Draft:Grapa (programming language)
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Last edited by Bearcat (talk | contribs) 0 seconds ago. (Update) |
Comment: In accordance with Wikipedia's Conflict of interest policy, I disclose that I have a conflict of interest regarding the subject of this article. Chris.Matichuk (talk) 22:20, 26 July 2025 (UTC)
| Grapa | |
|---|---|
| Paradigm | Grammar-based, imperative, functional |
| Designed by | Grapa Development Team |
| First appeared | 2001 |
| Stable release | Current
/ 2025 |
| Typing discipline | Dynamic, strong |
| OS | Cross-platform (Windows, macOS, Linux) |
| License | Open source |
| Website | grapa-dev |
| Major implementations | |
| C++ | |
| Influenced by | |
| YACC, BTree systems | |
| Influenced | |
| None | |
Grapa is a modern, grammar-based programming language and data processing platform designed for unlimited precision, true parallelism, and seamless Python integration. It features two core innovations: runtime grammar mutation and a weighted BTree storage engine. Grapa is used in production-grade ETL workflows and AWS Lambda environments, making it suitable for data engineers, educators, researchers, and developers requiring high-performance data processing and language experimentation.
History and Development
[edit]Grapa was developed as an experimental language to test a novel database engine design. The project originated from the question: "Could I build a language that can mutate its own grammar at runtime, with a storage engine to support fragmented, update-efficient columnar access?" The language evolved from early cross-platform BTree systems developed for mainframe simulation and terminal screen capture storage.
The weighted BTree concept emerged from the need to store fragmented columnar data with in-place updates, leading to the development of nodes that carry "weight" (byte length) instead of just count, enabling fast partial reads, inserts, and updates.
Core Innovations
[edit]Runtime Grammar Mutation
[edit]Grapa's most distinctive feature is its ability to mutate its own grammar at runtime using mutable $RULE variables. This enables scoped language evolution and meta-programming, making Grapa a "language for building languages." The system uses executable runtime syntax-mutable grammar, which is unique among programming languages.
Weighted BTree Storage Engine
[edit]The weighted BTree is a novel index structure supporting fragmented column-store access with in-place updates. Unlike traditional BTrees that balance based on node counts, Grapa's weighted BTree balances based on byte weights and fragment offsets, enabling efficient partial reads, inserts, and updates across COL, ROW, and GROUP storage models.
Key Features
[edit]- Unlimited Precision: Arbitrary-precision math for integers, floats, and time values
- True Parallelism: Production-ready parallel ETL and data processing with map/reduce/filter operations
- Unified File/Database API: Seamless navigation between file systems and databases
- Python Integration: GrapaPy module for idiomatic Python scripting and data workflows
- Executable BNF & Mutable Grammar: Define and experiment with grammars at runtime
- Cross-Platform Compatibility: Support for Windows, macOS, Linux, and AWS environments
- Built-in Grep Functionality: Advanced pattern matching with PCRE2 regex, Unicode support, and parallel processing
Architecture
[edit]Grapa is built from the ground up to support both BigEndian and LittleEndian formats, ensuring true cross-platform compatibility. The language selectively integrates established open source libraries (OpenSSL, PCRE2, BLST, FLTK) while maintaining entirely original architecture and execution models.
The execution model uses dynamic code execution with execution trees and meta-programming capabilities. The unified path system allows seamless navigation between file systems, databases, and other storage types.
Use Cases
[edit]Grapa is particularly well-suited for:
- Data Engineering & ETL: High-throughput data processing and automation
- Language Research: Compiler theory, grammar evolution, and meta-programming experimentation
- Education: Teaching compiler concepts and language prototyping
- High-Precision Computing: Applications requiring unlimited precision mathematics
- Parallel Processing: Scenarios where Python's GIL or precision limits are bottlenecks
Implementation
[edit]Grapa is implemented in C++ and provides both a command-line interface and Python integration through GrapaPy. The language supports multiple execution modes including interactive, script execution, and command-line operation.