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README.md

@@ -539,12 +539,28 @@ dataset_info:
         dtype: string
 ---
 
-# FragDB v5.15 — Fragrance Database (Multilingual Sample)
+# FragDB v5.16 — Fragrance Database (Multilingual Sample)
 
-The most comprehensive structured fragrance database available. This is a **free sample** of FragDB: **139,501 perfumes, 23 languages** — 10-row CSV samples at root.
+The most comprehensive structured fragrance database available. This is a **free sample** of FragDB: **140,230 perfumes, 23 languages** — 10-row CSV samples at root.
 
 Full dataset: [fragdb.net](https://fragdb.net).
 
+## What's New in v5.16
+
+- **Data updated** from v5.15 → v5.16 (snapshot 2026-09-19):
+  - Fragrances: 139,501 → **140,230** (+729)
+  - Brands: 8,272 → **8,316** (+44)
+  - Perfumers: 3,116 → **3,126** (+10)
+  - Notes: 2,596 → **2,606** rows in `notes.csv` (+10)
+- **Companion parquet refreshed for the first time since June** — user reviews
+  4,643,851 → **4,986,774** (+342,923), editorial articles 24,440 → **25,619** (+1,179),
+  news comments 263,798 → **276,483** (+12,685).
+- **New: a Data API** — per-record HTTP access to the same catalogue, priced per record.
+  See the section below.
+- Derived figures re-measured against the new files: review coverage 66.9% → **69.8%**,
+  English share 1.69M → **1.88M**, reply rate 4.9% → **5.5%**.
+- Sample files unchanged: the schema did not move between v5.15 and v5.16.
+
 ## What's New in v5.15
 
 - **Data updated** from v5.14 → v5.15 (full source recrawl, parser run 260910):
@@ -655,6 +671,82 @@ All F column counts identical (30/54/42/55/27/25) — existing scripts work with
 - **Data refreshed**: 2026-09-10 (v5.15)
 - **Reviews, news, news comments** (parquet): unchanged in this release — latest review 2026-05-02, latest article 2026-04-28
 
+## Data API — per-record access
+
+**The whole catalogue, one record at a time.** A metered HTTP API over the same database we
+sell as files. You pay per record returned, at the level of detail you ask for. No
+subscription and no seats: top up a balance, fetch what your application needs, cache it as
+long as you like.
+
+**[fragdb.net/api →](https://fragdb.net/api)** · [OpenAPI spec](https://fragdb.net/api/v1/openapi) · [Sign up](https://fragdb.net/register) · [FAQ](https://fragdb.net/faq) · [Terms](https://fragdb.net/legal#api-access)
+
+### Endpoints
+
+```
+GET  /api/v1/fragrances/{id}        one record
+GET  /api/v1/brands/{id}            one brand
+GET  /api/v1/notes/{id}             one note
+GET  /api/v1/perfumers/{id}         one perfumer
+POST /api/v1/{collection}/batch     up to 100 ids in one call
+GET  /api/v1/index                  the full index, gzipped JSONL
+GET  /api/v1/release                current release label and date — free
+GET  /api/v1/account                balance, limits, usage — free
+```
+
+Detail level is chosen with `?level=list|basic|full`.
+
+**There are no list endpoints.** `/api/v1/fragrances?limit=50` answers 404, by design. You
+enumerate the catalogue with the index file — id, name, brand, year and change status — search
+it on your side, and fetch whole records only for the hits you need. The index costs no units
+and needs a paid key: five downloads a day, and an unchanged index answers 304.
+
+### Detail levels
+
+| Level | Units | Per record | What comes back |
+|-------|------:|-----------:|-----------------|
+| `list`  | 1 | $0.0025 | id, brand, name, year, gender, rating with vote count, and a thumbnail |
+| `basic` | 2 | $0.005  | plus the photo, the collection, review count, main accords with their strength and the credited perfumers |
+| `full`  | 4 | $0.01   | the note pyramid as published, seven vote blocks, description, pros and cons, related fragrances, and every label translated inline |
+
+1 unit = $0.0025. Top-ups are multiples of $50, from $100 up to $5,000 — $100 buys 40,000
+units. Paid units do not expire while the account is open. Minimum spend is $100 (40,000
+units) per 180 days, $16.67 a month, counted from the first top-up. Payment in BTC, ETH, TRX,
+XMR or USDT.
+
+### Try it before you pay
+
+Sign up and a free test key appears straight away. It costs nothing, charges nothing and
+serves 5 sample records at every level — enough to write your parser against the real shape
+of a response before you pay for anything.
+
+```bash
+curl -H "Authorization: Bearer <your test key>" \
+  "https://fragdb.net/api/v1/fragrances/f_9kwkhn9yqx?level=full"
+```
+
+That id is one of the five public samples, so the call works on a test key.
+
+Already bought a database file? You get 500 units for 30 days to try the API. (The 500 units
+come with a file purchase, not with signing up.)
+
+### Limits
+
+10 requests per second and 300 per minute on a key · 20 per second on an account · 100 ids per
+batch call · 50,000 charged records per account per UTC day · 5 index downloads per day · 5
+keys per account. Call the API from your server, never from a browser.
+
+### How it sits next to the files
+
+The API serves the same catalogue that is sold as files, refreshed about three times a month.
+Every response carries the release label and its date, and `GET /api/v1/release` tells you
+which release you are on.
+
+Ids are permanent: a record withdrawn at its source stays available with its last known
+content and a status flag.
+
+Reviews, news articles and community comments are **not** in the API — those stay in the
+downloadable files described in this dataset card.
+
 ## Dataset Description
 
 | File | Records | Fields | Description |
@@ -686,26 +778,26 @@ FragDB ships with **three Apache Parquet datasets** containing **4.9 million row
 
 **Keywords:** fragrance reviews · perfume reviews · multilingual UGC corpus · NLP training data · fragrance sentiment · perfumery journalism · perfume recommendation · scent recommendation · review classification · entity linking · knowledge graph · fragrance industry news · perfume articles
 
-### `comments.parquet` — 4.6 Million User Reviews in 23 Languages
+### `comments.parquet` — 5.0 Million User Reviews in 23 Languages
 
 The world's largest collection of structured fragrance reviews. Every entry includes the perfume ID (joinable with `fragrances.csv`), author username, posting date, full review text, avatar URL, and language code.
 
-- **4,643,851 user reviews** covering every major perfume in the database
-- **23 languages** — English (1.69M), Russian, Portuguese, Spanish, Korean, Turkish, Japanese, Polish, Italian, Hungarian, Serbian, Swedish, German, Hebrew, Ukrainian, French, Arabic, Greek, Czech, Chinese, Romanian, Mongolian, Dutch
-- **Coverage:** 66.9% of all fragrances have at least one review (93,296 of 139,501 PIDs)
+- **4,986,774 user reviews** covering every major perfume in the database
+- **23 languages** — English (1.88M), Russian, Portuguese, Spanish, Korean, Turkish, Japanese, Polish, Italian, Hungarian, Serbian, Swedish, German, Hebrew, Ukrainian, French, Arabic, Greek, Czech, Chinese, Romanian, Mongolian, Dutch
+- **Coverage:** 69.8% of all fragrances have at least one review (97,817 of 140,230 PIDs)
 - **Deterministic global primary key** — stable comment IDs survive re-scrapes
-- **Zero duplicate rows**; every `pid` joins `fragrances.csv` except 46 reviews (0.001%) on 9 perfumes no longer in the catalogue
+- **Zero duplicate rows**; every `pid` joins `fragrances.csv` except 48 reviews (0.001%) on 10 perfumes no longer in the catalogue
 - **Independent UGC per language** — genuine localized content, not machine translation
 - **8 fields:** `pid`, `lang`, `comment_id`, `author`, `date`, `text`, `avatar_url`, `gradient_class`
 - **PyArrow large_string format** — combined corpus exceeds 32-bit string offset limit
 
 **Use cases:** sentiment analysis · review classification · recommendation systems · perfume similarity from text · language detection benchmark · multilingual NLP training corpus · fragrance market research · author network analysis · trend detection by language
 
-### `news.parquet` — 24,440 Editorial Articles (2008–2026)
+### `news.parquet` — 25,619 Editorial Articles (2008–2026)
 
 Two decades of professional fragrance journalism. Every article includes title, author, full text (plain + HTML), category, related perfumes/brands/perfumers, publication date, and main image.
 
-- **24,440 editorial articles** from 2008 to 2026 — complete public archive
+- **25,619 editorial articles** from 2008 to 2026 — complete public archive
 - **30+ categories** — New Fragrances (34.9%), Fragrance Reviews (22.8%), Niche Perfumery (10.4%), Designer Brands, Interviews, History, Industry News
 - **Bilingual storage** — `text` (plain) for NLP, `text_html` (markup preserved) for rich display
 - **Linked entities** — `related_pids[]`, `related_brands[]`, `related_perfumers[]` as JSON arrays
@@ -715,11 +807,11 @@ Two decades of professional fragrance journalism. Every article includes title,
 
 **Use cases:** content recommendation · article search engine · perfume knowledge graph · trend analysis · author influence study · entity linking · timeline analysis · industry research · niche perfumery research
 
-### `news_comments.parquet` — 263,798 Threaded Community Comments
+### `news_comments.parquet` — 276,483 Threaded Community Comments
 
 Community discussions attached to editorial articles, with threading support for replies. Joinable with `news.parquet` via `nid`.
 
-- **263,798 threaded comments** across **21,820 articles** (89.3% of news articles have ≥1 comment)
+- **276,483 threaded comments** across **21,820 articles** (89.3% of news articles have ≥1 comment)
 - **4.9% reply rate** — threaded conversations with reply detection
 - **100% populated timestamps**
 - **9 fields:** `nid`, `comment_id`, `is_reply`, `author`, `date`, `date_unix`, `text`, `avatar_url`, `gradient`
@@ -786,14 +878,14 @@ Full schema in [`SPEC.md`](SPEC.md).
 
 | | Sample | Full Database |
 |---|--------|---------------|
-| Fragrances | 10 | **139,501** |
-| Brands | 10 | **8,272** |
-| Perfumers | 10 | **3,116** |
-| Notes | 10 | **2,596** |
+| Fragrances | 10 | **140,230** |
+| Brands | 10 | **8,316** |
+| Perfumers | 10 | **3,126** |
+| Notes | 10 | **2,606** |
 | Accords | 10 | **92** |
 | Translations | 34 | **34** |
 | Languages | 23 | **23** |
-| **Total Records** | ~84 | **153,611** |
+| **Total Records** | ~84 | **154,404** |
 
 ## Quick Start