We extract high-fidelity music listings, audiophile equipment specs, mastering credits, pressing plant details, and dynamic inventory signals from Acoustic Sounds. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Vinyl & Music Records objects from acousticsounds.com. All fields typed and schema-versioned.
"sku": "AAPP 8412-45", "artist": "Miles Davis", "album_title": "Kind of Blue", "format": "200g Vinyl 2LP", "label": "Analogue Productions", "mastering_engineer": "Bernie Grundman", "weight_grams": 200, "speed_rpm": 45, "price": 60.0, "stock_status": "In Stock"
| # | sku | artist | album_title | format | label | pressing_plant |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Audio Equipment objects from acousticsounds.com. All fields typed and schema-versioned.
"sku": "SME-MODEL15", "brand": "SME", "model": "Model 15 Turntable", "category": "Equipment", "sub_category": "Turntables", "price": 9500.0, "stock_status": "Special Order", "weight": "18.5 kg", "warranty": "2 Years"
| # | sku | brand | model | category | sub_category | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Inventory objects from acousticsounds.com. All fields typed and schema-versioned.
"sku": "AAPP 8412-45", "upc": "753088841271", "price": 60.0, "list_price": 60.0, "discount_pct": 0, "stock_status": "Backorder", "availability_message": "Awaiting repress", "scraped_at": "2026-05-12T09:14:00Z"
| # | sku | upc | price | list_price | discount_pct | stock_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Tracklists & Metadata objects from acousticsounds.com. All fields typed and schema-versioned.
"sku": "AAPP 8412-45", "track_number": 1, "track_title": "So What", "duration": "9:22", "side": "A", "composer": "Miles Davis", "credits": "Trumpet: Miles Davis, Tenor Saxophone: John Coltrane"
| # | sku | album_title | track_number | track_title | duration | composer |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from acousticsounds.com. All fields typed and schema-versioned.
"review_id": "REV-99281", "sku": "AAPP 8412-45", "reviewer_name": "Audiophile John", "rating": 5, "review_date": "2025-11-04", "review_body": "Dead quiet pressing. The 45 RPM cut opens up the soundstage significantly.", "verified_purchase": true, "helpful_votes": 14
| # | review_id | sku | reviewer_name | rating | review_date | review_body |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Acoustic Sounds pages contain dense, unstructured text blocks detailing mastering engineers, pressing plants, and equipment specs. We deploy custom parsing heuristics to normalise this data into queryable fields.
Map 180g, 200g, 33 RPM, 45 RPM, SACD, and reel-to-reel tape variations to structured format fields.
Parse unstructured product descriptions to extract mastering engineer credits (e.g., Bernie Grundman, Kevin Gray) and pressing plants (e.g., QRP, RTI).
Monitor stock status changes across In Stock, Backorder, Pre-order, and Special Order states.
Extract and structure technical specifications for turntables, amplifiers, and DACs into nested JSON objects.
Capture pre-order release dates and availability windows for upcoming audiophile pressings.
Extract track titles, durations, and side allocations (Side A, Side B) from album listings.
Isolate audiophile labels such as Analogue Productions, Mobile Fidelity, and Impex Records for targeted filtering.
Extract product grids across specific genres, formats, and hardware categories with full pagination support.
Receive only records that have changed since the last run to minimise downstream processing overhead.
Brief in. Clean data out.
Provide category URLs, specific labels, or equipment types. We design the extraction schema together.
We configure Scrapy crawlers, regex parsers for audiophile metadata, and session management for acousticsounds.com.
Schema validation, null-rate checks, and metadata normalisation tests before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Acoustic Sounds presents unique parsing challenges due to unstructured product descriptions and complex format variations. Here is how we ensure data integrity.
Crucial details like 'Mastered by Ryan K. Smith at Sterling Sound' or 'Plated at QRP' are often buried in paragraphs of marketing copy. We use custom regex patterns and NLP heuristics to extract and normalise these entities into discrete database columns.
The same album may exist as a 33 RPM standard issue, a 45 RPM audiophile pressing, and an SACD — often with separate SKUs but identical titles. We map these relationships so you can compare pricing and availability across formats.
Audiophile pressings frequently shift between 'In Stock', 'Awaiting Repress', and 'Backorder'. Our crawlers monitor these state changes daily, emitting delta updates so your inventory models reflect reality.
Turntables and amplifiers feature complex technical specifications presented in inconsistent HTML tables or lists. We normalise these into structured key-value pairs (e.g., 'wow_and_flutter', 'signal_to_noise_ratio').
To prevent IP bans and ensure pipeline stability, we route requests through US residential proxies with conservative concurrency limits, mimicking genuine browsing behaviour.
Independent record stores and online retailers monitor Acoustic Sounds pricing and stock levels to adjust their own audiophile inventory.
Collectors and resellers track out-of-print titles and repress announcements to identify high-value acquisition targets.
Music databases and archival projects aggregate pressing plant details and mastering credits to build comprehensive audiophile discographies.
Audio hardware manufacturers analyse pricing trends and feature sets across high-end turntables and amplifiers.
Retailers monitor release dates for highly anticipated Analogue Productions and Mobile Fidelity pressings.
Brands monitor customer reviews on high-end equipment to inform product development and marketing strategies.
"Acoustic Sounds holds the definitive catalogue of audiophile pressings and high-end gear — but extracting structured mastering credits requires a purpose-built pipeline."
Parsing audiophile metadata is notoriously complex. Mastering engineers, pressing plants, and vinyl weights are often buried in unstructured descriptions. DataFlirt deploys custom regex and NLP heuristics alongside residential proxies to extract clean, normalised records.
Everything supported by our acousticsounds.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and deduplication. Playwright handles JavaScript rendering for dynamic inventory elements and high-resolution image galleries.
We maintain pools of US residential ISP proxies to avoid IP bans and rate limits, ensuring consistent access to the catalogue.
Pipelines run on AWS ECS. Airflow handles scheduling and SLA alerting. Extracted metadata is stored and normalised in managed PostgreSQL.
Data delivered to where your team already works — no new tooling required.
About acousticsounds.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product listings, pricing, and specifications is generally permissible. DataFlirt targets only public, non-authenticated data. We do not extract personal user data or circumvent authentication walls.
Yes. While this information is often unstructured, we deploy custom regex patterns to identify and extract entities like 'Bernie Grundman', 'Kevin Gray', 'QRP', and 'RTI' into dedicated columns.
We can configure pipelines to run daily or at custom intervals to capture shifts between In Stock, Backorder, and Pre-order states.
Yes. We parse tracklists, including track titles, durations, and side allocations (e.g., Side A, Side B) where available.
Absolutely. Our parsers identify format specifics (weight, speed, disc count) and structure them, allowing you to filter and compare different versions of the same album.
Engagements typically start with a defined category scope (e.g., all vinyl records or all turntables) delivered weekly. Contact us to scope your specific data requirements.
Yes. We provide a sample extraction of up to 500 products during the scoping phase to validate schema fit and parsing accuracy.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue export or continuous stock monitoring — we scope, build, and operate the pipeline. Tell us what you need.
