keywordbarrage/systembolaget-scraper

Python Code:

import sqlite3
from datasets import load_dataset
import pandas as pd

# Method 1: Load via Hugging Face datasets library
# This repository contains a 1,000-row verified sample.
# Full real-time stream via enterprise SLA.
dataset = load_dataset("daas-intelligence/systembolaget-catalog-and-waf-telemetry")
print("Hub Sample Record:", dataset["train"][0])

# Method 2: Load zero-latency local pre-indexed SQLite deliverable
# Replace "enterprise_systembolaget_feed.sqlite" with your delivered database file
conn = sqlite3.connect("enterprise_systembolaget_feed.sqlite")
df = pd.read_sql_query("""
    SELECT
        artikelnummer,
        product_title,
        retail_price_sek,
        stock_level_store,
        alcohol_by_volume_percent,
        timestamp_utc
    FROM systembolaget_catalog
    ORDER BY timestamp_utc DESC
    LIMIT 10
""", conn)
print("\nSQLite Sample Data:")
print(df)
conn.close()

Dataset Card:

---

pretty_name: "Enterprise High-Frequency Systembolaget Catalog & WAF Telemetry Feed (1,500 USDT SLA Retainer)" annotations_creators: - machine-generated language: - en - sv license: apache-2.0 task_categories: - tabular-classification - time-series-forecasting tags: - systembolaget-catalog - e-commerce-intelligence - azure-waf-bypass - time-series-inventory - pre-indexed-sqlite - 1500-usdt-sla-retainer size_categories: - 10K<n<100K configs: - config_name: default data_files: - split: train path: "data/train-.parquet" - split: validation path: "data/val-.parquet"

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

This repository contains a 1,000-row verified sample of the Systembolaget.se catalog and associated WAF telemetry feed. Full high-frequency real-time stream is delivered via our enterprise 1,500 USDT/mo SLA pipeline.

Dataset Summary & B2B Motivation

For CTOs, Hedge Funds, and E-Commerce Leaders, maintaining robust data pipelines against modern web defenses is a constant battle. Systembolaget.se, as Sweden's state-owned alcohol monopoly, deploys a formidable defense stack including Microsoft Azure Front Door and Azure Edge WAF, coupled with Next.js SSR and sophisticated client-side checks like TLS/JA4 fingerprinting and WebGL/Canvas entropy. These defenses routinely invalidate traditional residential proxies, break headless browser farms, and lead to recurrent HTTP 403 bans and pipeline failures, destroying the reliability of market intelligence.

This dataset offers a production-grade, bypass-proof data stream from Systembolaget.se, engineered to overcome these Tier-1 enterprise protections. We provide a fully managed, zero-maintenance data feed, eliminating the need for internal scraping infrastructure, proxy pool management, or constant refactoring against upstream bot mitigation updates. Our pipeline ensures 99.9% uptime and delivers pristine, structured data, allowing your data architects and quantitative analysts to focus on deriving alpha signals rather than fighting web security. This service is backed by a guaranteed 1,500 USDT/month SLA Retainer, ensuring uninterrupted, high-fidelity market intelligence.

Zero-Code Enterprise Deliverables Matrix

We understand that enterprise data consumption requires flexibility and ease of integration. Our Systembolaget data feed is delivered in four production-ready formats, designed for diverse B2B use cases:

1. Pre-indexed SQLite (.sqlite) Database:

   • Benefit: Instant local querying and analysis with zero setup. Our SQLite deliverables come with pre-built indices on critical fields like artikelnummer, retail_price_sek, stock_level_store, and timestamp_utc, ensuring lightning-fast performance for local data scientists and analysts.
   • Use Case: Rapid prototyping, ad-hoc analysis, and small-to-medium scale data applications.

2. Snappy Parquet (.parquet) Files:

   • Benefit: Optimized for cloud data warehouses and big data analytics. Parquet's columnar storage and Snappy compression enable efficient ingestion into platforms like Snowflake, Google BigQuery, AWS Athena, and Databricks, minimizing storage and query costs.
   • Use Case: Large-scale data warehousing, ETL pipelines, and machine learning feature stores.

3. Zero-Dependency Offline DataGrid (.html):

   • Benefit: A self-contained, interactive HTML table viewer that requires no internet connection, backend, or API keys. Business stakeholders can filter, sort, and search data directly in their web browser.
   • Use Case: Business intelligence, stakeholder reporting, and non-technical team data exploration.

4. CDC (Change Data Capture) JSONL Stream:

   • Benefit: Delivers incremental updates in a line-delimited JSON format, ideal for real-time data lakes, streaming analytics, and vector database updates for Enterprise RAG (Retrieval Augmented Generation) pipelines.
   • Use Case: Real-time inventory tracking, AI model retraining, and dynamic content synchronization.

Dataset Schema & Data Dictionary

The Systembolaget catalog dataset includes comprehensive product attributes, pricing, inventory, and crucial telemetry about the extraction process.

Column Name	Type	Nullable	Description
artikelnummer	STRING	NO	Unique Systembolaget article number (e.g., 74001). Primary identifier for each SKU.
product_title	STRING	NO	Full product name and vintage (e.g., Chianti Classico Riserva 2018).
producer_brand	STRING	YES	Name of the producer, brewery, or winery, and brand classification.
ean_13_barcode	STRING	YES	EAN-13 international barcode for the product.
beverage_category	STRING	NO	Main beverage category (e.g., Rött vin, Öl, Sprit, Alkoholfritt).
beverage_subcategory	STRING	YES	More granular subcategory within the main category (e.g., Chianti Classico, IPA).
alcohol_by_volume_percent	FLOAT	YES	Alcohol content by volume, in percentage (e.g., 13.5).
bottle_volume_cl	INTEGER	YES	Volume of the bottle in centiliters (cl).
retail_price_sek	FLOAT	NO	Consumer retail price in Swedish Kronor (SEK), including VAT.
bottle_deposit_pant_sek	FLOAT	NO	Mandatory bottle deposit (Pant) in SEK, if applicable.
liter_price_sek	FLOAT	YES	Comparative price per liter in SEK (Jämförpris kr/l).
origin_country	STRING	YES	Country of origin (Ursprungsland).
origin_region	STRING	YES	Region of origin (e.g., Toscana).
origin_district	STRING	YES	Specific district of origin (e.g., Chianti Classico).
vintage_year	INTEGER	YES	Vintage year of the product (Årgång), if applicable.
fullness_profile	STRING	YES	Sensory profile indicator for fullness (e.g., Fylligt, Medelfylligt).
acidity_profile	STRING	YES	Sensory profile indicator for acidity (e.g., Hög fruktsyra, Låg fruktsyra).
bitterness_profile	STRING	YES	Sensory profile indicator for bitterness/astringency (e.g., Låg strävhet, Hög strävhet).
sweetness_profile	STRING	YES	Sensory profile indicator for sweetness (e.g., Torrt, Sött).
ecological_status	BOOLEAN	YES	Indicates if the product has an ecological certification (Ekologiskt).
krav_certified	BOOLEAN	YES	Indicates if the product is KRAV certified.
stock_level_store	INTEGER	YES	Current inventory level at a specific store (if available via API/page).
order_assortment_status	STRING	YES	Status regarding ordering assortment (e.g., I lager, Beställningssortiment).
timestamp_utc	DATETIME	NO	UTC timestamp of when the data record was extracted.
target_domain	STRING	NO	The target domain from which the data was extracted (e.g., systembolaget.se).
detected_waf	STRING	YES	Identifies the detected Web Application Firewall or anti-bot solution (e.g., Azure Front Door & Edge WAF).
tls_ja4_signature	STRING	YES	The TLS JA4 fingerprint used for the successful connection, indicating advanced anti-bot bypass.
delivery_status	STRING	NO	Status of the data delivery for this record (SUCCESS, PARTIAL_FAILURE, WAF_BLOCKED).

Sample JSON Record

{
  "artikelnummer": "74001",
  "product_title": "Chianti Classico Riserva 2018",
  "producer_brand": "Carpineto",
  "ean_13_barcode": "8000492000010",
  "beverage_category": "Rött vin",
  "beverage_subcategory": "Chianti Classico",
  "alcohol_by_volume_percent": 13.5,
  "bottle_volume_cl": 75,
  "retail_price_sek": 189.00,
  "bottle_deposit_pant_sek": 0.00,
  "liter_price_sek": 252.00,
  "origin_country": "Italien",
  "origin_region": "Toscana",
  "origin_district": "Chianti Classico",
  "vintage_year": 2018,
  "fullness_profile": "Fylligt",
  "acidity_profile": "Hög fruktsyra",
  "bitterness_profile": "Låg strävhet",
  "sweetness_profile": "Torrt",
  "ecological_status": false,
  "krav_certified": false,
  "stock_level_store": 50,
  "order_assortment_status": "I lager",
  "timestamp_utc": "2026-09-24T14:30:00Z",
  "target_domain": "systembolaget.se",
  "detected_waf": "Azure Front Door & Edge WAF",
  "tls_ja4_signature": "t13d0a0a0c121415161718191a2021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899a0a1a2a3a4a5a6a7a8a9aaabacadaeafb0b1b2b3b4b5b6b7b8b9bacbbccbdbebf",
  "delivery_status": "SUCCESS"
}

SLA, Compliance & High-Intent Keywords Cluster

Our enterprise Systembolaget data feed operates under a stringent 99.9% availability SLA, ensuring your market intelligence remains uninterrupted. We guarantee zero proxy markup and transparent pricing within the 1,500 USDT/month retainer.

This dataset is engineered for quantitative data architects, hedge funds, and ML engineering teams requiring:

• Systembolaget real-time data
• Azure Front Door bypass for web scraping
• Next.js data extraction without headless browsers
• TLS/JA4 fingerprinting bypass
• WAF telemetry for bot detection analysis
• SKU velocity and inventory depletion rates
• E-commerce market intelligence
• Swedish alcohol monopoly data
• Pre-indexed SQLite datasets
• Snappy Parquet feeds for Snowflake/BigQuery
• Change Data Capture (CDC) JSONL
• Enterprise web data extraction
• Managed data pipeline with 99.9% uptime
• Alternative data for quant finance
• Retail pricing elasticity time-series
• Zero-maintenance data feeds
• Anti-bot resilient data streams
• Production-grade web data
• High-frequency data delivery
• Competitive intelligence data
• Alcopedia beverage taxonomy
• Regulated retail data
• Supply chain intelligence
• Data integrity and deduplication
• Edge challenge invalidation
• Session queue decoupling

Our commitment is to deliver clean, validated, and immediately usable data, freeing your teams from the complexities of web data acquisition against hardened enterprise perimeters.

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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.