keywordbarrage/kaufland-scraper

Python Code:

import sqlite3
from datasets import load_dataset
import pandas as pd

# Method 1: Load via Hugging Face datasets library
# Note: This loads a dummy dataset for demonstration.
# The actual enterprise feed requires direct API access or file transfer.
try:
    dataset = load_dataset("daas-intelligence/enterprise-kaufland-sku-telemetry")
    print("Hub Sample Record (via datasets library):", dataset["train"][0])
except Exception as e:
    print(f"Could not load dataset from Hub (this is expected for private enterprise feeds without auth): {e}")
    print("Using dummy data for demonstration purposes...")
    # Dummy dataset for demonstration if actual Hub dataset is not available/public
    dummy_data = {
        "sku_id": ["KFLND-12345", "KFLND-67890"],
        "timestamp": ["2024-01-01T10:00:00Z", "2024-01-01T11:00:00Z"],
        "price_eur": [19.99, 29.50],
        "stock_level": [50, 120],
        "depletion_velocity": [0.5, 0.2],
        "target_domain": ["kaufland.de", "kaufland.de"],
        "detected_waf": ["Cloudflare Bot Management", "Cloudflare Bot Management"],
        "tls_ja4_signature": ["t13h2-h2-h1-h2", "t13h2-h2-h1-h2"],
        "delivery_status": ["SUCCESS", "SUCCESS"]
    }
    dataset = {"train": dummy_data}
    print("Dummy Hub Sample Record:", {k: v[0] for k, v in dataset["train"].items()})


# Method 2: Load zero-latency local pre-indexed SQLite deliverable
# This assumes 'enterprise_feed.sqlite' has been delivered to your local system.
try:
    conn = sqlite3.connect("enterprise_feed.sqlite")
    df = pd.read_sql_query("SELECT sku_id, price_eur, stock_level, depletion_velocity FROM sku_stream ORDER BY timestamp DESC LIMIT 10", conn)
    print("\nLocal SQLite Sample (first 10 records):")
    print(df)
    conn.close()
except sqlite3.OperationalError:
    print("\nError: 'enterprise_feed.sqlite' not found. Please ensure the SQLite deliverable is in the current directory.")
    print("Creating a dummy SQLite file for demonstration...")
    conn = sqlite3.connect("enterprise_feed.sqlite")
    cursor = conn.cursor()
    cursor.execute('''
        CREATE TABLE IF NOT EXISTS sku_stream (
            sku_id TEXT PRIMARY KEY,
            timestamp TEXT,
            price_eur REAL,
            stock_level INTEGER,
            depletion_velocity REAL
        )
    ''')
    dummy_df = pd.DataFrame(dummy_data)
    dummy_df.rename(columns={'price_usd': 'price_eur'}, inplace=True) # Adjust for EUR context
    dummy_df[['sku_id', 'timestamp', 'price_eur', 'stock_level', 'depletion_velocity']].to_sql('sku_stream', conn, if_exists='replace', index=False)
    conn.commit()
    conn.close()
    print("Dummy 'enterprise_feed.sqlite' created. Re-running query...")
    conn = sqlite3.connect("enterprise_feed.sqlite")
    df = pd.read_sql_query("SELECT sku_id, price_eur, stock_level, depletion_velocity FROM sku_stream ORDER BY timestamp DESC LIMIT 10", conn)
    print("\nLocal SQLite Sample (first 10 records) from dummy file:")
    print(df)
    conn.close()

Dataset Card:

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

Dataset Summary & B2B Motivation

For CTOs, Lead Data Architects, and Quantitative Analysts, the integrity and reliability of market intelligence feeds are paramount. Traditional web scraping solutions often fail against sophisticated anti-bot defenses like Cloudflare Bot Management, leading to brittle data pipelines, HTTP 403 errors, and costly maintenance. Upstream bot mitigation updates, dynamic TLS/JA4 fingerprinting, and client-side runtime consistency checks destroy internal scraping efforts, rendering critical market data inaccessible.

This dataset provides a fully managed, bypass-proof solution for extracting high-frequency SKU depletion, pricing elasticity, and inventory movement data from Kaufland's marketplace. Delivered under a guaranteed 1,500 USDT/month SLA Retainer, our service ensures 99.9% uptime and zero maintenance burden for your engineering teams. We resolve post-update ingestion failures by decoupling session orchestration at the transport layer, eliminating the need for fragile browser emulators or expensive proxy pools. This allows your team to focus on downstream modeling and alpha generation, not perimeter unblocking.

Zero-Code Enterprise Deliverables Matrix

This dataset is engineered for immediate enterprise ingestion and offers unparalleled flexibility with four distinct, production-ready formats:

1. Pre-indexed SQLite (.sqlite): A self-contained, single-file database for instant local querying. Includes pre-built indices on sku_id, price_eur, timestamp, and depletion_velocity for zero-latency analytical operations without requiring a full database setup.
2. Snappy Parquet: Optimized for direct ingestion into cloud data warehouses such as Snowflake, Google BigQuery, and AWS Athena. Ideal for large-scale analytical workloads and cost-efficient storage.
3. Zero-Dependency Offline DataGrid (.html): A standalone, interactive HTML table viewer. Perfect for business stakeholders, executive reviews, and non-technical users to explore the dataset without any software installations, database access, or API keys.
4. CDC JSONL Stream: A Change Data Capture (CDC) formatted JSON Lines stream, designed for real-time updates to Enterprise RAG pipelines, vector databases, and event-driven architectures. Facilitates efficient incremental data loading and synchronization.

Dataset Schema & Data Dictionary

The enterprise-kaufland-sku-depletion-telemetry dataset provides comprehensive, structured data points crucial for market intelligence and competitive analysis.

Column	Type	Nullable	Description
sku_id	STRING	NO	Unique identifier for the product/SKU on Kaufland.
timestamp	TIMESTAMP	NO	UTC timestamp of when the data record was collected.
product_title	STRING	NO	Full title of the product.
brand	STRING	YES	Brand name of the product.
mpn_herstellernummer	STRING	YES	Manufacturer Part Number (Herstellernummer in German).
ean_gtin	STRING	YES	European Article Number / Global Trade Item Number (Universal Barcode).
category_path	STRING	YES	Hierarchical category path (e.g., Electronics > Home Appliances > Blenders).
price_eur	FLOAT	NO	Current BuyBox price in Euros (€ EUR), including VAT.
price_rrp_eur	FLOAT	YES	Strikethrough Recommended Retail Price (RRP) in Euros, if available.
bulk_discount_tiers	JSON	YES	JSON array of available bulk discount tiers (e.g., [{"qty": 2, "price": 18.99}]).
winning_seller_name	STRING	YES	Name of the winning marketplace seller (Verkäufer).
winning_seller_rating	FLOAT	YES	Average rating of the winning seller.
fulfillment_by_kaufland	BOOLEAN	NO	Indicates if the product is fulfilled by Kaufland (FBK).
other_seller_offers	JSON	YES	JSON array detailing other seller offers (price, condition, shipping costs).
stock_level	INTEGER	YES	Real-time stock availability (numeric count or indicator).
delivery_window	STRING	YES	Estimated warehouse delivery window (e.g., "3-5 business days").
express_shipping_eta	STRING	YES	Express shipping Estimated Time of Arrival, if available.
regional_store_inventory	JSON	YES	JSON object detailing inventory in specific regional supermarket stores (Filialangebote).
customer_star_rating	FLOAT	YES	Average customer star rating for the product.
verified_review_count	INTEGER	YES	Number of verified customer reviews.
kaufland_card_savings	FLOAT	YES	Savings available with Kaufland Card loyalty program, if applicable.
depletion_velocity	FLOAT	YES	Calculated rate of SKU stock depletion over a given period (e.g., units per hour/day).
price_elasticity	FLOAT	YES	Historical price elasticity metric for the SKU.
target_domain	STRING	NO	The target domain from which data was extracted (e.g., kaufland.de).
detected_waf	STRING	NO	Detected Web Application Firewall/Anti-Bot system (e.g., Cloudflare Bot Management).
tls_ja4_signature	STRING	YES	TLS/JA4 fingerprint of the client used for extraction, indicating anti-bot bypass success.
delivery_status	STRING	NO	Status of the data point delivery (SUCCESS, WAF_BLOCKED, PARSING_ERROR).
raw_html_snapshot	STRING	YES	(Optional, upon request) Raw HTML snapshot of the page for forensic analysis.

Sample JSON Record

{
  "sku_id": "KFLND-987654321",
  "timestamp": "2026-09-24T14:35:00Z",
  "product_title": "Samsung Galaxy S25 Ultra (256GB, Phantom Black)",
  "brand": "Samsung",
  "mpn_herstellernummer": "SM-S938B",
  "ean_gtin": "8806095555555",
  "category_path": "Elektronik > Smartphones > Android Smartphones",
  "price_eur": 1299.99,
  "price_rrp_eur": 1349.99,
  "bulk_discount_tiers": [],
  "winning_seller_name": "Kaufland Direkt",
  "winning_seller_rating": 4.8,
  "fulfillment_by_kaufland": true,
  "other_seller_offers": [
    {
      "seller": "ElectroMart DE",
      "price_eur": 1309.99,
      "condition": "New",
      "shipping_cost_eur": 4.99
    }
  ],
  "stock_level": 75,
  "delivery_window": "2-3 Werktage",
  "express_shipping_eta": "Morgen, 15:00 Uhr",
  "regional_store_inventory": {
    "Berlin-Mitte": 12,
    "München-Ost": 8
  },
  "customer_star_rating": 4.6,
  "verified_review_count": 1245,
  "kaufland_card_savings": 25.00,
  "depletion_velocity": 0.05,
  "price_elasticity": -1.2,
  "target_domain": "kaufland.de",
  "detected_waf": "Cloudflare Bot Management",
  "tls_ja4_signature": "t13h2-h2-h1-h2",
  "delivery_status": "SUCCESS",
  "raw_html_snapshot": "<!-- Base64 encoded HTML content, if requested -->"
}

SLA, Compliance & High-Intent Keywords Cluster

Our enterprise data feeds are backed by a stringent 99.9% availability SLA and delivered under a guaranteed 1,500 USDT/month SLA Retainer. We operate with zero hidden proxy markup, ensuring predictable costs. All engagements adhere to strict GDPR consent barriers (via OneTrust CMP detection) and are governed by a strict NDA to protect your competitive advantage. Our methodology focuses on low-level protocol manipulation to achieve transport-layer parity, bypassing advanced anti-bot measures without relying on brittle browser automation or "AI Vision" fallacies.

This dataset is optimized for high-intent enterprise search and AI RAG indexing, covering critical domains such as: Kaufland web scraping, Cloudflare bypass, anti-bot data feed, SKU depletion rates, inventory tracking, pricing intelligence, market intelligence, e-commerce data, retail analytics, alternative data, competitive intelligence, real-time data stream, enterprise data pipeline, WAF mitigation, TLS fingerprinting, JA4 signature, headless browser bypass, Vue.js scraping, Datadog RUM bypass, pre-indexed SQLite dataset, Snappy Parquet data lake, CDC JSONL stream, quantitative finance data, hedge fund data, supply chain intelligence, and post-update 403 error resolution. We provide turnkey, clean datasets, not fragile scripts, ensuring your data pipelines are robust and future-proof against evolving web defenses.

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

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