflows/
- https://docs.github.com/en/actions/deployment/security-hardening-your-deployments/configuring-openid-connect-in-pypi
lcz 0.1.7
Simplified Leela Chess Zero (aka lc0 aka lcz) with Python
Requires Python: >=3.10

# Lcz

> Python bindings for Leela Chess Zero, simplified

Provides a simple interface around the original [LCZero python bindings](https://github.com/LeelaChessZero/lc0)

## Usage

```python
import lcz

lcz.eval(fens=[
    'rnbqkbnr/pp2pppp/2p5/3p4/3PP3/8/PPP2PPP/RNBQKBNR w KQkq - 0 3',
    'r2qkbnr/pp2pppp/2n5/3p1b2/3P1B2/5N2/PPP2PPP/RN1QKB1R w KQkq - 4 6'
], weights_path='/path/to/lcz.pb.gz') # if not specified, uses the pre-packaged 'maia-1900.pb.gz'

# [{'b1d2': 0.008045054972171783, # [0, 1] probabilities (softmaxed)
#   'b1a3': 5.8913348766509444e-05,
#   'b1c3': 0.21684584021568298,
#    ...
#   },
#   {'b1d2': 0.015918008983135223,
#    'b1a3': 0.0013550063595175743,
#    'b1c3': 0.09632844477891922,
#    ...
#   }]

```

## Heads up

Expect it to take ages to build, as the whole C++ lib gets compiled. You can use `pip install -v` to check progress