StatistaAmeri/backend/scrape_lme.py

256 lines
8.5 KiB
Python

import urllib.request
import re
from datetime import datetime
import threading
import time
HEADERS = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36',
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
'Accept-Language': 'en-US,en;q=0.5'
}
_cache = {
"data": None,
"last_fetched": 0
}
_history_cache = {}
_lock = threading.Lock()
FIELD_MAP = {
"copper": "LME_Cu_cash",
"cu": "LME_Cu_cash",
"aluminium": "LME_Al_cash",
"al": "LME_Al_cash",
"aluminum": "LME_Al_cash",
"zinc": "LME_Zn_cash",
"zn": "LME_Zn_cash",
"nickel": "LME_Ni_cash",
"ni": "LME_Ni_cash",
"lead": "LME_Pb_cash",
"pb": "LME_Pb_cash",
"tin": "LME_Sn_cash",
"sn": "LME_Sn_cash",
}
FA_NAMES = {
"Copper": "مس (Copper)",
"Tin": "قلع (Tin)",
"Lead": "سرب (Lead)",
"Zinc": "روی (Zinc)",
"Aluminium": "آلومینیوم (Aluminium)",
"Nickel": "نیکل (Nickel)",
}
MONTHS_MAP = {
"january": "01", "february": "02", "march": "03", "april": "04",
"may": "05", "june": "06", "july": "07", "august": "08",
"september": "09", "october": "10", "november": "11", "december": "12"
}
def clean_num(val: str) -> float:
if not val:
return 0.0
val = val.replace(',', '').replace('+', '').replace('$', '').strip()
try:
return float(val)
except:
return 0.0
def parse_date_iso(raw: str) -> str:
# Example: "25. August 2026"
try:
parts = raw.replace('.', '').split()
if len(parts) >= 3:
day = parts[0].zfill(2)
month = MONTHS_MAP.get(parts[1].lower(), "01")
year = parts[2]
return f"{year}-{month}-{day}"
except:
pass
return raw
def fetch_raw():
url = 'https://www.westmetall.com/en/markdaten.php'
req = urllib.request.Request(url, headers=HEADERS)
with urllib.request.urlopen(req, timeout=12) as resp:
html = resp.read().decode('utf-8', errors='ignore')
tables = re.findall(r'<table[^>]*>([\s\S]*?)</table>', html)
if len(tables) < 2:
return None
# Table 0: Official LME Prices
t0_rows = re.findall(r'<tr[^>]*>([\s\S]*?)</tr>', tables[0])
date_str = ""
prices = []
if t0_rows:
header_cells = re.findall(r'<t[dh][^>]*>([\s\S]*?)</t[dh]>', t0_rows[0])
if len(header_cells) > 1:
date_str = re.sub(r'<.*?>', '', header_cells[1]).strip()
for r in t0_rows[2:]:
cells = [re.sub(r'<.*?>', '', c).replace('&nbsp;', ' ').strip() for c in re.findall(r'<t[dh][^>]*>([\s\S]*?)</t[dh]>', r)]
if len(cells) >= 3 and cells[0]:
prices.append({
"metal": cells[0],
"name_fa": FA_NAMES.get(cells[0], cells[0]),
"cash": clean_num(cells[1]),
"cash_str": cells[1],
"three_months": clean_num(cells[2]),
"three_months_str": cells[2],
"unit": "USD/mt"
})
# Table 1: LME Stocks
t1_rows = re.findall(r'<tr[^>]*>([\s\S]*?)</tr>', tables[1])
stocks = []
if len(t1_rows) > 2:
for r in t1_rows[2:]:
cells = [re.sub(r'<.*?>', '', c).replace('&nbsp;', ' ').strip() for c in re.findall(r'<t[dh][^>]*>([\s\S]*?)</t[dh]>', r)]
if len(cells) >= 3 and cells[0]:
stocks.append({
"metal": cells[0],
"name_fa": FA_NAMES.get(cells[0], cells[0]),
"stocks": clean_num(cells[1]),
"stocks_str": cells[1],
"change": clean_num(cells[2]),
"change_str": cells[2],
"unit": "mt"
})
# Combine Prices + Stocks by metal
combined_metals = []
stocks_map = {s["metal"]: s for s in stocks}
for p in prices:
m_name = p["metal"]
s_data = stocks_map.get(m_name, {})
spread = round(p["three_months"] - p["cash"], 2)
combined_metals.append({
"metal": m_name,
"name_fa": p["name_fa"],
"cash_settlement": p["cash"],
"cash_str": p["cash_str"],
"three_months": p["three_months"],
"three_months_str": p["three_months_str"],
"spread": spread,
"spread_str": f"{spread:+,.2f}",
"stocks": s_data.get("stocks", 0),
"stocks_str": s_data.get("stocks_str", "-"),
"stocks_change": s_data.get("change", 0),
"stocks_change_str": s_data.get("change_str", "-"),
"unit": "USD/mt"
})
# Table 2: FX Rates
fx = []
if len(tables) > 2:
for r in re.findall(r'<tr[^>]*>([\s\S]*?)</tr>', tables[2])[1:]:
cells = [re.sub(r'<.*?>', '', c).replace('&nbsp;', ' ').strip() for c in re.findall(r'<t[dh][^>]*>([\s\S]*?)</t[dh]>', r)]
if len(cells) >= 2 and cells[0]:
fx.append({
"pair": cells[0],
"rate": clean_num(cells[1]),
"rate_str": cells[1]
})
# Table 4: Precious Metals
precious = []
if len(tables) > 4:
for r in re.findall(r'<tr[^>]*>([\s\S]*?)</tr>', tables[4])[1:]:
cells = [re.sub(r'<.*?>', '', c).replace('&nbsp;', ' ').strip() for c in re.findall(r'<t[dh][^>]*>([\s\S]*?)</t[dh]>', r)]
if len(cells) >= 2 and cells[0]:
precious.append({
"name": cells[0],
"price_str": cells[1]
})
return {
"date": date_str or datetime.utcnow().strftime("%d. %B %Y"),
"updated_at": datetime.utcnow().isoformat(),
"metals": combined_metals,
"stocks": stocks,
"exchange_rates": fx,
"precious_metals": precious
}
def get_lme_data(ttl_seconds: int = 180):
now = time.time()
with _lock:
if _cache["data"] and (now - _cache["last_fetched"]) < ttl_seconds:
return _cache["data"]
try:
fresh = fetch_raw()
if fresh:
_cache["data"] = fresh
_cache["last_fetched"] = now
return fresh
except Exception as e:
if _cache["data"]:
return _cache["data"]
raise e
return _cache["data"]
def get_metal_history(metal_key: str, ttl_seconds: int = 300):
norm_key = metal_key.lower().strip()
field = FIELD_MAP.get(norm_key)
if not field:
# Fallback: check if the key already is a field
if norm_key.startswith("lme_"):
field = metal_key
else:
field = f"LME_{norm_key[:2].capitalize()}_cash"
now = time.time()
with _lock:
cached = _history_cache.get(field)
if cached and (now - cached["time"]) < ttl_seconds:
return cached["data"]
url = f'https://www.westmetall.com/en/markdaten.php?action=table&field={field}'
req = urllib.request.Request(url, headers=HEADERS)
with urllib.request.urlopen(req, timeout=12) as resp:
html = resp.read().decode('utf-8', errors='ignore')
tables = re.findall(r'<table[^>]*>([\s\S]*?)</table>', html)
if not tables:
return {"metal": metal_key, "field": field, "points": []}
rows = re.findall(r'<tr[^>]*>([\s\S]*?)</tr>', tables[0])
points = []
# Skip header
for r in rows[1:]:
cells = [re.sub(r'<.*?>', '', c).replace('&nbsp;', ' ').strip() for c in re.findall(r'<t[dh][^>]*>([\s\S]*?)</t[dh]>', r)]
if len(cells) >= 4 and cells[0]:
c_val = clean_num(cells[1])
tm_val = clean_num(cells[2])
s_val = clean_num(cells[3])
date_iso = parse_date_iso(cells[0])
points.append({
"date": date_iso,
"date_display": cells[0],
"cash": c_val,
"cash_str": cells[1],
"three_months": tm_val,
"three_months_str": cells[2],
"spread": round(tm_val - c_val, 2),
"stocks": s_val,
"stocks_str": cells[3],
})
# Reverse points to chronological order (oldest to newest) for charting
points.reverse()
result = {
"metal": metal_key,
"name_fa": FA_NAMES.get(metal_key.capitalize(), metal_key),
"field": field,
"total_points": len(points),
"points": points
}
with _lock:
_history_cache[field] = {"time": now, "data": result}
return result