dr-web-engine 0.5.1.1

A data retrieval engine based on Playwright.

DR Web Engine

DR Web Engine is an open-source data retrieval engine designed for extracting structured data from web pages using Playwright. It allows users to define queries in JSON5 or YAML format and execute them to retrieve data from websites. The project is highly extensible and can be used for web scraping, data extraction, and automation tasks.

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Features

• Queryable Web: Define data extraction queries in JSON5 or YAML format.
• Playwright Integration: Leverages Playwright for reliable and efficient web automation.
• Extensible: Easily extend the engine by adding new parsers, extractors, or custom logic.
• Command-Line Interface (CLI): Run queries directly from the terminal.
• Docker Support: Use the engine in a containerized environment for easy deployment.

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Installation

Option 1: Install from Source

1. Clone the repository:

   git clone https://github.com/starlitlog/dr-web-engine.git
   cd dr-web-engine
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Install the project in editable mode:

   pip install -e .
   

Option 2: Install via pip

The project is available on PyPI. You can install it directly via pip:

pip install dr-web-engine

Option 3: Run with Docker

1. Build the Docker image:

   docker build -t dr-web-engine .
   

2. Run the container, mounting your local data directory:

   docker run -v $(pwd)/data:/app/data dr-web-engine -q /app/data/query.json5 -o /app/data/output.json
   

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Usage

Command Line Interface (CLI)

To execute queries using the CLI, run:

dr-web-engine -q engine/data/query.json5 -o engine/data/output.json

Available Parameters

• -q or --query: Path to the query file (JSON5 or YAML format).
• -o or --output: Path to the output file where results will be saved.
• -f or --format: Query format (json5 or yaml). Default: json5.
• -l or --log-level: Set the logging level (error, warning, info, debug). Default: error.
• --log-file: Path to a log file. If not specified, logs are printed to stdout.

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Extending the Project

Adding New Parsers

To add a custom parser:

1. Create a new parser in the web_engine/parsers/ directory.
2. Implement a parse() function that takes a file path and returns a parsed query.
3. Register the parser in web_engine/parsers/__init__.py using the get_parser() function.

Example:

# web_engine/parsers/custom_parser.py
def parse(file_path):
    # Custom parsing logic here
    return parsed_query

Adding New Extractors

To add a new extractor:

1. Create a new extractor in the web_engine/extractors/ directory.
2. Implement the extraction logic.
3. Update the execute_query() function in web_engine/engine.py to use the new extractor.

Adding New Query Types

To define a new query type:

1. Create a new query model in web_engine/models.py.
2. Modify the ExtractionQuery class to support the new query type.
3. Add the relevant parsing and extraction logic for the new query type.

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Example Queries

JSON5 Query Example

{
  "@url": "https://example.com",
  "@steps": [
    {
      "@xpath": "//div[@class='item']",
      "@name": "items",
      "@fields": {
        "title": ".//h2",
        "description": ".//p"
      }
    }
  ],
  "@pagination": {
    "@xpath": "//a[@class='next']",
    "@limit": 5
  }
}

YAML Query Example

url: https://example.com
steps:
  - xpath: //div[@class='item']
    name: items
    fields:
      title: .//h2
      description: .//p
pagination:
  xpath: //a[@class='next']
  limit: 5

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Learn More

For additional details and use cases, check out the blog posts at:

• Queryable Web Blog

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Contributing

Contributions are welcome! To contribute, follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bugfix.
3. Submit a pull request with a detailed description of your changes.

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License

This project is licensed under the MIT License. See the LICENSE file for more details.

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Support

If you encounter any issues or have questions, please open an issue on GitHub.

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