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§RGWML (an AI, Data Science & Machine Learning Library designed to minimize developer cognitive load)

This library simplifies Data Science, Machine Learning, and Artifical Intelligence operations. It’s designed to leverage the best features of RUST, in a manner that is graceful, elegant, and ticklishly fun to build upon.

§Modules Overview

§db_utils

  • Purpose: Query various SQL databases with simple elegant syntax.
  • Features: This module supports the following database connections:
    • MSSQL Server

§csv_utils

  • Purpose: A Comprehensive Toolkit for CSV File Management, in AI/ML pipelines.
  • Features: csv_utils offers a powerful suite of tools designed for efficient and flexible handling of CSV files. Key components include:
    • CsvBuilder: A versatile builder for creating and manipulating CSV files, facilitating:-
      • Easy Initialization: Start with a new CSV or load from an existing file.
      • Custom Headers and Rows: Set custom headers and add rows effortlessly.
      • Advanced Data Manipulation: Rename, drop, and reorder columns, sort data, and apply complex filters like fuzzy matching and timestamp comparisons.
      • Chainable Methods: Combine multiple operations in a fluent and readable manner.
      • Data Analysis Aids: Count rows, print specific rows, ranges, or unique values for quick analysis.
      • Flexible Saving Options: Save your modified CSV to a desired path.
    • CsvResultCacher: Cache the results of CSV file generation for future use.
    • CsvConverter: Convert various data structures, like JSON, into CSV format.

§ai_utils

  • Purpose: Leverage Rust’s concurrency for AI/Graph Theory-based analysis.
  • Features:
    • Conduct complex data analyses and process neural networks in parallel.
    • Utilize Rust’s performance and safety features.
    • Work directly with CSV files, with an elegant syntax, for model training.

§api_utils

  • Purpose: Gracefully make and cache API calls.
  • Features:
    • ApiCallBuilder: Make and cache API calls effortlessly, and manage cached data for efficient API usage.

§loop_utils

  • Purpose: Simplify asynchronous operations in loops.
  • Features:
    • FutureLoop: Handle multiple tasks simultaneously when working with lists or collections, while working with a fluent interface.

§License

This project is licensed under the MIT License - see the LICENSE file for details.

Modules§