Expand description
§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.
- CsvBuilder: A versatile builder for creating and manipulating CSV files, facilitating:-
§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.