semvec/pypi-packages huggingface dataset:
monochrome-dionny 0.0.4
Transformar as cores de uma imagem em tons de cinza ou binarizadas em preto e branco

# Monochrome Dionny
Esse pacote permite transformar as cores de uma imagem em tons de cinza ou binarizadas em preto e branco.

## Descrição
O objetivo da criação desse pacote foi para experienciar e aprender a como utilizar o PyPI.

O pacote contem duas funções:
 - Acinzentar imagem: Transforma as cores da imagem em tons de cinza
 - Binarizar imagem: Transforma as cores da imagem em preto e branco

A imagem será salva com o sufixo "cinza" ou "binarizada" de acordo com a função utilizada.

## Instalação
```
pip install monochrome-dionny
```

## Uso
### Acinzentar imagem
```python
import monochrome_dionny as monodio

camimho_imagem = r"C:\Users\UserA\Imagens\dio.jpg"

monodio.acinzentar_imagem(camimho_imagem)
```

### Binarizar imagem
```python
import monochrome_dionny as monodio

camimho_imagem = r"C:\Users\UserA\Imagens\dio.jpg"

monodio.binarizar_imagem(camimho_imagem)
```

## Cuidados
Certifique-se de adiconar um "r" antes do caminho da imagem, isso evitará problemas com as "\\".

```python
camimho = r"C:\Users\UserA\Imagens\dio.jpg"
```
aimigrate 0.2.2
AI tool for migrating code
Requires Python: >=3.10

# AIMigrate

AIMigrate helps migrate code to maintain compatability when one of your dependency packackages changes


## Installation
```
pip install aimigrate
```

### Configure LLM Provider

AIMigrate is compatabile with openai, gemini, and anthropic models. To use these tools you will need an API key. 

- For Gemini, get your API key from: https://aistudio.google.com/apikey
- For OpenAI, get your API key from: https://platform.openai.com/settings/organization/api-keys
- For Anthropic, get your API key from: https://www.anthropic.com/api

Once you have these keys, we recommend using [python-dotenv](https://pypi.org/project/python-dotenv/) for managing your keys. Store them as environment variables `GEMINI_API_KEY`, `OPENAI_API_KEY`, or `ANTHROPIC_API_KEY` respective.

**Running open weight (i.e., local) models**:
You can also use `ollama` to run models locally. To start open a terminal run `ollama serve`. If it is your first time running the model you'll need to pull it first (e.g., `ollama run llama3`). You will likely need to [increase the context window](https://github.com/ollama/ollama/blob/main/docs/faq.md#:~:text=How%20can%20I%20specify%20the%20context%20window%20size%3F).

**DO NOT UNDER ANY CIRCUMSTANCE SHARE OR UPLOAD TO GITHUB YOUR API KEY!**

## Usage

Let's say we have a project *Zombiesim* that we want to migrate from Starsim v1 (v1.0.3) to v2 (v2.2.0). Typical usage is to migrate all the files in a folder to a new folder:
```py
import starsim as ss
import aimigrate as aim

aim.migrate(
    starsim = ss, # can also be the path to the folder, which must be the cloned repo (not from pypi)
    from_version = 'v1.0.3', # can be any valid git tag or hash
    to_version = 'v2.2.0', # can be any valid git tag or hash
    model = 'openai:gpt-4o', # use aisuite provider:model syntax
    source = '/path/to/your/code/folder', # folder with the code to migrate
    dest = '/path/to/migrated/folder', # folder to output migrated code into
)
```

## Tests
```
uv run --group dev pytest -v test_*.py
```
django-base64-bytesio 0.0.8
Input a base64 string and return BytesIO
Requires Python: >=3.8

<!--
 * @Author: Bryan x23399937@student.ncirl.ie
 * @Date: 2025-03-01 12:23:20
 * @LastEditors: Bryan x23399937@student.ncirl.ie
 * @LastEditTime: 2025-03-01 14:11:42
 * @FilePath: /cpp-project-library/README.md
 * @Description: 
 * 
 * Copyright (c) 2025 by Bryan Jiang, All Rights Reserved. 
-->
# django-base64-bytesio

This library provides functionality to decode base64 encoded files and return them as `BytesIO` objects.

## Scenario

When your website using base64 as image format. And front-end will upload some images to your django back-end.
In django framework mostly using file object to recieve image. In this moment, you may need to convert base64 to a bytes io object. Meantime, In our scenario I don't need to save my file on server. Just upload AWS s3 bucket that will fine.

## Installation

You can install the library via pip:

```bash
pip install django-base64-bytesio
```

## Usages

Example of using the library
```
from django_base64_bytesio import DjangoBase64BytesIO

data = "data:image/jpeg;base64,..."
decoder = DjangoBase64BytesIO()
file_object, filename = decoder.decode(data)
```