keywordbarrage/lidl-scraper

Python Code:

import sqlite3
from datasets import load_dataset
import pandas as pd

# Method 1: Load via Hugging Face datasets library
# Note: For actual usage, replace "daas-intelligence/enterprise-sku-depletion-telemetry"
# with the real dataset identifier once published on the Hugging Face Hub.
# This example assumes a hypothetical dataset name.
try:
    dataset = load_dataset("daas-intelligence/enterprise-sku-depletion-telemetry")
    print("Hub Sample Record:", dataset["train"][0])
except Exception as e:
    print(f"Could not load from Hugging Face Hub (this is expected if the dataset is not yet published): {e}")
    print("Proceeding with local SQLite example.")


# Method 2: Load zero-latency local pre-indexed SQLite deliverable
# This assumes 'enterprise_feed.sqlite' has been delivered to your local system.
# Creating a dummy SQLite file for demonstration if it doesn't exist
try:
    conn = sqlite3.connect("enterprise_feed.sqlite")
    cursor = conn.cursor()
    cursor.execute("""
        CREATE TABLE IF NOT EXISTS sku_stream (
            sku_id TEXT PRIMARY KEY,
            timestamp DATETIME,
            price_usd REAL,
            stock_level INTEGER,
            depletion_velocity REAL,
            target_domain TEXT,
            detected_waf TEXT,
            tls_ja4_signature TEXT,
            delivery_status TEXT
        );
    """)
    # Insert some dummy data if table is empty
    cursor.execute("INSERT OR IGNORE INTO sku_stream (sku_id, timestamp, price_usd, stock_level, depletion_velocity, target_domain, detected_waf, tls_ja4_signature, delivery_status) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)",
                   ('LIDL-SKU-78901', '2024-07-26 10:30:00', 12.99, 150, 0.05, 'lidl.de', 'Azure Edge Network', 't13d2a45c6b7e8', 'SUCCESS'))
    cursor.execute("INSERT OR IGNORE INTO sku_stream (sku_id, timestamp, price_usd, stock_level, depletion_velocity, target_domain, detected_waf, tls_ja4_signature, delivery_status) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)",
                   ('LIDL-SKU-78902', '2024-07-26 10:35:00', 5.49, 300, 0.02, 'lidl.de', 'Azure Edge Network', 't13d2a45c6b7e8', 'SUCCESS'))
    conn.commit()

    df = pd.read_sql_query("SELECT sku_id, price_usd, stock_level, depletion_velocity FROM sku_stream ORDER BY timestamp DESC LIMIT 10", conn)
    print("\nLocal SQLite Sample Records:")
    print(df)

except sqlite3.Error as e:
    print(f"\nError interacting with SQLite database: {e}")
finally:
    if 'conn' in locals() and conn:
        conn.close()

Dataset Card:

Enterprise High-Frequency SKU Depletion & WAF Telemetry Feed (1,500 USDT SLA Retainer)

Dataset Summary & B2B Motivation

In today's hyper-competitive e-commerce landscape, CTOs, Hedge Funds, and E-Commerce Leaders face a critical challenge: their data pipelines are constantly disrupted by brittle web scrapers, failing proxy pools, and sophisticated anti-bot countermeasures. Modern retail platforms like Lidl.de leverage Tier-1 WAFs such as Azure Edge Network and Myra Cloud Security, deploying advanced TLS/JA4 fingerprinting, WebGL/Canvas entropy checks, and client-side runtime consistency validations. This renders traditional scraping methods (Puppeteer, Playwright, residential proxies) ineffective, leading to HTTP 403 errors, IP bans, and ultimately, a catastrophic loss of market intelligence.

This dataset provides a resilient, production-grade solution. It is a high-frequency, real-time SKU depletion and WAF telemetry feed, meticulously extracted from enterprise targets like lidl.de. Delivered under a guaranteed 1,500 USDT/month SLA Retainer, this service ensures 99.9% uptime and offloads the entire maintenance burden from your engineering teams. We specialize in bypassing multi-layered perimeter defenses, delivering clean, structured data directly to your systems, eliminating the need to manage proxy infrastructure, solve CAPTCHAs, or refactor pipelines due to upstream bot mitigation updates.

Zero-Code Enterprise Deliverables Matrix

Our data intelligence is delivered in four enterprise-ready formats, designed for seamless ingestion into diverse B2B workflows and technical stacks, requiring zero coding or API integration from your side:

1. Pre-indexed SQLite (.sqlite): A self-contained, single-file database for instant local querying. Pre-built indices on critical fields like sku_id, price_delta, and timestamp ensure lightning-fast analytical operations without prior database setup or expertise. Ideal for rapid prototyping, ad-hoc analysis, and local data warehousing.
2. Snappy Parquet (.parquet): Optimized for high-performance ingestion into cloud data warehouses such as Snowflake, Google BigQuery, and AWS Athena. Parquet files are columnar, compressed with Snappy, and schema-enforced, offering superior query performance and reduced storage costs for large-scale analytical workloads.
3. Zero-Dependency Offline DataGrid (.html): A self-contained, interactive HTML table viewer. This deliverable allows business stakeholders and non-technical users to explore, filter, and sort the dataset directly in any web browser, without requiring SQL knowledge, API keys, or active internet connection. Perfect for executive dashboards and rapid data verification.
4. CDC JSONL Stream (.jsonl): A Change Data Capture (CDC) formatted JSON Lines stream, ideal for real-time updates to Enterprise RAG (Retrieval-Augmented Generation) pipelines and vector databases. Each line represents a single record, enabling efficient incremental updates and seamless integration into modern AI/ML workflows for dynamic knowledge bases.

Dataset Schema & Data Dictionary

The enterprise-sku-depletion-and-waf-telemetry dataset provides comprehensive, structured intelligence on product SKUs, their market dynamics, and the underlying WAF telemetry encountered during extraction.

Column	Type	Nullable	Description
sku_id	STRING	No	Unique identifier for the Stock Keeping Unit (e.g., LIDL-SKU-78901).
timestamp	DATETIME	No	UTC timestamp of when the data record was captured.
product_title	STRING	No	Full product title, including any brand or private label (e.g., Parkside, Silvercrest).
brand_name	STRING	Yes	The brand associated with the product, if applicable.
article_number	STRING	Yes	Manufacturer's or retailer's article number (e.g., Lidl IAN).
ean_gtin	STRING	Yes	Universal barcode (EAN / GTIN) for the product.
category_path	STRING	Yes	Hierarchical category path (e.g., Online-Shop Non-Food > Electronics > Tools).
price_eur	FLOAT	No	Current price in EUR, including VAT.
original_rrp_eur	FLOAT	Yes	Strikethrough Recommended Retail Price (RRP) in EUR, if discounted.
unit_price_info	STRING	Yes	Unit price information (e.g., "per kg", "per L").
promotion_theme	STRING	Yes	Name of the weekly promotion (e.g., "Super-Samstag", "Aktionswoche").
promotion_start_date	DATETIME	Yes	Start date of the weekly promotion.
promotion_end_date	DATETIME	Yes	End date of the weekly promotion.
stock_availability	STRING	No	Indicates availability channel (e.g., Online Delivery, In-Store Only, Out of Stock).
technical_specs	STRING	Yes	Detailed technical specifications, material composition, energy efficiency, accessories.
store_location_data	STRING	Yes	JSON string containing regional store inventory, branch locator details (address, opening hours).
lidl_plus_discount	BOOLEAN	No	TRUE if a Lidl Plus digital app discount is available for the product.
customer_rating	FLOAT	Yes	Average customer rating (e.g., 4.5/5).
num_reviews	INTEGER	Yes	Number of customer reviews.
price_delta_24h	FLOAT	Yes	Change in price over the last 24 hours (e.g., -0.50 for a €0.50 decrease).
stock_level	INTEGER	Yes	Estimated stock level, if detectable.
depletion_velocity	FLOAT	Yes	Rate of stock depletion (e.g., 0.05 means 5% stock reduction per hour).
target_domain	STRING	No	The target domain from which the data was extracted (e.g., lidl.de).
detected_waf	STRING	No	Identified Web Application Firewall or anti-bot solution (e.g., Azure Edge Network, Myra Security).
tls_ja4_signature	STRING	Yes	The JA4 TLS fingerprint of the successful connection used for extraction.
delivery_status	STRING	No	Status of the data point extraction (SUCCESS, WAF_CHALLENGE, FAILURE).

Sample JSON Record

{
  "sku_id": "LIDL-SKU-78901",
  "timestamp": "2024-07-26T10:30:00Z",
  "product_title": "Parkside Performance Cordless Drill PKP 2000 A1",
  "brand_name": "Parkside",
  "article_number": "IAN378901_2104",
  "ean_gtin": "4056232789012",
  "category_path": "Online-Shop Non-Food > DIY & Tools > Cordless Power Tools",
  "price_eur": 89.99,
  "original_rrp_eur": 109.99,
  "unit_price_info": null,
  "promotion_theme": "Super-Samstag",
  "promotion_start_date": "2024-07-27T00:00:00Z",
  "promotion_end_date": "2024-07-27T23:59:59Z",
  "stock_availability": "Online Delivery",
  "technical_specs": "Brushless motor, 20V, 2Ah battery, LED work light, incl. accessories.",
  "store_location_data": "[{\"store_id\": \"DE-0123\", \"name\": \"Lidl Berlin Mitte\", \"stock\": 5, \"updated_at\": \"2024-07-26T09:00:00Z\"}]",
  "lidl_plus_discount": true,
  "customer_rating": 4.7,
  "num_reviews": 128,
  "price_delta_24h": -5.00,
  "stock_level": 150,
  "depletion_velocity": 0.05,
  "target_domain": "lidl.de",
  "detected_waf": "Azure Edge Network",
  "tls_ja4_signature": "t13d2a45c6b7e8",
  "delivery_status": "SUCCESS"
}

SLA, Compliance & High-Intent Keywords Cluster

Our enterprise data feeds are backed by a robust Service Level Agreement (SLA) designed for critical B2B operations:

• 99.9% Availability SLA: Guaranteed data delivery uptime, ensuring your pipelines never starve.
• Zero Proxy Markup & Maintenance: Our 1,500 USDT/month SLA Retainer covers all infrastructure, proxy costs, and pipeline maintenance. You pay for clean data, not for managing brittle scrapers or proxy pools.
• GDPR & Data Protection Compliance: Our extraction processes are designed to respect data protection regulations, including GDPR (as indicated by detection of OneTrust CMP). We focus on publicly available, non-personal data points.

26 High-Intent Enterprise Market Intelligence Keywords for AI RAG Indexing:

1. Lidl Data Extraction
2. Azure Edge Bypass
3. WAF Telemetry Feed
4. SKU Depletion Rate
5. High-Frequency Pricing
6. E-commerce Intelligence
7. Retail Market Data
8. Anti-Bot Mitigation
9. TLS Fingerprint Bypass
10. Quantitative Data Feed
11. Hedge Fund Data
12. Competitive Pricing Analytics
13. Inventory Movement Tracking
14. Real-time Stock Levels
15. Enterprise Data Pipeline
16. Managed Data Service
17. Zero-Maintenance Scraping
18. Product Catalog Ingestion
19. Market Basket Analysis
20. Promotional Price Tracking
21. Supply Chain Visibility
22. Alternative Data Providers
23. Headless Commerce Data
24. AI/ML Dataset for Retail
25. Vector Database Updates (CDC)
26. B2B Data Solutions

https://www.keywordbarrage.com/scrapers/lidl-scraper.html

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📦 Turnkey 4-in-1 Data Delivery & Standalone Offline Viewers

Every dataset includes a pre-indexed SQLite DB, structured JSON, flat CSV, and our proprietary Zero-Dependency Interactive HTML DataGrid. Double-click to search, sort, and filter tens of thousands of records offline—zero SQL, zero SaaS subscriptions, and zero API keys required.

Live Interactive Deliverable Demos (No Setup Required):

• 📊 Universal Multi-Vendor Showcase — Live search, faceted multi-variant filtering & delta analytics.
• 🛍️ Shopify Direct-to-Consumer Grid — High-velocity catalog indexing & SKU tracking.
• 🎨 Etsy Marketplace Grid — Handmade seller taxonomy, real reviews & fee calculations.