semvec/pypi-packages huggingface dataset:
image-processing-jvlc 0.0.2
Image Processing Package using Skimage
Requires Python: >=3.5

# image-processing-jvlc

## Description
The **image-processing-jvlc** package provides tools for image processing, including operations for adjustment and visualization. The package’s main functionalities include:

### Main Features
- **Histogram Matching**: Matches the histogram of an image to that of another image.
- **Structural Similarity**: Computes the structural similarity between two images, ideal for detailed comparisons.
- **Resize Image**: Resizes images to specified dimensions.

### Utilities
- **Read Image**: Loads an image from a file.
- **Save Image**: Saves the processed image to a file.
- **Plot Image**: Displays an image.
- **Plot Result**: Compares and displays images side-by-side.
- **Plot Histogram**: Shows the histogram of an image for pixel distribution analysis.

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install **image-processing-jvlc**:

```bash
pip install -i https://test.pypi.org/simple/ image-processing-jvlc==0.0.1
```

## Usage
- **Here’s an example of how to use the package to resize an image and display the result:**
```python
from image_processing_jvlc.processing import transformation
from image_processing_jvlc.utils import io, plot

# Load an image
image = io.read_image("path/to/image.jpg")

# Resize the image
resized_image = transformation.resize_image(image, (200, 200))

# Display the original and resized images
plot.plot_image(image, title="Original Image")
plot.plot_image(resized_image, title="Resized Image")

```

## Author
João Vitor Leal de Castro

## License
This project is licensed under the MIT license.

[MIT](https://choosealicense.com/licenses/mit/)
py-carbone-connect 1.1.2
A Python client for the Carbone API
Requires Python: >=3.7

# CarboneConnect Python Client

A Python client library for interacting with the Carbone API service. This library provides a simple interface to render documents using templates and data.

## Installation

```bash
pip install py-carbone-connect
```

## Features

- Template rendering with data
- Support for both file paths and file-like objects as templates  
- Streaming response support
- Error handling with custom exceptions
- Automatic content type detection

## Usage

### Basic Usage

```python
from carbone_connect import CarboneConnect

# Initialize the client
carbone = CarboneConnect('http://selfhosted.carbone-server.com') # it does not have Auth yet

# Render a template with data
template_path = 'path/to/template.docx'
data = {
    'name': 'John Doe',
    'company': 'ACME Corp'
}

# Generate document
result = carbone.render(template_path, data)

# Save the result
with open('output.docx', 'wb') as f:
    f.write(result)
```

### Streaming Response

```python
# Get a streaming response
response = carbone.render_stream(template_path, data)

# Process the stream
with open('output.docx', 'wb') as f:
    for chunk in response.iter_content(chunk_size=8192):
        f.write(chunk)
```

## API Reference

### CarboneConnect

#### `__init__(api_url: str)`

Initialize the Carbone client with the API URL.

#### `render(template: Union[str, BinaryIO], data: Dict[str, Any], options: Optional[Dict[str, Any]] = None) -> bytes`

Render a template with provided data and return the result as bytes.

- `template`: Path to template file or file-like object
- `data`: Dictionary containing data to render in the template
- `options`: Optional rendering options

#### `render_stream(template: Union[str, BinaryIO], data: Dict[str, Any], options: Optional[Dict[str, Any]] = None) -> requests.Response`

Render a template and return a streaming response.

## Error Handling

The library includes a custom `CarboneError` exception class for handling API-related errors:

```python
try:
    result = carbone.render(template_path, data)
except CarboneError as e:
    print(f'Error: {e}')
```
## Test
### Install development dependencies
pip install -e .[dev]

### Run tests
pytest

### Run tests with coverage report
pytest --cov=carbone_connect --cov-report=term-missing

### Run specific test
pytest tests/test_client.py -k test_initialization

## License

MIT License

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.