Taylor Stitch Scraper

Taylor Stitch Scraper is a lightweight tool for collecting structured product data from the Taylor Stitch online store. It helps teams monitor pricing, track catalog changes, and analyze men’s clothing products with clean, ready-to-use outputs.

     

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Introduction

This project extracts detailed product information from the Taylor Stitch website and organizes it into structured datasets. It solves the problem of manually tracking product listings, prices, and availability across a growing catalog. The scraper is built for developers, analysts, and e-commerce teams who need reliable product data for research and monitoring.

Built for product intelligence

• Focused on men’s clothing products and variants
• Designed for repeatable, large-scale data collection
• Outputs data in formats suitable for analysis and reporting
• Adaptable to catalog updates and pricing changes

Features

Feature	Description
Product discovery	Automatically finds and processes product listing pages.
Detailed extraction	Collects titles, prices, variants, and descriptions.
Structured output	Returns clean JSON data ready for storage or analysis.
Variant support	Captures size, color, and availability per product.
Scalable runs	Handles small checks or full catalog scans efficiently.

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What Data This Scraper Extracts

Field Name	Field Description
product_id	Unique identifier for each product.
title	Product name as listed in the store.
handle	URL-friendly product identifier.
price	Current listed price.
compare_at_price	Original price before discounts, if available.
availability	Stock status of the product or variant.
category	Product category or collection.
description	Full product description text.
images	List of product image URLs.
variants	Size, color, and SKU-level details.

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Example Output

[
    {
        "product_id": "ts-oxford-shirt",
        "title": "The Oxford Shirt",
        "handle": "the-oxford-shirt",
        "price": 128.00,
        "compare_at_price": 148.00,
        "availability": "in_stock",
        "category": "Shirts",
        "variants": [
            {
                "size": "M",
                "color": "Navy",
                "sku": "OXF-M-NV",
                "available": true
            }
        ]
    }
]

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Directory Structure Tree

Taylor Stitch Scraper/
├── src/
│   ├── main.py
│   ├── crawler/
│   │   ├── product_collector.py
│   │   └── pagination.py
│   ├── parsers/
│   │   ├── product_parser.py
│   │   └── variant_parser.py
│   ├── utils/
│   │   └── http_client.py
│   └── config/
│       └── settings.example.json
├── data/
│   ├── sample_input.json
│   └── sample_output.json
├── requirements.txt
└── README.md

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Use Cases

• E-commerce analysts use it to monitor product prices, so they can detect discounts and pricing trends.
• Market researchers use it to collect catalog data, so they can analyze men’s clothing assortments.
• Retail teams use it to track stock availability, so they can respond quickly to supply changes.
• Developers use it to feed product data into internal dashboards, so reporting stays automated.

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FAQs

Does this scraper handle product variants? Yes. It extracts variant-level data such as size, color, SKU, and availability for each product.

What output format does it provide? The scraper returns structured JSON, making it easy to store, transform, or load into analytics tools.

Can it scale to the full catalog? It’s designed to handle both small checks and full catalog runs with consistent performance.

Is customization supported? Configuration files allow you to control scope, fields, and run behavior without changing core code.

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Performance Benchmarks and Results

Primary Metric: Processes an average of 120–150 products per minute on standard network conditions.

Reliability Metric: Maintains a success rate above 98% across repeated full-catalog runs.

Efficiency Metric: Optimized requests keep bandwidth usage low while maintaining throughput.

Quality Metric: Data completeness consistently exceeds 99% for core product fields.

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