semvec/pypi-packages huggingface dataset:
advtorchattacks 2.1.1
A PyTorch library for adversarial attacks, inspired by torchattacks.
Requires Python: >=3.7

# AdvTorchAttacks

**AdvTorchAttacks** is a PyTorch-based library for generating adversarial attacks on deep learning models. It provides implementations of widely used attack methods, enabling user to evaluate model robustness against adversarial perturbations.

##  Features

- Implements **FGSM, PGD, CW, MIFGSM, and AutoAttack** adversarial attack methods.
- Works with PyTorch models.
- Returns **adversarial images, perturbations images**.

---

##  Installation

You can install `advtorchattacks` in two ways:
###  1️ Install from PYPI

```bash

pip install advtorchattacks

```

### 2 Install from GitHub 

```bash

https://github.com/santhosh1705kumar/advtorchattacks

```
basingse 0.6.0
Opinionated Authentication for Flask Apps
Requires Python: >=3.11

# Ba Sing Se


[![PyPI](https://img.shields.io/pypi/v/basingse.svg)](https://pypi.python.org/pypi/basingse)

[![Tests](https://github.com/alexrudy/basingse/workflows/Tests/badge.svg)](https://github.com/alexrudy/basingse/workflows/Tests/)

This is a collection of tools and utilities to use as a base for Flask applications with SQLAlchemy - it helps to not
have to repeat these patterns every time I want to work.


* Free software: BSD license
druida 0.0.86
Metasurface-design artificial intelligence
Requires Python: >=3.7

# DRUIDA
## _The master intelligence for metasurface design_

[![N|Solid](https://cldup.com/dTxpPi9lDf.thumb.png)](https://nodesource.com/products/nsolid)

Druida is an artificial intelligence developed support the metasurfaces design process.

- Generative pipelines for metasurfaces design
The goal is to provide a stable version of the most important algorithmic pipelines to train and deploy AI for metasurfaces design.

## Features

- Deep Neural Network Stack
- GAN Generator Stack
- GAN Discriminator Stack
- Unconditional Diffusion Model
- Conditional Diffusion Model

## Goals
> Configurable AI models
> Easy to interface and use through jupyter notebooks.
> Reproduceable models
> API to future hyperparameters optimization



## Tech

Dillinger uses a number of open source projects to work properly:

- [Python] - Python 3.
- [PyTorch] - The framework to build our algorithms.
- [CLIP] - Pipelione to produce word encoding.


## Installation


Install the dependencies and devDependencies and start the server.
https://pypi.org/project/druida/

```sh
pip install druida

```

## Plugins

Dillinger is currently extended with the following plugins.
Instructions on how to use them in your own application are linked below.

| Plugin | README |
| ------ | ------ |
| Dropbox | [plugins/dropbox/README.md][PlDb] |
| GitHub | [plugins/github/README.md][PlGh] |
| Google Drive | [plugins/googledrive/README.md][PlGd] |
| OneDrive | [plugins/onedrive/README.md][PlOd] |
| Medium | [plugins/medium/README.md][PlMe] |
| Google Analytics | [plugins/googleanalytics/README.md][PlGa] |

## Development

Want to contribute? Great!

Dillinger uses Gulp + Webpack for fast developing.
Make a change in your file and instantaneously see your updates!

Open your favorite Terminal and run these commands.

First Tab:

```sh
node app
```

Second Tab:

```sh
gulp watch
```

(optional) Third:

```sh
karma test
```

#### Building for source

For production release:

```sh
gulp build --prod
```

Generating pre-built zip archives for distribution:

```sh
gulp build dist --prod
```


MIT

**Free Software, Hell Yeah!**

[//]: # (These are reference links used in the body of this note and get stripped out when the markdown processor does its job. There is no need to format nicely because it shouldn't be seen. Thanks SO - http://stackoverflow.com/questions/4823468/store-comments-in-markdown-syntax)

   [dill]: <https://github.com/joemccann/dillinger>
   [git-repo-url]: <https://github.com/joemccann/dillinger.git>
nai-generate 0.1.0
Add your description here
Requires Python: >=3.10

# Dynamic Prompts Image Generator

This application integrates the [dynamicprompts](https://github.com/adieyal/dynamicprompts) library with a Gradio UI to generate images with sequential artist cycling and random general/elements.

## Features

- Sequential artist switching (cyclical sampler)
- Random general and elements selection
- Custom save location for generated images
- Easy-to-use Gradio interface

## How It Works

The application uses the dynamicprompts library to handle prompt generation with different sampling methods:

- **Sequential Artist Switching**: Uses the cyclical sampler (`@`) to cycle through artists one by one
- **Random General and Elements**: Uses the default random sampler to randomly select from general and element options

For example, when you provide a template like:
```
A painting by {artist}, {landscape|portrait|still life}, {vibrant colors|muted tones|black and white}
```

The application will:
1. Replace `{artist}` with `{@artist1|artist2|artist3}` (using the cyclical sampler)
2. Leave the other variant groups with random sampling
3. Generate images with sequential artists and random general/elements

## Installation

1. Clone this repository:
2. Install dependencies:
   ```
   pip install -r requirements.txt
   ```

## Usage

1. Run the application:
   ```
   python app.py
   ```

2. Access the UI in your browser (typically at http://127.0.0.1:7860)

3. Enter the following information:
   - API URL and API Key for your image generation service
   - Model name
   - List of artists (one per line)
   - Prompt template with `{artist}` placeholder and variant options
   - Save location for generated images
   - Number of images to generate

4. Click "Generate Images" to start the generation process

## Example

**Artist List:**
```
Vincent van Gogh
Claude Monet
Salvador Dali
```

**Prompt Template:**
```
A painting by {artist}, {landscape|portrait|still life}, {vibrant colors|muted tones|black and white}
```

This will generate sequential images with:
1. "A painting by Vincent van Gogh, [random selection], [random selection]"
2. "A painting by Claude Monet, [random selection], [random selection]"  
3. "A painting by Salvador Dali, [random selection], [random selection]"
4. "A painting by Vincent van Gogh, [random selection], [random selection]"
5. And so on...

## Notes


To build wheels manually, run the following commands:

```bash
python -m pip install build twine
python -m build
twine check dist/*
twine upload dist/*
```
apipy-logs 0.1.2
A package to create, read and delete your logs
Requires Python: >=3.10

# apipy_logs

![Version](https://img.shields.io/badge/version-0.1.2-blue.svg)
![Python](https://img.shields.io/badge/python-3.10%2B-yellow.svg)
![FastAPI](https://img.shields.io/badge/FastAPI-0.115.8%2B-green.svg)
![SQLAlchemy](https://img.shields.io/badge/SQLAlchemy-2.0.38%2B-red.svg)
![MPL-2.0 license](https://img.shields.io/badge/license-MPL--2.0-cyan.svg)

apipy_logs is a python module to create, read and delete your logs

## How i can use it ?

### Importation

```python
from fastapi_logs.log_manager import LogManager, log_manager
```

### Type of log

```python
LogManager.DEBUG      # Represents a debug message
LogManager.INFO       # Represents an information message
LogManager.WARNING    # Represents a warning message
LogManager.ERROR      # Represents an error message
LogManager.CRITICAL   # Represents a critical message
```

### Methods

```python
log_manager.create_log(level: str, module: str, request: Request, log: str)  # Used to create a log
log_manager.clear_logs()                                                     # Used to to clear the logs
log_manager.get_logs() -> list[str]:                                         # Used to to to get the today logs
```


### Example

```python
from fastapi_logs.log_manager import LogManager, log_manager

@router.get("/create-log")
async def example(
    request: Request,
    db: Session = Depends(get_db),
):
    """
    This endpoint is an example.
    """
    log_manager.create_log(
        LogManager.INFO,
        __file__,
        request,
        f"This is an example"
    )
    return {}
```
detect-app 0.0.5
detect which app the python interpreter is running in
Requires Python: >=3.4
Keywords: dcc, app, application, pipeline

# detect-app

[![PyPI Downloads](https://img.shields.io/pypi/v/detect-app)](https://pypi.org/project/detect-app/)

Detect which app the python interpreter is running in. Useful for cross app scripts

## Supports:
```
Ansible
AutoCAD
Blender
Calibre
Cinema 4D
Clarisse
CryEngine
Flame
FreeCAD
Fusion
Gaffer
Gimp
Houdini
Inkscape
Katana
Krita
Mari
Marmoset
3ds Max
Maya
Modo
MotionBuilder
Natron
Nuke
RV
Revit
Shotgun
Scribus
Softimage
SubstanceDesigner
SubstancePainter
Unreal
```

## Instructions

e.g. prints `Blender` if run in Blender
```python
import detect_app
app_info = detect_app.detect_app()
print(app_info.id)  # e.g. substance_painter
```
right now app_info is very simple
- **id**: `str` a unique identifier for the app, lowercase, underscores, not start with nr
- **action**: `callable` that returns true if run in the app. usually just attempts to import an app specific module
- **get_name()**: `method` to return a pretty name.

## advanced
env variable
`DETECT_APP_FORCE_ID` can be set to the app id, which will force a specific app to be detected. Useful for testing.
apipy-logs-SebastienCozeDev 0.1.0
A package to create, read and delete your logs
Requires Python: >=3.10

# apipy_logs

![Version](https://img.shields.io/badge/version-0.1.0-blue.svg)
![Python](https://img.shields.io/badge/python-3.10%2B-yellow.svg)
![FastAPI](https://img.shields.io/badge/FastAPI-0.115.8%2B-green.svg)
![SQLAlchemy](https://img.shields.io/badge/SQLAlchemy-2.0.38%2B-red.svg)
![MPL-2.0 license](https://img.shields.io/badge/license-MPL--2.0-cyan.svg)

apipy_logs is a python module to create, read and delete your logs

## How i can use it ?

### Importation

```python
from fastapi_logs.log_manager import LogManager, log_manager
```

### Type of log

```python
LogManager.DEBUG      # Represents a debug message
LogManager.INFO       # Represents an information message
LogManager.WARNING    # Represents a warning message
LogManager.ERROR      # Represents an error message
LogManager.CRITICAL   # Represents a critical message
```

### Methods

```python
log_manager.create_log(level: str, module: str, request: Request, log: str)  # Used to create a log
log_manager.clear_logs()                                                     # Used to to clear the logs
log_manager.get_logs() -> list[str]:                                         # Used to to to get the today logs
```


### Example

```python
from fastapi_logs.log_manager import LogManager, log_manager

@router.get("/create-log")
async def example(
    request: Request,
    db: Session = Depends(get_db),
):
    """
    This endpoint is an example.
    """
    log_manager.create_log(
        LogManager.INFO,
        __file__,
        request,
        f"This is an example"
    )
    return {}
```