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Search Service API Documentation

Repository Overview

This repository provides a robust search service utilizing Elasticsearch and MongoDB, designed for efficient handling of search queries through a web API. It's suitable for developers seeking to integrate advanced search functionalities into their applications.

Files and Modules

Python Scripts

  • common.py: Contains utility functions for logging and JSON operations.
  • config.py: Defines configuration settings like debug state, default port, and host.
  • create_search_index.py: Manages the creation and management of search indices in Elasticsearch.
  • search_api.py: Flask application that processes search API requests.
  • substring_search.py: Handles substring searches and caching mechanisms.
  • test_client.py: Command-line client for testing the search API.
  • python_client.py: A Python client demonstrating how to interact with the API.
  • api_docs.py and app.py: Flask applications serving API documentation.

HTML Templates

  • base.html: Base template providing the basic HTML structure.
  • doc.html: Detailed API documentation accessible via the web.
  • 404.html: Custom page for handling 404 errors.

Setup and Configuration

Ensure MongoDB and Elasticsearch are configured as per settings in config.py. Dependencies should be installed from a requirements.txt file (assumed to exist).

Running the Application

  • Start the Flask app (search_api.py) to serve the search API.
  • Use test_client.py or python_client.py to interact with the API.
  • Access the API documentation through a web browser at the root URL served by app.py or api_docs.py.

Documentation and Testing

  • API documentation is served via Flask and can be customized in doc.html.
  • Use the test_client.py to send queries to your API and validate responses.

Deployment Notes

  • Adjust DEBUG, DEFAULT_PORT, and DEFAULT_HOST in config.py based on your deployment environment.
  • Consider adding security layers, such as SSL/TLS, especially for handling production traffic.

Contribution Guidelines

Encourage contributions through pull requests. Guidelines should include standards for coding, commenting, and testing new features. Issue tracking can be managed via GitHub issues to facilitate community interactions.

Reusability

This documentation and repository setup is designed to be forked and adapted for any developer looking to implement a search API using Elasticsearch. By following the outlined structure, developers can extend the functionality or integrate it with different databases and frontend frameworks.