semvec/pypi-packages huggingface dataset:
agent-flow-tdd 0.1.9
Framework para desenvolvimento orientado a testes com agentes de IA
Requires Python: >=3.8

# Agent Flow TDD

<p align="center">
  <img src="assets/flow2.png" alt="Agent Flow TDD Logo" width="400">
</p>

Framework para desenvolvimento orientado a testes usando agentes de IA.

## 🔍 Visão Geral

O Agent Flow TDD utiliza modelos de IA para auxiliar no desenvolvimento orientado a testes, gerando código, testes e documentação com base em prompts.

## 🚀 Início Rápido

```bash
# Clone o repositório
git clone https://github.com/Malnati/agent-flow-tdd.git
cd agent-flow-tdd

# Instale as dependências
make install

# Execute um exemplo
make tdd prompt="Criar API REST em Python" format=json
```

## 📚 Documentação

A documentação completa está disponível no diretório [docs/](docs/):

- **[Visão Geral](docs/overview/README.md)** - Arquitetura e tecnologias
- **[Instalação](docs/installation/README.md)** - Requisitos e configuração
- **[Uso](docs/usage/README.md)** - Comandos e exemplos
- **[Modelos](docs/examples/model-examples.md)** - Exemplos de uso com diferentes modelos
- **[Troubleshooting](docs/troubleshooting/README.md)** - Solução de problemas

## 🔧 Principais Comandos

```bash
# Gerar código/testes a partir de um prompt
make tdd prompt="Criar sistema de login" format=json

# Especificar modelo
make tdd prompt="Implementar ordenação" model=deepseek_local format=python

# Visualizar logs
make logs

# Executar testes
make test
```

## 🤖 Modelos Suportados

### Locais (Offline)
- `tinyllama-1.1b` - TinyLLaMA (1.1B)
- `phi1` - Microsoft Phi-1 (1.3B)
- `deepseek_local` - DeepSeek Coder (6.7B)
- `phi3` - Microsoft Phi-3 Mini

### Remotos (API)
- `gpt-3.5-turbo`, `gpt-4-turbo` - OpenAI
- `claude-3-opus`, `claude-3-sonnet` - Anthropic
- `gemini-pro` - Google

## 📝 Licença

Este projeto está licenciado sob a licença MIT - veja o arquivo [LICENSE](LICENSE) para detalhes.
praline-config 0.1.3
Easy app configuration.
Requires Python: >=3.11

# praline-config

Python app configuration library to instantiate Python objects from various
configuration inputs.

## Purpose

`praline-config` endeavours to make gathering configuration inputs from various
sources as low-friction and straightforward as possible.

## Getting Started

### Installation

```shell
pip install praline-config
```

### Example Usage

Using `praline.config` has a few steps...

1. Write configuration data in a supported format(yaml, toml, dotenv, etc..)
2. Define a dataclass to hold your configuration data
3. Instantiate the configuration object

#### Example YAML Configuration

```yaml
server_address: "www.example.com"
threads: 4
```
#### Example Program

```python
#!/usr/bin/env python3

from dataclasses import dataclass
from praline.config import AppConfigBase


@dataclass
class AppConfig(AppConfigBase):
    server_address: str = None
    threads: int = None


def main():
    app_config: AppConfig = AppConfig.load(config="example.yaml")
    print(f"Server: {app_config.server_address}")
    print(f"Threads: {app_config.threads}")


if __name__ == "__main__":
    exit(main())

```

#### Output

```text
Server: www.example.com
Threads: 4
```

## Supported Configuration Sources

`praline-config` leverages the `python-configuration` package to handle the raw
configuration data, so any format it supports is supported. Additionally,
`praline-config` can handle importing `dotenv` formatted files and binding
environment variable values to fields in your configuration class. Finally, it
can also incorporate values gathered from the CLI or similar through a
dictionary.

See the documentation for [python-configuration](https://pypi.org/project/python-configuration/) for the complete list of supported formats.

## Dependencies

### [python-configuration](https://pypi.org/project/python-configuration/)

> A library to load configuration parameters hierarchically from multiple
> sources and formats

`python-configuration` is an excellent library designed to interface with many
different sources commonly used to store configuration data. We use it here as
an adaptor for the various configuration sources being used as inputs.

### [python-dotenv](https://pypi.org/project/python-dotenv/)

> Python-dotenv reads key-value pairs from a .env file and can set them as
> environment variables. It helps in the development of applications following
> the 12-factor principles.

Used to load `.env` formatted files.
gidapptools 0.8.8
WiP
Requires Python: >=3.9


GidAppTools :superscript:`(Working Title)`
====================================================



.. image:: https://github.com/Giddius/GidAppTools/blob/master/docs/source/_images/gid_app_tools_logo.png?raw=true



===================
Description
===================


⚠️⚠️⚠️⚠️⚠️ PLACEHOLDER ⚠️⚠️⚠️⚠️⚠️


==================
Installation
==================

⚠️⚠️⚠️⚠️⚠️ PLACEHOLDER ⚠️⚠️⚠️⚠️⚠️


==================
Links
==================

Full Documentation
   `giddius.github.io/GidAppTools <https://giddius.github.io/GidAppTools/>`_
smartpaste 0.1.2
Reliable cross-platform clipboard pasting for Python.
Requires Python: >=3.7
Keywords: smartpaste, paste, automation, gui, pyautogui, pyperclip, emoji, clipboard

# SmartPaste

Paste anything, reliably. This Python library uses the system clipboard for cross-platform (Win/Mac/Linux) text input, ensuring emojis and complex characters work correctly. Automatically saves/restores clipboard. Ideal for GUI automation.

## Features

*   **Reliable Pasting:** Uses the system clipboard (copy/paste) which is generally the most robust way to handle complex characters, emojis, and different scripts compared to simulated typing.
*   **Cross-Platform:** Automatically detects the OS (Windows, macOS, Linux) and uses the correct paste shortcut (`Ctrl+V` or `Cmd+V`).
*   **Clipboard Preservation:** Saves the current clipboard content before pasting and restores it afterward, minimizing disruption to the user's workflow.
*   **Error Handling:** Includes basic error handling for clipboard operations.
*   **Configurable Delay:** Allows adding a small delay after pasting to ensure the target application processes the input, especially useful for large text blocks or slower applications.

## Installation

```bash
pip install smartpaste
```

## Usage

Import the package and call it directly with the text you want to paste:

```python
import smartpaste # Import the package
import time

# Give yourself time to focus the target input field
print("Focus the target input field now. Pasting in 5 seconds...")
time.sleep(5)

text_to_paste = "Hello, world! 👋 This text will be pasted reliably."
try:
    # Call the package directly!
    smartpaste(text_to_paste)
    # You can still optionally provide a delay:
    # smartpaste("Some text", delay_after_paste=0.2)
    print("Pasting successful!")
except Exception as e:
    print(f"An error occurred: {e}")

# The original function is still accessible if needed:
# smartpaste.reliable_paste_text("Original function call")
```

**Important:** The script requires a target input field (like a text editor, browser address bar, etc.) to have focus *before* the paste function is called.

## How it Works

The package uses a callable class instance assigned to `sys.modules[__name__]` in its `__init__.py`. When you call `smartpaste(...)`, it invokes the `__call__` method of this instance, which in turn calls the underlying `reliable_paste_text` function.

1.  **Save Clipboard:** Reads and stores the current clipboard content.
2.  **Copy Target Text:** Copies the desired text to the clipboard.
3.  **Paste:** Simulates the platform-specific paste keyboard shortcut (e.g., `Ctrl+V` or `Cmd+V`).
4.  **Delay (Optional):** Pauses briefly to allow the paste action to complete.
5.  **Restore Clipboard:** Copies the original content back to the clipboard.

## Dependencies

*   [pyperclip](https://pypi.org/project/pyperclip/)
*   [PyAutoGUI](https://pypi.org/project/PyAutoGUI/)

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
portalbrasil.intranet 1.0.0b3
Solução de Intranet construída com PortalBrasil
Requires Python: >=3.12
Keywords: CMS, Intranet, Plone, PortalBrasil

# portalbrasil.intranet

Solução de Intranet construída com PortalBrasil & Plone

## Features

TODO: List our awesome features

## Installation

Install portalbrasil.intranet with `pip`:

```shell
pip install portalbrasil.intranet
```
And to create the Plone site:

```shell
make create_site
```

## Contribute

- [Issue Tracker](https://github.com/portal-br/intranet/issues)
- [Source Code](https://github.com/portal-br/intranet/)

## License

The project is licensed under GPLv2.

## Credits and Acknowledgements 🙏

Crafted with care by **This was generated by [cookiecutter-plone](https://github.com/plone/cookieplone-templates/backend_addon) on 2024-07-01 21:48:53**. A special thanks to all contributors and supporters!
usvseg 1.0.2
Python ver of USVSEG
Requires Python: >=3.6

# USVSEG for Python

<img src="./misc/screenshot.png" width="500"> &nbsp;&nbsp;

This is a Python implementation of USVSEG. USVSEG is a GUI-based script for robust segmentation of rodents' ultrasonic vocalizations originally written in MATLAB. 

See [the repository of the original MATLAB version](https://github.com/rtachi-lab/usvseg) for general information about USVSEG. 

## Getting Started

To install the software in an Anaconda virtual environment, run the following command:
```
(base) C:\> conda create -n usvseg python=3.7 numpy scipy matplotlib tqdm pyyaml
(base) C:\> conda activate usvseg
(usvseg) C:\> pip install opencv-python soundfile
(usvseg) C:\> pip install usvseg
```

Alternatively, you can install the software in a Python venv virtual environment by running the following command:
```
C:\> python -m venv usvseg 
C:\> .\usvseg\scripts\activate.bat 
(usvseg) C:\> pip install numpy scipy matplotlib tqdm pyyaml PyQt5 opencv-python soundfile
(usvseg) C:\> pip install usvseg
```

To start the USVSEG GUI, run the following commands in the virtual environment:
```
(usvseg) C:\> usvseg
```

The GUI is compatible to the original USVSEG. You can find the usage of the GUI on [the original site](https://github.com/rtachi-lab/usvseg).

## Contacts
Feel free to open an issue in github for questions and feature requests.

## License
This software is released under the MIT License. See [LICENSE](./LICENSE.txt) for more information. 

This python version of USVSEG is based on [the original MATLAB version](https://github.com/rtachi-lab/usvseg). See [Third Party Notices](./ThirdPartyNotices.txt) for more information. 

## Citation
Original idea and processing procedures of USVSEG have been published in an open-access journal. Please cite this paper when you publish research works with using this software:

> [**USVSEG: A robust method for segmentation of ultrasonic vocalizations in rodents.**](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0228907),            
> Tachibana RO, Kanno K, Okabe S, Kobayasi KI, Okanoya K      
> *[PloS one 15(2) e0228907](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0228907)*