Bedbathandbeyond Parser Spider

Bedbathandbeyond Parser Spider extracts structured Bed Bath & Beyond product data at scale, turning messy product pages into clean, analysis-ready records. Use it to capture pricing, availability, images, and specifications for reliable market research and competitive monitoring.

     

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Introduction

This project collects detailed product information from Bed Bath & Beyond listings and converts it into consistent, structured output. It solves the problem of manually tracking fast-changing catalog data (price changes, stock status, variant options, and media) across large product sets. It’s built for analysts, e-commerce teams, and developers who need repeatable product data extraction for reporting and decision-making.

Product Catalog Intelligence Workflow

• Parses product pages into normalized fields (pricing, inventory, images, and specs)
• Handles variant-rich SKUs by mapping options to a consistent schema
• Captures canonical URLs and identifiers to support de-duplication and change tracking
• Produces dataset-ready output for dashboards, ETL pipelines, and audits
• Designed for stable runs with retries, throttling, and structured error logging

Features

Feature	Description
Product detail parsing	Extracts key attributes from product pages into clean structured fields.
Pricing intelligence	Captures list price, sale price, currency, and discount context for analysis.
Availability tracking	Records stock state and availability messaging for inventory monitoring.
Variant & option mapping	Normalizes options (size/color/pack) into a consistent representation.
Media extraction	Collects primary and gallery images for catalog enrichment.
Specs & attributes capture	Parses bullet points and specification tables into structured key/value pairs.
Robust crawling controls	Supports rate limiting, retries, and safe concurrency for stable runs.
Output-ready structure	Produces data shaped for analytics, exports, and downstream pipelines.

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What Data This Scraper Extracts

Field Name	Field Description
productId	Unique identifier for the product, used for tracking and de-duplication.
sku	Stock keeping unit, when available on the page.
title	Product name/title shown on the listing.
brand	Brand or manufacturer name, when present.
url	Canonical product URL for stable referencing.
categoryPath	Breadcrumb/category hierarchy for catalog classification.
price	Current displayed price (numeric).
currency	Currency code or symbol associated with the price.
originalPrice	List/was price for discount comparisons (when available).
discountPercent	Computed discount percentage (when applicable).
availability	Stock status (in_stock / out_of_stock / limited / unknown).
availabilityMessage	Human-readable availability text shown on the page.
rating	Average rating value (when present).
reviewCount	Number of reviews for the product (when present).
images	Array of image URLs (primary + gallery).
primaryImage	Best representative image URL for the product.
description	Product description text (short or long, when present).
highlights	Key selling points/bullets extracted from the page.
specifications	Structured specs as key/value pairs (material, dimensions, features, etc.).
variants	Variant matrix including option names and values (size, color, pack, etc.).
seller	Seller/merchant info if the listing includes marketplace sellers.
shippingInfo	Shipping details or delivery messaging (when available).
timestamp	Collection timestamp for change history and auditing.

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Example Output

[
      {
            "productId": "bb-10492831",
            "sku": "92831-XL-BLK",
            "title": "Microfiber Comforter Set",
            "brand": "Nestwell",
            "url": "https://www.bedbathandbeyond.com/example-product",
            "categoryPath": ["Bedding", "Comforters & Sets"],
            "price": 49.99,
            "currency": "USD",
            "originalPrice": 79.99,
            "discountPercent": 38,
            "availability": "in_stock",
            "availabilityMessage": "In Stock - Ships in 1–2 days",
            "rating": 4.6,
            "reviewCount": 312,
            "primaryImage": "https://images.examplecdn.com/products/10492831/main.jpg",
            "images": [
                  "https://images.examplecdn.com/products/10492831/main.jpg",
                  "https://images.examplecdn.com/products/10492831/alt-1.jpg",
                  "https://images.examplecdn.com/products/10492831/alt-2.jpg"
            ],
            "highlights": [
                  "Soft brushed microfiber",
                  "Machine washable",
                  "Includes shams and comforter"
            ],
            "specifications": {
                  "Material": "100% Polyester",
                  "Fill": "Hypoallergenic fiberfill",
                  "Care": "Machine wash cold",
                  "Set Includes": "1 comforter, 2 shams"
            },
            "variants": [
                  {
                        "option": "Color",
                        "value": "Black"
                  },
                  {
                        "option": "Size",
                        "value": "Full/Queen"
                  }
            ],
            "shippingInfo": "Free shipping over $49",
            "timestamp": 1766332800000
      }
]

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Directory Structure Tree

bedbathandbeyond-parser-spider (IMPORTANT :!! always keep this name as the name of the apify actor !!! Bedbathandbeyond Parser Spider )/
├── .actor/
│   ├── actor.json
│   └── input_schema.json
├── src/
│   ├── main.py
│   ├── runner/
│   │   ├── __init__.py
│   │   ├── settings.py
│   │   └── logging.py
│   ├── spiders/
│   │   └── bedbathandbeyond_parser_spider.py
│   ├── pipelines/
│   │   ├── __init__.py
│   │   ├── normalize.py
│   │   └── validators.py
│   ├── extractors/
│   │   ├── __init__.py
│   │   ├── product_details.py
│   │   ├── pricing.py
│   │   ├── inventory.py
│   │   ├── media.py
│   │   └── specs.py
│   └── utils/
│       ├── __init__.py
│       ├── http.py
│       ├── parsing.py
│       └── dates.py
├── tests/
│   ├── __init__.py
│   ├── test_parsing_pricing.py
│   ├── test_parsing_specs.py
│   └── fixtures/
│       ├── sample_product_page.html
│       └── sample_output.json
├── data/
│   ├── sample_input_urls.txt
│   └── sample_output.json
├── Dockerfile
├── requirements.txt
├── .gitignore
└── README.md

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Use Cases

• E-commerce analysts use it to track price and stock changes daily, so they can detect competitor moves and react faster.
• Marketplace operators use it to enrich internal catalogs with images and specs, so they can improve product discoverability and conversion.
• Data teams use it to feed ETL pipelines with consistent product records, so they can build reliable BI dashboards and reports.
• Merchandising teams use it to compare variant pricing across sizes/colors, so they can optimize assortment and promotional strategy.
• Researchers use it to collect large product datasets for trend analysis, so they can quantify category shifts over time.

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FAQs

Q: What inputs do I need to run Bedbathandbeyond Parser Spider? You typically provide one or more product or listing URLs (or a set of start URLs). For best results, keep inputs focused on product-detail pages when you need full specs, images, and variants. If you provide category/listing URLs, the spider should discover product links and then parse each detail page.

Q: Does it handle products with multiple variants (size/color/pack)? Yes. Variant options are normalized into a predictable variants structure, and where possible each option/value pair is captured so you can group or compare variants in analytics. If the site only exposes variant data after selection, the spider records what is visible and logs missing variant details for traceability.

Q: How do you avoid duplicates when the same product appears in multiple categories? The output includes stable identifiers (productId, sku when available) and the canonical url. Downstream, you can de-duplicate by productId first, and fall back to canonical URL hashing when needed.

Q: What are common reasons a product record might be incomplete? The most common causes are dynamic page fragments not rendered in the initial HTML, regional content differences, temporary throttling, or missing fields on the listing itself. The spider is designed to capture partial records with consistent defaults and clear logging so you can re-run or patch gaps.

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Performance Benchmarks and Results

Primary Metric: Average parsing throughput of ~35–60 product pages/minute on a typical VM profile, depending on variant complexity and media count.

Reliability Metric: 97–99% successful fetch-and-parse rate on stable runs, with automatic retries recovering most transient network or throttling failures.

Efficiency Metric: Memory usage remains stable for long runs by streaming results and limiting in-memory page retention; CPU load primarily scales with HTML parsing and variant normalization.

Quality Metric: Data completeness typically reaches 90%+ for core commerce fields (title, price, availability, images), with specs coverage varying by category based on how consistently tables are published.

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