Create yahooinfo.py

app/yahooinfo.py

@@ -0,0 +1,298 @@
+# ======================================================
+# FINAL YAHOO FINANCE INFO PROCESSOR + RENDERER
+# ======================================================
+
+import yfinance as yf
+import pandas as pd
+import traceback
+import re
+from datetime import datetime, UTC
+from math import floor
+
+from .persist import exists, load, save
+
+
+# ======================================================
+# CONSTANTS
+# ======================================================
+CR  = 10_000_000
+KCR = 10_000_000_000
+LCR = 10_000_000_000_000
+
+DATE_KEYS = ("date", "timestamp", "time", "yearend")
+
+
+# ======================================================
+# RAW YAHOO FETCH
+# ======================================================
+def yfinfo(symbol):
+    try:
+        t = yf.Ticker(symbol + ".NS")
+        info = t.info
+        return info if isinstance(info, dict) else {}
+    except Exception as e:
+        return {"__error__": str(e)}
+
+
+# ======================================================
+# HELPERS
+# ======================================================
+def truncate(num, decimals=4):
+    f = 10 ** decimals
+    return floor(num * f) / f
+
+
+def compress_key(key, used):
+    if len(key) <= 10:
+        used.add(key)
+        return key
+
+    parts = re.findall(r"[A-Z][a-z]*|[a-z]+", key)
+    base = "".join(p[:3] for p in parts)
+
+    if base not in used:
+        used.add(base)
+        return base
+
+    i = 1
+    while f"{base}_{i}" in used:
+        i += 1
+
+    final = f"{base}_{i}"
+    used.add(final)
+    return final
+
+
+# ======================================================
+# CORE PROCESSOR
+# ======================================================
+def process_info(info):
+    main = {}
+    long_text = {}
+
+    new_to_old = {}
+    old_to_new = {}
+
+    used_keys = set()
+
+    for old_k, v in info.items():
+        lk = old_k.lower()
+        new_k = compress_key(old_k, used_keys)
+
+        new_to_old[new_k] = old_k
+        old_to_new[old_k] = new_k
+
+        # ---- Long text ----
+        if isinstance(v, str) and len(v) > 200:
+            long_text[new_k] = v
+            continue
+
+        # ---- Date conversion ----
+        if (
+            isinstance(v, int)
+            and v >= 1_000_000_000
+            and any(x in lk for x in DATE_KEYS)
+        ):
+            if v > 1_000_000_000_000:
+                v //= 1000
+            try:
+                main[new_k] = datetime.fromtimestamp(v, UTC).strftime("%d-%m-%Y")
+            except:
+                main[new_k] = v
+            continue
+
+        # ---- Large numbers (Cr/KCr/LCr) ----
+        if isinstance(v, (int, float)) and abs(v) >= CR:
+            av = abs(v)
+            sign = -1 if v < 0 else 1
+
+            if av >= LCR:
+                main[new_k] = f"{sign * av / LCR:.2f} LCr"
+            elif av >= KCR:
+                main[new_k] = f"{sign * av / KCR:.2f} KCr"
+            else:
+                main[new_k] = f"{sign * av / CR:.2f} Cr"
+            continue
+
+        # ---- Float trimming ----
+        if isinstance(v, float):
+            main[new_k] = 0.0 if v == 0.0 else truncate(v)
+            continue
+
+        main[new_k] = v
+
+    return main, long_text, new_to_old, old_to_new
+
+
+# ======================================================
+# NOISE
+# ======================================================
+NOISE_KEYS = {
+    "maxAge", "priceHint", "triggerable",
+    "customPriceAlertConfidence",
+    "sourceInterval", "exchangeDataDelayedBy",
+    "esgPopulated"
+}
+
+def is_noise(k):
+    return k in NOISE_KEYS
+
+
+# ======================================================
+# DUPLICATE RESOLUTION (OLD KEYS)
+# ======================================================
+DUPLICATE_PRIORITY = {
+    "price": ["regularMarketPrice", "currentPrice"],
+    "prev": ["regularMarketPreviousClose", "previousClose"],
+    "open": ["regularMarketOpen", "open"],
+    "high": ["regularMarketDayHigh", "dayHigh"],
+    "low": ["regularMarketDayLow", "dayLow"],
+    "volume": ["regularMarketVolume", "volume"],
+}
+
+def resolve_duplicates(data, new_to_old):
+    resolved = {}
+    used_old = set()
+
+    for keys in DUPLICATE_PRIORITY.values():
+        for old_k in keys:
+            for new_k, mapped_old in new_to_old.items():
+                if mapped_old == old_k and new_k in data:
+                    resolved[new_k] = data[new_k]
+                    used_old.update(keys)
+                    break
+            else:
+                continue
+            break
+
+    for new_k, v in data.items():
+        if new_to_old[new_k] not in used_old:
+            resolved[new_k] = v
+
+    return resolved
+
+
+# ======================================================
+# CLASSIFIERS (UNCHANGED – OLD KEYS ONLY)
+# ======================================================
+def classify_price_volume_subgroup(old_key):
+    k = old_key.lower()
+    if "volume" in k: return "Volume"
+    if "average" in k or "dma" in k: return "Moving Avg"
+    if "week" in k or "beta" in k: return "Range / Vol"
+    if "target" in k or "recommend" in k: return "Bid / Analyst"
+    return "Live Price"
+
+
+def classify_key(old_key, value):
+    k = old_key.lower()
+
+    if isinstance(value, (int, float)) and any(x in k for x in [
+        "price", "volume", "avg", "change", "percent",
+        "market", "week", "beta", "target"
+    ]):
+        return "price_volume"
+
+    if any(x in k for x in [
+        "revenue", "income", "profit", "margin",
+        "pe", "pb", "roe", "roa", "debt", "equity"
+    ]):
+        return "fundamental"
+
+    if isinstance(value, str) and len(value) > 80:
+        return "long_text"
+
+    return "profile"
+
+
+# ======================================================
+# GROUP BUILDER (KEY POINT)
+# ======================================================
+def build_grouped_info(info, new_to_old):
+    groups = {
+        "price_volume": {},
+        "fundamental": {},
+        "profile": {},
+        "long_text": {},
+    }
+
+    for new_k, v in info.items():
+        if v in [None, "", [], {}]:
+            continue
+
+        old_k = new_to_old.get(new_k, new_k)
+        g = classify_key(old_k, v)
+        groups[g][new_k] = v
+
+    return groups
+
+
+# ======================================================
+# FORMATTERS
+# ======================================================
+def format_number(x):
+    try:
+        x = float(x)
+        if abs(x) >= 100:
+            return f"{x:,.0f}"
+        if abs(x) >= 1:
+            return f"{x:,.2f}"
+        return f"{x:.4f}"
+    except:
+        return str(x)
+
+
+def build_df_from_dict(data):
+    rows = []
+    for k, v in data.items():
+        if is_noise(k):
+            continue
+        if isinstance(v, (int, float)):
+            v = format_number(v)
+        rows.append([k, v])
+    return pd.DataFrame(rows, columns=["Field", "Value"])
+
+
+# ======================================================
+# MAIN ENTRY (CACHED)
+# ======================================================
+def fetch_info(symbol):
+    cache_key = f"info_{symbol}"
+
+    if exists(cache_key, "html"):
+        cached = load(cache_key, "html")
+        if cached:
+            return cached
+
+    try:
+        raw = yfinfo(symbol)
+        if not raw or "__error__" in raw:
+            return "No data"
+
+        info, long_text, new_to_old, _ = process_info(raw)
+        groups = build_grouped_info(info, new_to_old)
+
+        html = ""
+
+        # ---- PRICE / VOLUME ----
+        pv = resolve_duplicates(groups["price_volume"], new_to_old)
+        for new_k, v in pv.items():
+            html += f"<div><b>{new_k}</b> : {v}</div>"
+
+        # ---- FUNDAMENTALS ----
+        for new_k, v in groups["fundamental"].items():
+            html += f"<div><b>{new_k}</b> : {v}</div>"
+
+        # ---- PROFILE ----
+        for new_k, v in groups["profile"].items():
+            html += f"<div><b>{new_k}</b> : {v}</div>"
+
+        # ---- LONG TEXT ----
+        for v in long_text.values():
+            html += f"<div style='margin-top:8px'>{v}</div>"
+
+        save(cache_key, html, "html")
+        return html
+
+    except Exception:
+        return f"<pre>{traceback.format_exc()}</pre>"