Delete yahooinfo2.py

yahooinfo2.py

@@ -1,376 +0,0 @@
-
-# ==============================
-# Imports
-# ==============================
-import yfinance as yf
-import pandas as pd
-import traceback
-
-# ==============================
-# Yahoo Finance info fetch
-# ==============================
-def yfinfo(symbol):
-    try:
-        t = yf.Ticker(symbol+".NS")
-        info = t.info
-        if not info or not isinstance(info, dict):
-            return {}
-        return info
-    except Exception as e:
-        return {"__error__": str(e)}
-
-
-# ==============================
-# HTML card renderer
-# ==============================
-def html_card(title, body, mini=False):
-    font = "12px" if mini else "14px"
-    pad  = "6px" if mini else "10px"
-
-    return f"""
-    <div style="
-        background:#111;
-        border:1px solid #333;
-        border-radius:6px;
-        padding:{pad};
-        margin:6px 0;
-        color:#eee;
-        font-size:{font};
-    ">
-        <div style="
-            font-weight:600;
-            color:#6cf;
-            margin-bottom:4px;
-        ">
-            {title}
-        </div>
-        <div>{body}</div>
-    </div>
-    """
-
-
-# ==============================
-# DataFrame → HTML table
-# ==============================
-def make_table(df, compact=False):
-    if df is None or df.empty:
-        return "<i>No data</i>"
-
-    font = "11px" if compact else "13px"
-    pad  = "2px 6px" if compact else "4px 8px"
-
-    th = "".join(
-        f"<th style='padding:{pad};border-bottom:1px solid #444'>{c}</th>"
-        for c in df.columns
-    )
-
-    rows = ""
-    for _, r in df.iterrows():
-        tds = "".join(
-            f"<td style='padding:{pad};border-bottom:1px solid #222'>{v}</td>"
-            for v in r
-        )
-        rows += f"<tr>{tds}</tr>"
-
-    return f"""
-    <table style="
-        width:100%;
-        border-collapse:collapse;
-        font-size:{font};
-        color:#eee;
-    ">
-        <thead><tr>{th}</tr></thead>
-        <tbody>{rows}</tbody>
-    </table>
-    """
-
-
-# ==============================
-# Number formatting
-# ==============================
-def format_number(x):
-    try:
-        if x is None:
-            return "-"
-        x = float(x)
-        if abs(x) >= 100:
-            return f"{x:,.0f}"
-        if abs(x) >= 1:
-            return f"{x:,.2f}"
-        return f"{x:.4f}"
-    except Exception:
-        return str(x)
-
-
-def format_large_number(x):
-    try:
-        x = float(x)
-        for u in ["", "K", "M", "B", "T"]:
-            if abs(x) < 1000:
-                return f"{x:.2f}{u}"
-            x /= 1000
-        return f"{x:.2f}P"
-    except Exception:
-        return str(x)
-
-
-# ==============================
-# HTML error block
-# ==============================
-def html_error(msg):
-    return f"""
-    <div style="
-        background:#300;
-        color:#f88;
-        border:1px solid #800;
-        border-radius:6px;
-        padding:10px;
-        font-weight:600;
-    ">
-        ❌ {msg}
-    </div>
-    """
-# ------------------------------------------------------------
-# 1. Noise keys (internal Yahoo junk)
-# ------------------------------------------------------------
-NOISE_KEYS = {
-    "maxAge", "priceHint", "triggerable",
-    "customPriceAlertConfidence",
-    "sourceInterval", "exchangeDataDelayedBy",
-    "esgPopulated"
-}
-
-def is_noise(k):
-    return k in NOISE_KEYS
-
-
-# ------------------------------------------------------------
-# 2. Duplicate resolution priority
-# ------------------------------------------------------------
-DUPLICATE_PRIORITY = {
-    "price": ["regularMarketPrice", "currentPrice"],
-    "prev": ["regularMarketPreviousClose", "previousClose"],
-    "open": ["regularMarketOpen", "open"],
-    "high": ["regularMarketDayHigh", "dayHigh"],
-    "low": ["regularMarketDayLow", "dayLow"],
-    "volume": ["regularMarketVolume", "volume"],
-}
-
-def resolve_duplicates(data):
-    resolved = {}
-    used = set()
-
-    for _, keys in DUPLICATE_PRIORITY.items():
-        for k in keys:
-            if k in data:
-                resolved[k] = data[k]
-                used.update(keys)
-                break
-
-    for k, v in data.items():
-        if k not in used:
-            resolved[k] = v
-
-    return resolved
-
-
-# ------------------------------------------------------------
-# 3. Short display names (<=12 chars)
-# ------------------------------------------------------------
-SHORT_NAMES = {
-    "regularMarketPrice": "Price",
-    "regularMarketChange": "Chg",
-    "regularMarketChangePercent": "Chg%",
-    "regularMarketPreviousClose": "Prev",
-    "regularMarketOpen": "Open",
-    "regularMarketDayHigh": "High",
-    "regularMarketDayLow": "Low",
-
-    "regularMarketVolume": "Vol",
-    "averageDailyVolume10Day": "AvgV10",
-    "averageDailyVolume3Month": "AvgV3M",
-
-    "fiftyDayAverage": "50DMA",
-    "fiftyDayAverageChangePercent": "50DMA%",
-    "twoHundredDayAverage": "200DMA",
-    "twoHundredDayAverageChangePercent": "200DMA%",
-
-    "fiftyTwoWeekLow": "52WL",
-    "fiftyTwoWeekHigh": "52WH",
-    "fiftyTwoWeekRange": "52WR",
-
-    "beta": "Beta",
-
-    "targetHighPrice": "TgtH",
-    "targetLowPrice": "TgtL",
-    "targetMeanPrice": "Tgt",
-    "recommendationMean": "Reco",
-}
-
-def pretty_key(k):
-    return SHORT_NAMES.get(k, k[:12])
-
-
-# ------------------------------------------------------------
-# 4. Price / Volume sub-group classifier
-# ------------------------------------------------------------
-def classify_price_volume_subgroup(key):
-    k = key.lower()
-
-    if any(x in k for x in [
-        "price", "open", "close", "change", "day"
-    ]):
-        return "Live Price"
-
-    if "volume" in k:
-        return "Volume"
-
-    if "average" in k or "fiftyday" in k or "twohundredday" in k:
-        return "Moving Avg"
-
-    if any(x in k for x in ["week", "range", "high", "low", "alltime", "beta"]):
-        return "Range / Vol"
-
-    if any(x in k for x in ["bid", "ask", "target", "recommendation", "analyst"]):
-        return "Bid / Analyst"
-
-    return "Other"
-
-
-def build_price_volume_subgroups(data):
-    sub = {}
-    for k, v in data.items():
-        sg = classify_price_volume_subgroup(k)
-        sub.setdefault(sg, {})[k] = v
-    return sub
-
-
-# ------------------------------------------------------------
-# 5. Main key classifier
-# ------------------------------------------------------------
-def classify_key(key, value):
-    k = key.lower()
-
-    if isinstance(value, str) and len(value) > 80:
-        return "long_text"
-
-    if isinstance(value, (int, float)) and any(x in k for x in [
-        "price", "volume", "avg", "average", "change",
-        "percent", "market", "day", "week", "bid",
-        "ask", "beta", "target", "recommendation"
-    ]):
-        return "price_volume"
-
-    if any(x in k for x in [
-        "revenue", "income", "earnings", "profit",
-        "margin", "pe", "pb", "roe", "roa",
-        "cash", "debt", "equity", "dividend",
-        "ebitda", "growth", "ratio", "shares"
-    ]):
-        return "fundamental"
-
-    return "profile"
-
-
-# ------------------------------------------------------------
-# 6. Group builder
-# ------------------------------------------------------------
-def build_grouped_info(info):
-    groups = {
-        "price_volume": {},
-        "fundamental": {},
-        "profile": {},
-        "long_text": {}
-    }
-
-    for k, v in info.items():
-        if v in [None, "", [], {}]:
-            continue
-
-        grp = classify_key(k, v)
-        groups[grp][k] = v
-
-    return groups
-
-
-# ------------------------------------------------------------
-# 7. Final DataFrame builder
-# ------------------------------------------------------------
-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)
-        elif isinstance(v, list):
-            v = ", ".join(map(str, v[:5]))
-
-        rows.append([pretty_key(k), v])
-
-    return pd.DataFrame(rows, columns=["Field", "Value"])
-
-
-# ------------------------------------------------------------
-# 8. MAIN FUNCTION (NAME UNCHANGED)
-# ------------------------------------------------------------
-def fetch_info(symbol):
-    try:
-        info = yfinfo(symbol)
-        if not info:
-            return html_error(f"No information found for {symbol}")
-
-        groups = build_grouped_info(info)
-
-        final_html = ""
-
-        # ---------------- PRICE / VOLUME ----------------
-        price_data = groups["price_volume"]
-        price_data = resolve_duplicates(price_data)
-
-        price_subgroups = build_price_volume_subgroups(price_data)
-
-        price_html = ""
-        for title, data in price_subgroups.items():
-            df = build_df_from_dict(data)
-            if not df.empty:
-                price_html += html_card(
-                    title,
-                    make_table(df, compact=True),
-                    mini=True
-                )
-
-        if price_html:
-            final_html += html_card("📈 Price / Volume", price_html)
-
-        # ---------------- FUNDAMENTALS ----------------
-        if groups["fundamental"]:
-            df = build_df_from_dict(groups["fundamental"])
-            final_html += html_card(
-                "📊 Fundamentals",
-                make_table(df, compact=True)
-            )
-
-        # ---------------- PROFILE ----------------
-        if groups["profile"]:
-            df = build_df_from_dict(groups["profile"])
-            final_html += html_card(
-                "🏢 Company Profile",
-                make_table(df, compact=True)
-            )
-
-        # ---------------- LONG TEXT ----------------
-        for k, v in groups["long_text"].items():
-            final_html += html_card(
-                pretty_key(k),
-                f"<div class='long-text'>{v}</div>"
-            )
-
-        return final_html
-
-    except Exception as e:
-        return html_error(
-            f"INFO ERROR: {e}<br><pre>{traceback.format_exc()}</pre>"
-        )