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--- |
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license: mit |
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tags: |
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- nodejs |
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pretty_name: nodejs-all.json |
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--- |
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# Node.js API Dataset |
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> **Source**: [Node.js](https://nodejs.org/) official documentation (JSON variant) |
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> **Processing Type**: Extractive, Hierarchical Flattening. |
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## Overview |
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This dataset contains a structured representation of the Node.js API, derived from the official `nodejs.json` distribution. Unlike raw documentation dumps, this dataset has been processed into two distinct formats to serve different machine learning and analytical purposes: **Macro-level (Documents)** and **Micro-level (Granular Items)**. |
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This "Dataset-as-a-Repo" approach ensures that the data is not just a transient output of a pipeline but a versioned, maintained artifact suitable for training high-quality code models. |
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## Methodology & Design Choices |
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### 1. The "Abstract-to-Concrete" Philosophy |
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The core design philosophy here is that "code intelligence" requires understanding both the *forest* (modules, high-level concepts) and the *trees* (individual function signatures, property types). |
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- **Raw Input**: The `nodejs.all.json` is a massive, nested structure that can be overwhelming for simple sequential models. |
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- **Transformation**: We "pulled apart" the JSON to create focused training examples. |
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### 2. Dual-Format Output |
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We intentionally avoided a "one-size-fits-all" schema. |
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- **Documents (`nodejs_documents.jsonl`)**: Preserves the cohesiveness of a module. Good for teaching a model "concept association" (e.g., that `fs.readFile` belongs with `fs.writeFile`). |
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- **Granular (`nodejs_granular.jsonl`)**: Isolates every single function and property. Good for "instruction tuning" (e.g., "Write a function signature for `http.createServer`"). |
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### 3. File Formats |
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- **JSONL**: Chosen for its streaming capabilities and human readability. Perfect for NLP pipelines. |
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- **Parquet**: Chosen for the "Granular" dataset to allow fast columnar access, filtering, and analysis (e.g., "Find all methods with > 3 arguments"). |
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## Dataset Structure |
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### Output Location |
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All processed files are located in `output/`: |
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```text |
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output/ |
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├── nodejs_documents.jsonl # High-level module data |
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├── nodejs_granular.jsonl # Individual API items |
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└── nodejs_granular.parquet # Parquet version of granular data |
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``` |
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### Schema: Documents (`nodejs_documents.jsonl`) |
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Representing a whole Module (e.g., `Buffer`, `http`). |
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| Field | Type | Description | |
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|-------|------|-------------| |
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| `module_name` | string | Name of the module (e.g., `fs`). | |
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| `type` | string | Usually `module` or `global`. | |
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| `description` | string | Raw HTML/Markdown description of the module. | |
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| `content` | json-string | Full nested JSON blob of the module's contents (methods, props). | |
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### Schema: Granular (`nodejs_granular.jsonl`) |
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Representing a single API item (Function, Property, Event). |
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| Field | Type | Description | |
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|-------|------|-------------| |
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| `id` | string | Unique namespaced ID (e.g., `fs.readFile`). | |
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| `parent` | string | Parent module (e.g., `fs`). | |
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| `type` | string | `method`, `property`, `event`, etc. | |
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| `name` | string | Short name (e.g., `readFile`). | |
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| `description` | string | Description of *just* this item. | |
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| `metadata` | json-string | Detailed signatures, params, stability indices. | |
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## Use Cases |
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### 1. Pre-Training Code Models |
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Feed `nodejs_documents.jsonl` into a language model to teach it the general structure and API surface of Node.js. The large context windows of modern LLMs can easily ingest entire modules. |
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### 2. Instruction Tuning / RAG |
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Use `nodejs_granular.jsonl` to build a Retrieval Augmented Generation (RAG) system. |
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- **Query**: "How do I read a file in Node?" |
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- **Retrieval**: Search against the `description` field in the granular dataset. |
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- **Context**: Retrieve the exact `metadata` (signature) for `fs.readFile`. |
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### 3. API Analysis |
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Use `nodejs_granular.parquet` with Pandas/DuckDB to answer meta-questions: |
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- *Which Node.js APIs are marked as Experimental?* |
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- *What is the average number of arguments for `fs` methods vs `http` methods?* |
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## Provenance |
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- **Original File**: `datasets/raw/nodejs.all.json` |
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- **Script**: `src/process_nodejs.py` |
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- **Maintainer**: Antigravity (Agent) / User |
