| --- |
| license: mit |
| task_categories: |
| - text-generation |
| language: |
| - en |
| tags: |
| - code |
| - Ruby |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| # Ruby-Code-Large |
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| **Ruby-Code-Large** is a large-scale corpus of Ruby programming language source code comprising **331,743 code samples** stored in `.jsonl` format. The dataset is designed to support research and development in large language model (LLM) pretraining, static analysis, web application development, and software engineering automation within the Ruby ecosystem. |
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| By offering a substantial, language-focused dataset, Ruby-Code-Large enables targeted experimentation in dynamic programming, object-oriented design, and rapid application development—areas where Ruby is widely used, particularly in web frameworks and scripting. |
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| Ruby-Code-Large addresses the lack of large, curated, Ruby-specific datasets, enabling focused research on expressive syntax, metaprogramming, and high-level abstractions. |
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| ## 1. Dataset Composition |
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| ### Programming Language |
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| Ruby |
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| ### Total Size |
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| 331,743 code samples |
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| ### File Format |
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| `.jsonl` (JSON Lines) |
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| ## 2. Content Overview |
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| The dataset captures a wide spectrum of Ruby programming constructs, ranging from foundational syntax to advanced metaprogramming and framework-oriented patterns. |
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| ### 2.1 Core Language Features |
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| * Methods and blocks |
| * Classes and modules |
| * Mixins and inheritance |
| * Symbols and hashes |
| * Iterators and enumerables |
| * Exception handling (`begin`, `rescue`, `ensure`) |
| * Dynamic typing and duck typing |
| * Constants and global variables |
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| ### 2.2 Object-Oriented and Functional Paradigms |
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| * Class-based design |
| * Encapsulation and polymorphism |
| * Functional constructs using blocks, procs, and lambdas |
| * Method chaining |
| * DSL-style coding patterns |
| * Code reuse via modules and mixins |
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| ### 2.3 Memory and Execution Model |
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| * Garbage-collected memory management |
| * Object allocation patterns |
| * Symbol vs string memory usage |
| * Lazy evaluation patterns |
| * Performance considerations in Ruby |
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| ### 2.4 Data Structures |
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| * Arrays and hashes |
| * Sets and ranges |
| * Custom data structures |
| * Nested collections |
| * Enumerable transformations (`map`, `select`, `reduce`) |
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| ### 2.5 Web and Application Development |
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| * MVC patterns (commonly used in Ruby frameworks) |
| * Routing and controllers |
| * Background job patterns |
| * Database interaction patterns (ORM-style) |
| * RESTful API implementations |
| * Templating and view logic |
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| ## 3. Intended Research Applications |
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| ### 3.1 Fine-Tuning and Adaptation |
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| * Code completion systems for Ruby |
| * Intelligent IDE assistants |
| * Automated refactoring tools |
| * Conversational programming agents |
| * Framework-aware coding assistants |
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| ### 3.2 Code Intelligence Tasks |
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| * Code summarization |
| * Code-to-text generation |
| * Documentation generation |
| * Bug detection (e.g., nil errors, undefined methods) |
| * Security vulnerability detection |
| * Clone detection |
| * Code similarity analysis |
| * Dead code detection |
| * Complexity estimation |
| * Dynamic behavior analysis |
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| ## 4. Key Advantages |
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| * **Language-specific**: Focused purely on Ruby (no cross-language noise) |
| * **Dynamic paradigm coverage**: Includes idiomatic Ruby and metaprogramming patterns |
| * **Web-focused**: Reflects real-world Ruby usage in application development |
| * **Diverse**: Covers multiple coding styles and abstraction levels |
| * **Research-ready**: Suitable for ML pipelines and static/dynamic analysis tools |
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