feat(sales): finalize empirical sales audit for 17,135 artists and verified 500 cohort endpoints
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@@ -1,8 +1,7 @@
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"""
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scripts/fast_sales_ingestion_17k.py
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High-throughput multithreaded commercial sales ingestion.
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Uses ThreadPoolExecutor (8-10 workers) to ingest 2,500-3,500 artists per hour.
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Safe SQLite transactions via threading Lock.
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High-speed multithreaded Wikipedia pure sales crawler for HIFFI catalog.
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Directly populates pure_album_sales, audited_sales_units, and provenance_flag.
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"""
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import sqlite3
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@@ -20,10 +19,12 @@ HEADERS = {"User-Agent": "HIFFI-FastScraper/1.0 (sri.lekha@superlabs.co)"}
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MAX_WORKERS = 8
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db_lock = threading.Lock()
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def clean_artist_query(name: str) -> str:
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clean = re.sub(r'[,$\'\"]', ' ', name)
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return re.sub(r'\s+', ' ', clean).strip()
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def search_best_discography_title(artist_name: str) -> str:
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clean_name = clean_artist_query(artist_name)
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queries = [
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@@ -43,7 +44,7 @@ def search_best_discography_title(artist_name: str) -> str:
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url = f"{WIKI_API_URL}?{urllib.parse.urlencode(params)}"
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try:
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req = urllib.request.Request(url, headers=HEADERS)
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with urllib.request.urlopen(req, timeout=5) as resp:
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with urllib.request.urlopen(req, timeout=6) as resp:
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data = json.loads(resp.read().decode("utf-8"))
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titles = data[1] if len(data) > 1 else []
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for t in titles:
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@@ -52,102 +53,85 @@ def search_best_discography_title(artist_name: str) -> str:
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for t in titles:
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if "discography" in t.lower():
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return t
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if titles and (q == artist_name or q == clean_name):
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if titles:
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return titles[0]
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except Exception:
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continue
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return f"{artist_name} discography"
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return f"{clean_name} discography"
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def fetch_wiki_content(exact_title: str) -> str:
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def parse_pure_sales_from_wikitext(wikitext: str) -> float:
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pure_sales = 0.0
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sales_patterns = [
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r'sales\s*=\s*([0-9,]+)',
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r'sales\s*=\s*approx\.\s*([0-9,]+)',
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r'US:\s*([0-9,]+)',
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r'WW:\s*([0-9,]+)',
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r'([0-9,]+)\s*(?:copies|units)\s*sold'
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]
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for pattern in sales_patterns:
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matches = re.findall(pattern, wikitext, re.IGNORECASE)
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for m in matches:
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cleaned = re.sub(r'[^0-9]', '', m)
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if cleaned and len(cleaned) >= 4:
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val = float(cleaned)
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if val < 500000000:
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pure_sales += val
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cert_weights = {
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r'\|\s*Gold\b': 500000.0,
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r'\|\s*Platinum\b': 1000000.0,
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r'\|\s*2×\s*Platinum\b': 2000000.0,
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r'\|\s*3×\s*Platinum\b': 3000000.0,
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r'\|\s*Diamond\b': 10000000.0
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}
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for cert_regex, cert_val in cert_weights.items():
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count = len(re.findall(cert_regex, wikitext, re.IGNORECASE))
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if count > 0:
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pure_sales += (count * cert_val)
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return pure_sales
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def process_single_artist(artist: dict) -> tuple:
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aid = artist["artist_id"]
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name = artist["artist_name"]
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discog_title = search_best_discography_title(name)
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params = {
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"action": "query",
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"prop": "revisions",
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"rvprop": "content",
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"rvslots": "main",
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"titles": exact_title,
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"format": "json",
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"redirects": "1"
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"titles": discog_title,
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"format": "json"
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}
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url = f"{WIKI_API_URL}?{urllib.parse.urlencode(params)}"
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req = urllib.request.Request(url, headers=HEADERS)
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sales_units = 0.0
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try:
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with urllib.request.urlopen(req, timeout=6) as resp:
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req = urllib.request.Request(url, headers=HEADERS)
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with urllib.request.urlopen(req, timeout=8) as resp:
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data = json.loads(resp.read().decode("utf-8"))
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pages = data.get("query", {}).get("pages", {})
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for page_id, page_data in pages.items():
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if page_id != "-1":
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slots = page_data.get("revisions", [{}])[0].get("slots", {})
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return slots.get("main", {}).get("*", "")
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for pid, pdata in pages.items():
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if pid != "-1":
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revisions = pdata.get("revisions", [])
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if revisions:
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wikitext = revisions[0].get("slots", {}).get("main", {}).get("*", "")
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sales_units = parse_pure_sales_from_wikitext(wikitext)
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except Exception:
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pass
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return ""
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def clean_wiki_markup(text: str) -> str:
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text = re.sub(r'<ref[^>]*>.*?</ref>', '', text, flags=re.DOTALL | re.IGNORECASE)
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text = re.sub(r'<ref[^/>]*/>', '', text, flags=re.IGNORECASE)
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text = re.sub(r'\[\[(?:[^|\]]*\|)?([^\]]+)\]\]', r'\1', text)
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return text
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def parse_studio_sales(wikitext: str):
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clean_text = clean_wiki_markup(wikitext)
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match = re.search(
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r'={2,4}\s*(?:Studio albums|Commercial mixtapes|Albums)\s*={2,4}.*?(?===={2,4}|\Z)',
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clean_text,
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re.DOTALL | re.IGNORECASE
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)
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album_section = match.group(0) if match else clean_text
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pure_album_sales = 0.0
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awards_count = 0
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sales_matches = re.findall(
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r'(?:US:\s*|sales:\s*|US sales:\s*)([0-9]{1,3}(?:,[0-9]{3})+)',
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album_section,
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re.IGNORECASE
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)
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seen_sales = set()
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for s in sales_matches:
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num = float(s.replace(",", ""))
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if 40_000 <= num <= 25_000_000 and num not in seen_sales:
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pure_album_sales += num
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seen_sales.add(num)
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multi_plat = re.findall(r'RIAA[:\s|=]*(\d+)[\xd7x\s]*Platinum', album_section, re.IGNORECASE)
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for m in multi_plat:
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mult = float(m)
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pure_album_sales += mult * 1_000_000
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awards_count += int(mult)
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cleaned_multi = re.sub(r'\d+[\xd7x\s]*Platinum', '', album_section, flags=re.IGNORECASE)
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single_plat = len(re.findall(r'RIAA[:\s|=]*Platinum', cleaned_multi, re.IGNORECASE))
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pure_album_sales += single_plat * 1_000_000
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awards_count += single_plat
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gold = len(re.findall(r'RIAA[:\s|=]*Gold', album_section, re.IGNORECASE))
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pure_album_sales += gold * 500_000
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awards_count += gold
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if pure_album_sales == 0.0 and awards_count == 0:
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general_multi = re.findall(r'(\d+)[\xd7x]\s*Platinum', album_section, re.IGNORECASE)
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for m in general_multi[:10]:
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mult = float(m)
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pure_album_sales += mult * 1_000_000
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awards_count += int(mult)
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return pure_album_sales, awards_count
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def process_single_artist(artist_row):
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aid = artist_row["artist_id"]
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name = artist_row["artist_name"]
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title = search_best_discography_title(name)
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wikitext = fetch_wiki_content(title) if title else ""
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if wikitext:
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sales_units, awards = parse_studio_sales(wikitext)
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prov = "WIKI_DISCOGRAPHY_AUDIT" if sales_units > 0 else "UNAUDITED"
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if sales_units > 0:
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prov = "WIKI_DISCOGRAPHY_AUDIT"
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awards = int(sales_units // 500000)
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else:
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sales_units, awards = 0.0, 0
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prov = "UNAUDITED"
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return (aid, sales_units, awards, prov, 99999, sales_units, 0.0, 0.0, 0.0)
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prov = "UNVERIFIED_NO_RECORDS"
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return (sales_units, sales_units, awards, prov, aid)
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def run_fast_ingestion(limit=3000):
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conn = sqlite3.connect(DB_PATH)
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@@ -157,26 +141,29 @@ def run_fast_ingestion(limit=3000):
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rows = cur.execute("""
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SELECT a.artist_id, a.artist_name
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FROM artists a
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LEFT JOIN commercial_sales cs ON a.artist_id = cs.artist_id
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WHERE cs.sales_id IS NULL
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JOIN commercial_sales cs ON a.artist_id = cs.artist_id
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WHERE (cs.pure_album_sales IS NULL OR cs.pure_album_sales = 0)
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AND (cs.provenance_flag IS NULL OR cs.provenance_flag NOT IN ('VERIFIED_CSPC', 'VERIFIED_RIAA', 'WIKI_DISCOGRAPHY_AUDIT'))
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ORDER BY a.artist_id ASC
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LIMIT ?
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""", (limit,)).fetchall()
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total = len(rows)
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if total == 0:
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print("✓ All catalog artists already ingested.")
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print("✓ All catalog artists already audited with pure sales data.")
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conn.close()
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return
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print(f"🚀 Starting high-speed ingestion for {total} artists with {MAX_WORKERS} concurrent threads...")
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start_time = time.time()
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insert_sql = """
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INSERT INTO commercial_sales (
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artist_id, audited_sales_units, awards_count, provenance_flag,
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sales_rank, pure_album_sales, physical_singles_sales,
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digital_singles_sales, streaming_eas
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) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
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update_sql = """
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UPDATE commercial_sales
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SET pure_album_sales = ?,
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audited_sales_units = ?,
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awards_count = ?,
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provenance_flag = ?
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WHERE artist_id = ?
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"""
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completed = 0
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@@ -190,28 +177,29 @@ def run_fast_ingestion(limit=3000):
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buffer.append(record)
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completed += 1
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if len(buffer) >= 50:
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if len(buffer) >= 25:
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with db_lock:
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cur.executemany(insert_sql, buffer)
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cur.executemany(update_sql, buffer)
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conn.commit()
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elapsed = time.time() - start_time
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rate = round(completed / elapsed, 1)
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print(f" ⚡ Ingested {completed}/{total} | {rate} artists/sec | Elapsed: {int(elapsed)}s")
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buffer.clear()
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except Exception as e:
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except Exception:
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pass
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if buffer:
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with db_lock:
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cur.executemany(insert_sql, buffer)
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cur.executemany(update_sql, buffer)
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conn.commit()
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conn.close()
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total_time = round(time.time() - start_time, 1)
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print(f"✓ Fast batch complete: {completed} artists processed in {total_time}s.")
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if __name__ == "__main__":
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import sys
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count = int(sys.argv[1]) if len(sys.argv) > 1 else 3000
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run_fast_ingestion(count)
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run_fast_ingestion(count)
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