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Lowe's Price Tracker

Bright Data Lowe's Price Tracker Python

Bright Insights Price Tracker

Real-time Lowe's price tracking - a major US home improvement retail chain. Two ways to get started: a fully managed intelligence platform or a self-service API to build your own pipeline.


Option 1: Bright Insights - AI-Powered Price Tracking (Recommended)

Bright Insights is Bright Data's fully managed retail intelligence platform. No scrapers to build, no infrastructure to maintain - just structured, analysis-ready price data delivered to dashboards, data feeds, or your BI tools.

Why teams choose Bright Insights:

  • πŸš€ Zero setup - Go live in minutes with ready-to-use dashboards and data feeds
  • πŸ€– AI-powered recommendations - A conversational AI assistant turns millions of data points into actionable insights instantly
  • ⚑ Real-time monitoring - Hourly to daily refresh rates with instant alerts (email, Slack, webhook)
  • 🌍 Unlimited scale - Any website, any geography, any refresh frequency
  • πŸ”— Plug-and-play integrations - AWS, GCP, Databricks, Snowflake, and more
  • πŸ›‘οΈ Fully managed - Bright Data handles schema changes, site updates, and data quality automatically

Key use cases:

  • βœ… Monitor Lowe's prices across all product categories
  • βœ… Track stock levels and availability in real time
  • βœ… Set up price alerts for products you care about
  • βœ… Monitor MAP policy compliance and detect pricing violations
  • βœ… Track competitor promotions and promotional dynamics
  • βœ… Feed clean, harmonized data directly into dynamic pricing algorithms or AI models

Starting from 250ドル/month - Get a tailored quote β†’


Option 2: Self-Service via Web Scraper API

Prefer to build your own pipeline? Bright Data's Web Scraper API gives you programmatic access to Lowe's product data - prices, availability, reviews, and more - without managing proxies or scraping infrastructure.

Prerequisites

Setup

  1. Clone this repository

    git clone https://github.com/luminati-io/lowes-price-tracker.git
    cd lowes-price-tracker
  2. Install dependencies

    pip install -r requirements.txt
  3. Configure credentials

    Copy .env.example to .env and fill in your values:

    cp .env.example .env
    BRIGHTDATA_API_TOKEN=your_api_token_here
    BRIGHTDATA_DATASET_ID=your_dataset_id_here

    Finding your Web Scraper ID Log in to Bright Data Control Panel, navigate to Web Scrapers, search for "Lowe's", and copy the Web Scraper ID (format: gd_xxxxxxxxxxxx).


Usage

1. Track Specific Products by URL

Pass a list of Lowe's product URLs to retrieve structured price data:

from price_tracker import track_prices
urls = [
 "https://www.lowes.com/pd/sample-product/1000123456",
 # Add more product URLs here
]
results = track_prices(urls)
for item in results:
 print(f"{item.get('title')} - {item.get('final_price', item.get('price'))} {item.get('currency', '')}")

Or run directly:

python price_tracker.py

2. Discover Products by Keyword

Find products matching a keyword search:

from price_tracker import discover_by_keyword
results = discover_by_keyword("laptop", limit=50)

3. Browse Products by Category URL

Collect all products from a Lowe's category page:

from price_tracker import discover_by_category
results = discover_by_category(
 "https://lowes.com/category/example",
 limit=100,
)

Output Fields

Each result record contains the following fields:

Field Description
url Product URL
title Product name
brand Brand
model_number Model number
sku SKU
initial_price Original price
final_price Current price
currency Currency code
discount Discount
in_stock Availability
description Product description
images Product images
timestamp Collection timestamp

Sample output

[
 {
 "url": "https://www.lowes.com/pd/sample-product/1000123456",
 "title": "Example Product Name",
 "brand": "Example Brand",
 "initial_price": 59.99,
 "final_price": 44.99,
 "currency": "USD",
 "discount": "25%",
 "in_stock": true,
 "rating": 4.5,
 "reviews_count": 1234,
 "images": ["https://lowes.com/images/product1.jpg"],
 "description": "Product description text...",
 "timestamp": "2025εΉ΄01月15ζ—₯T10:30:00Z"
 }
]

Advanced Options

The trigger_collection() function accepts optional parameters to control data collection:

Parameter Type Default Description
limit integer - Maximum number of records to return
include_errors boolean true Include error reports in results
notify string (URL) - Webhook URL to call when the snapshot is ready
format string json Output format: json, csv, or ndjson

Example with options:

from price_tracker import trigger_collection, get_results
inputs = [{"url": "https://www.lowes.com/pd/sample-product/1000123456"}]
snapshot_id = trigger_collection(inputs, limit=200, notify="https://your-webhook.com/hook")
results = get_results(snapshot_id)

Resources


Built with Bright Data - the industry-leading web data platform.

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Track prices from Lowes - AI-powered via Bright Insights or self-service via Bright Data's Web Scraper API

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