semvec/pypi-packages huggingface dataset:
aws-cdk-common 0.1.58
A shared package for common modules and constants for AWS Lambda applications
License: MIT
Requires Python: <4.0,>=3.11

# AWS CDK Common

`aws-cdk-common` is a shared package for common modules and constants for AWS Lambda applications based on AWS CDK. It provides essential tools and configurations for managing AWS resources efficiently.

## Python Environment

### Installing Poetry
[Poetry](https://python-poetry.org/) is a tool to manage Python projects in a deterministic way. Follow the instructions to set up your environment.

### Installing Required Modules
To install required modules, run:
```bash
poetry install --no-root
```

### Development Environment Setup
To install required modules for development, run:
```bash
poetry install --with dev --no-root
```

### Activating the Virtual Environment
To activate the virtual environment:
- **Linux/macOS**:
  ```bash
  source $(poetry env info --path)/bin/activate
  ```
- **Windows (PowerShell)**:
  ```powershell
  . $(poetry env info --path)/Scripts/activate
  ```

### Pre-commit Hooks
Install pre-commit hooks to ensure consistent code quality:
```bash
poetry run pre-commit install
```

### Code Formatting and Quality Checks
- Format code with **Black**:
  ```bash
  poetry run black .
  ```
- Sort imports with **isort**:
  ```bash
  poetry run isort .
  ```
- Check code quality with **Flake8**:
  ```bash
  poetry run flake8 .
  ```

## Tests

### Unit Tests
Run unit tests:
```bash
poetry run pytest tests/unit
```

### Integration Tests
Run integration tests:
```bash
poetry run pytest tests/integration
```

### All Tests
Run all tests:
```bash
poetry run pytest
```

## Deployment
To deploy the application, use:
```bash
python app_setup.py deploy
```
For a faster deployment without installations or tests, use:
```bash
python app_setup.py fast_deploy
```

## Setup
Ensure that the `aws-common` repository is cloned and updated as part of the setup process.
pdfimageextractor 0.1.1
Extract high-quality images from PDF files while preserving metadata
License: MIT
Requires Python: >=3.8
Keywords: extraction, images, pdf

# PDF Image Extractor

A tool to extract high-quality images from PDF files while preserving metadata and positioning information.

## Features

- Extracts images in their original quality without recompression
- Preserves image metadata including DPI and positioning
- Detects and skips duplicate images
- Generates detailed JSON metadata file
- Sorts images by their position on the page

## Installation

```bash
pip install pdfimageextractor
```

## Usage

```bash
pdfextractimages <PDF_FILE> [OUTPUT_FOLDER]
```

Arguments:
- `PDF_FILE`: Path to the PDF file to process
- `OUTPUT_FOLDER`: Optional directory to save extracted images (defaults to PDF_FILE_images)

## Output

The tool creates:
- Original quality images extracted from the PDF
- A `image_metadata.json` file containing detailed information about each image