Denodo integration

[vishwamartur]

Feature Request: Denodo Integration for Multimodal Trading Bot

Description
Integrate Denodo into the Multimodal Trading Bot repository to enhance data integration, virtualization, and seamless access to various trading-related data sources. This feature would provide a centralized data access layer, enabling the bot to retrieve, analyze, and process information from diverse sources in real time, improving decision-making and trading strategies.

Objective

Leverage Denodo's data virtualization capabilities to consolidate trading data from multiple sources such as financial APIs, databases, and streaming platforms.

Enable efficient querying and processing of data without duplicating or moving it.

Support real-time and historical data access for enhanced trading insights.

Key Features

1. Denodo Connection

Establish a connection to a Denodo Virtual DataPort server using Python.

Provide support for authentication mechanisms (e.g., username/password or token-based).

2. Query Execution

Implement a Python-based interface to execute SQL queries against the Denodo layer.

Support parameterized queries for dynamic data access.

3. Data Integration

Enable seamless access to multiple trading data sources, such as financial market APIs, historical data repositories, and internal databases.

Allow the trading bot to perform cross-database joins and aggregations transparently through Denodo.

4. Real-Time Data Streaming

Incorporate support for consuming real-time data streams via Denodo, leveraging its integration with streaming platforms.

5. Error Handling and Logging

Add robust error handling for connection failures, query errors, and data retrieval issues.

Provide detailed logging for debugging and monitoring.

Benefits

Simplifies data integration and eliminates the need for complex ETL processes.

Enables faster prototyping and testing of trading strategies.

Reduces the time and effort required to manage multiple data sources.

Improves scalability and maintainability of the trading bot's data access layer.

Proposed Approach

1. Add a denodo_integration.py module to the repository.

2. Use the jaydebeapi or pyodbc library to establish a connection to Denodo.

3. Create utility functions for executing queries and retrieving results in a structured format.

4. Document the setup process, including prerequisites (e.g., Denodo JDBC driver) and configuration steps.

Requirements

Access to a Denodo Virtual DataPort server.

Installation of required Python libraries (e.g., jaydebeapi, pyodbc).

Denodo JDBC driver for Python integration.

Additional Notes

Consider implementing a caching mechanism to optimize query performance for frequently accessed data.

Explore Denodo’s API capabilities for advanced functionalities, such as metadata retrieval and dynamic schema discovery.

References

Denodo Python Integration Guide

jaydebeapi Library Documentation

pyodbc Library Documentation

Let me know if you'd like assistance in implementing this feature!