semvec/pypi-packages huggingface dataset:
lazy-dev-ai 0.2.3
A simple tool for applying chatgpt prompts to code
Requires Python: <4.0,>=3.10

# Lazy Dev AI

This tool is being built as a local or pipeline tool for applying general prompts to a chatgpt endpoint and applying responses to the code in question.

The intent is to be flexible enough for users to apply their own prompts while still providing good examples and foundations to be used out of the box.

## Environment

The following environment variables are supported
`OPENAI_API_KEY` - this is your openai key for use with their endpoints. REQUIRED
`OPENAI_PROJECT` - openai project. OPTIONAL
`OPENAI_ORGANIZATION`- openai organization. OPTIONAL

Option flags will override anything provided as environment variables

## Use
After installing, full help and commands can be found by running `lazy-dev-ai` in the terminal

## Example

`lazy-dev-ai improve-comments ./src/*.py` - this will attempt to improve comments for all python files within the folder `./src`

`lazy-dev-ai generate-docstrings ./src/*.py` - this will attempt to generate docstrings for all functions within the files matching the pattern



## Current commands
pyimfit 1.1
Python wrapper for astronomical image-fitting program Imfit
Requires Python: >=3.10

# Pyimfit

This is a Python wrapper for the astronomical image-fitting program Imfit.

Online documentation: [https://pyimfit.readthedocs.io/en/latest/](https://pyimfit.readthedocs.io/en/latest/).


## Sample Usage

The following assumes an interactive Python session (such as an iPython session
or Jupyter notebook):

    from astropy.io import fits
    import pyimfit
    
    imageFile = "<path-to-FITS-file-directory>/ic3478rss_256.fits"
    imfitConfigFile = "<path-to-config-file-directory>/config_exponential_ic3478_256.dat"

    # read in image data, convert to proper double-precisions, little-endian format
    image_data = fits.getdata(imageFile)

    # construct model from config file; construct new Imfit fitter based on model,;
    model_desc = pyimfit.ModelDescription.load(imfitConfigFile)

    # create an Imfit object, using the previously loaded model configuration
    imfit_fitter = pyimfit.Imfit(model_desc)

    # load the image data and image characteristics and do a standard fit
    # (using default chi^2 statistics and Levenberg-Marquardt solver)
    result = imfit_fitter.fit(image_data, gain=4.725, read_noise=4.3, original_sky=130.14)
    
    # check the fit and print the resulting best-fit parameter values
    if result.fitConverged is True:
        print("Fit converged: chi^2 = {0}, reduced chi^2 = {1}".format(imfit_fitter.fitStatistic,
            result.reducedFitStat))
        bestfit_params = result.params
        print("Best-fit parameter values:", bestfit_params)
togger 24.10.5a1
A python logging frontend using T-Strings
Requires Python: >=3.14

# togger 

T-String Logging Library built ontop of python logging module. 

Logger names are always based on the `__NAME__`

Strings formatting is lazy, so if the log level is not enabled, no stringification takes place. 

```python
# Works with all the standard levels
from togger import debug, fatal

debug"fun times"
fatal"oh noes"

# Works with logging by level int instead of name
from togger import log

level1=log(1)
level1"{level1!r} Error Message"

# Works with custom level names
import logging
logging.addLevelName(51, "SPEW")
from togger import spew

spew"halp! i'm dying here"
```
image-processing-ottojacometo 0.0.1
Realiza o processamento de imagens (combinação e transformação).
Requires Python: >=3.8

# image_processing_ottojacometo

Description. 
The package image_processing is used to:
	Processing:
		- Histogram matching
		- Structural similarity
		- Resize image	
	Utils:
		- Read image
		- Save image
		- Plot image
		- Plot result
		- Plot histogram

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install image_processing

```bash
pip install image_processing_ottojacometo
```

## Usage

```python
from image_processing_ottojacometo.module_name import file_name
file_name.function()
```

## Author
Otto-21

## License
[MIT](https://choosealicense.com/licenses/mit/)
qtcodeedit 0.1.0
A code editing widget for PyQt and PySide
Requires Python: >=3.10

# CodeEdit for Qt and Python

This is a simple code editor widget for Python and Qt supporting multiple languages and color
themes.

## Features

- Syntax and theming support powered by [Pygments](https://pygments.org), so any language and theme
  supported by it can be used
- Hide and show line numbers
- Spaces or tabs for indentation

## Implementation

The CodeEdit widget is based on `QPlainTextEdit` and syntax highlight is provided by a Pygments
based implementation of `QSyntaxHighlighter`. The line number implementation was based on [this
sample](https://doc.qt.io/qt-5/qtwidgets-widgets-codeeditor-example.html) from the Qt docs, with a
bit of cleanup and refactoring on my part.
Syncraa 1.6.1
A tool to manage Plex playlists and import from streaming services
Requires Python: >=3.6

## Syncra

### Syncra is a powerful and intuitive application designed to manage your Plex playlists effortlessly. With a modern and user-friendly interface, it allows you to:

- Import .m3u and .m3u8 playlists into Plex.
- Export your Plex playlists to .m3u files.
- Delete unwanted playlists from your Plex server.
- Convert playlists from popular streaming services like Spotify, Deezer, and Tidal directly into Plex playlists.