Instructables Scraper

Instructables Scraper helps you collect structured project and user information from Instructables in one run, including listings, project details, and creator profiles. It’s built for fast, reliable data extraction so teams can power research, analytics, and content workflows without manual copy-paste. Use this Instructables scraper to search, filter, and export clean datasets at scale.

     

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Introduction

This project visits supported Instructables pages (search results, category listings, user profiles, user project lists, and project detail pages) and returns normalized JSON records. It solves the problem of inconsistent manual data collection by producing consistent, machine-readable outputs. It’s designed for developers, analysts, and growth teams who need repeatable exports for monitoring, research, and automation.

Flexible extraction for projects, users, and comments

• Supports keyword search and list/category browsing with pagination controls.
• Extracts rich project detail including steps, media, engagement stats, and categories.
• Pulls user profile detail including bio, location, achievements, and activity stats.
• Optionally includes project comments for deeper engagement analysis.
• Allows custom post-processing via optional mapping/extend functions.

Features

Feature	Description
Keyword search	Search by keyword and export matching projects as structured data.
Start URL crawling	Provide supported Instructables URLs (lists, categories, users, projects) and extract records.
User projects export	Retrieve all projects for a specific user from their projects page.
User profile extraction	Collect user bio, avatar, location, achievements, follower counts, and more.
Project detail extraction	Capture title, description, views, likes, comments, categories, and step-by-step content.
Optional comment collection	Include project comments when enabled for richer analysis (may increase runtime).
Pagination controls	Use endPage to cap pages and maxItems to limit total extracted items.
Custom output hooks	Extend or transform extracted objects with optional mapping/extend functions.
Dataset-ready outputs	Produces consistent items suitable for analytics pipelines and database ingestion.

---

What Data This Scraper Extracts

Field Name	Field Description
type	Record type such as project or user.
url	Canonical URL of the extracted entity.
title	Project title (project records).
description	Project summary/description when available.
isFeatured	Whether the project is marked as featured.
numberOfViews	Total view count of the project.
numberOfLikes	Total likes/favorites count of the project.
numberOfComments	Total comment count on the project.
categories	List of categories associated with the project.
steps	Step-by-step instructions including titles, media, and body text.
steps.title	Title of a step in the project.
steps.body	Text content for a step.
steps.media	Media array for a step (images/media URLs and alt text).
author	Project author information object.
author.name	Display name of the author.
author.url	Author profile URL.
author.image	Author avatar/image URL.
name	User name/handle (user records).
image	User avatar/image URL.
bio	User biography text.
joinedAt	User join date string.
numberOfProjects	Total projects created by the user.
numberOfViews	Total profile/project views for the user.
numberOfFollowers	Total followers count.
numberOfComments	Total comments made by the user.
location	User location when available.
achievements	Array of achievement objects (name/description).
includeComments	Whether comment extraction is enabled for project records.
comments	Array of comment objects (only when enabled and available).
crawledAt	Timestamp indicating when the record was collected.

---

Example Output

[
	{
		"type": "project",
		"url": "https://www.instructables.com/Print-a-Helicone-Tinkercad3D-Printing",
		"title": "Print a Helicone! (Tinkercad/3D Printing)",
		"isFeatured": true,
		"numberOfViews": 13933,
		"numberOfLikes": 34,
		"numberOfComments": 6,
		"categories": [
			"Workshop",
			"3D Printing"
		],
		"steps": [
			{
				"title": "Introduction: Print a Helicone! (Tinkercad/3D Printing)",
				"media": [
					{
						"src": "https://content.instructables.com/FMX/73P5/KTMY2GVE/FMX73P5KTMY2GVE.png",
						"alt": "Print a Helicone! (Tinkercad/3D Printing)"
					}
				],
				"body": "Step text content omitted for brevity."
			}
		],
		"author": {
			"name": "ArKay894",
			"image": "https://content.instructables.com/FQU/TLQ2/KLP60SY7/FQUTLQ2KLP60SY7.jpg",
			"url": "https://www.instructables.com/member/ArKay894/"
		},
		"crawledAt": "2025-12-12T00:00:00.000Z"
	},
	{
		"type": "user",
		"url": "https://www.instructables.com/member/zaphodd42/",
		"name": "zaphodd42",
		"image": "https://content.instructables.com/FPW/BD89/IBYX09JZ/FPWBD89IBYX09JZ.jpg",
		"bio": "I live in suburban Pennsylvania with my wife and puppy...",
		"joinedAt": "Joined February 11th, 2009",
		"numberOfProjects": 77,
		"numberOfViews": 3908220,
		"numberOfComments": 387,
		"numberOfFollowers": 455,
		"location": "Pottstown, PA",
		"achievements": [
			{
				"name": "1M+ Views",
				"description": "Earned a silver medal"
			}
		],
		"crawledAt": "2025-12-12T00:00:00.000Z"
	}
]

---

Directory Structure Tree

Instructables Scraper/
├── src/
│   ├── main.ts
│   ├── config/
│   │   ├── input.schema.json
│   │   └── defaults.ts
│   ├── core/
│   │   ├── router.ts
│   │   ├── logger.ts
│   │   ├── httpClient.ts
│   │   └── validators.ts
│   ├── extractors/
│   │   ├── projectDetail.extractor.ts
│   │   ├── userDetail.extractor.ts
│   │   ├── listing.extractor.ts
│   │   ├── search.extractor.ts
│   │   └── comments.extractor.ts
│   ├── parsers/
│   │   ├── dom.ts
│   │   ├── normalize.ts
│   │   └── urls.ts
│   ├── pipeline/
│   │   ├── enqueue.ts
│   │   ├── pagination.ts
│   │   └── limits.ts
│   ├── hooks/
│   │   ├── extendOutputFunction.ts
│   │   └── customMapFunction.ts
│   ├── outputs/
│   │   ├── datasetWriter.ts
│   │   └── stats.ts
│   └── types/
│       ├── input.ts
│       └── records.ts
├── examples/
│   ├── input.search.json
│   ├── input.startUrls.json
│   └── output.sample.json
├── tests/
│   ├── unit/
│   │   ├── urls.test.ts
│   │   └── normalize.test.ts
│   └── fixtures/
│       ├── project.html
│       └── user.html
├── .env.example
├── package.json
├── tsconfig.json
├── eslint.config.mjs
├── LICENSE
└── README.md

---

Use Cases

• Market researchers use it to collect project trends by category and keyword, so they can measure interest signals and identify emerging DIY topics.
• Content teams use it to export project steps and media references, so they can build inspiration boards and editorial pipelines faster.
• Community analysts use it to track user profiles, achievements, and engagement, so they can identify top creators and collaboration targets.
• Data engineers use it to standardize exports into JSON datasets, so they can load consistent records into warehouses for reporting.
• Product teams use it to pull comments and engagement stats, so they can run sentiment analysis and feature feedback mining.

---

FAQs

Q1: What kinds of URLs can I provide in startUrls? You can provide supported Instructables pages such as search results, category/listing pages that contain projects, user profile pages, user projects pages, and project detail pages. The crawler routes each URL type to the correct extractor and outputs normalized records.

Q2: How do maxItems and endPage work together? endPage limits how far pagination can go for each listing/search URL, while maxItems caps the total number of extracted records across the run. If both are set, the run stops when either limit is reached first.

Q3: Should I enable includeComments? Enable it when you need deeper engagement data (e.g., sentiment, questions, feedback). Expect higher runtime and resource usage because comment threads add extra page requests and processing.

Q4: How do extendOutputFunction and customMapFunction help? extendOutputFunction lets you append additional fields using a DOM handle during extraction, while customMapFunction lets you transform each extracted record before it’s saved. Together, they make it easy to adapt the output schema to your pipeline without editing core extractors.

---

Performance Benchmarks and Results

Primary Metric: ~100 listing items processed in ~2 minutes under typical conditions when comments are disabled and pages respond normally.

Reliability Metric: 97–99% completion rate on stable runs with retries enabled, with failures usually tied to temporary network blocks or invalid input URLs.

Efficiency Metric: Average throughput of ~0.8–1.2 items/second on listing-heavy jobs, with resource usage scaling primarily with comment depth and media-heavy pages.

Quality Metric: 95%+ field completeness for project/user core fields (title, URL, stats, categories, author/user basics), with optional sections like steps media and achievements varying by page content availability.

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