Delete nse.py

nse.py

@@ -1,204 +0,0 @@
-import requests
-import pandas as pd
-from datetime import datetime
-
-# ================================
-# NSE Base Settings
-# ================================
-NSE_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-Language": "en-US,en;q=0.9",
-}
-
-# Persistent session
-session = requests.Session()
-session.get("https://www.nseindia.com", headers=NSE_HEADERS, timeout=5)
-
-
-# ================================
-# Helper: Convert DataFrame to HTML
-# ================================
-def _to_html(title, df):
-    if df is None or df.empty:
-        return f"<h3>{title}</h3><p>No data available</p>"
-    return f"<h3>{title}</h3>" + df.to_html(index=False, border=1)
-
-
-# ================================
-# Helper: Perform GET request
-# ================================
-def _get_json(url):
-    try:
-        r = session.get(url, headers=NSE_HEADERS, timeout=5)
-        r.raise_for_status()
-        return r.json()
-    except Exception as e:
-        return {"error": str(e)}
-
-
-# ================================
-# 1. Stock Quote
-# ================================
-def nse_stock(symbol):
-    url = f"https://www.nseindia.com/api/quote-equity?symbol={symbol.upper()}"
-    data = _get_json(url)
-
-    if "error" in data:
-        return f"<p>Error fetching stock: {data['error']}</p>"
-
-    info = pd.json_normalize(data.get("info", {}))
-    price = pd.json_normalize(data.get("priceInfo", {}))
-    meta = pd.json_normalize(data.get("metadata", {}))
-
-    html = ""
-    html += _to_html("Stock Info", info)
-    html += _to_html("Price Info", price)
-    html += _to_html("Metadata", meta)
-    return html
-
-
-# ================================
-# 2. F&O / Option Chain
-# ================================
-def nse_fno(symbol):
-    url = f"https://www.nseindia.com/api/option-chain-equities?symbol={symbol.upper()}"
-    data = _get_json(url)
-
-    if "error" in data:
-        return f"<p>Error fetching FNO: {data['error']}</p>"
-
-    records = data.get("records", {})
-    all_data = pd.DataFrame(records.get("data", []))
-
-    ce_list = [x["CE"] for x in records.get("data", []) if "CE" in x]
-    pe_list = [x["PE"] for x in records.get("data", []) if "PE" in x]
-
-    df_ce = pd.DataFrame(ce_list)
-    df_pe = pd.DataFrame(pe_list)
-
-    html = ""
-    html += _to_html("F&O Combined", all_data)
-    html += _to_html("CALL Options (CE)", df_ce)
-    html += _to_html("PUT Options (PE)", df_pe)
-    return html
-
-
-# ================================
-# 3. Futures Data
-# ================================
-def nse_future(symbol):
-    url = f"https://www.nseindia.com/api/quote-derivative?symbol={symbol.upper()}"
-    data = _get_json(url)
-
-    if "error" in data:
-        return f"<p>Error fetching futures: {data['error']}</p>"
-
-    futures = pd.DataFrame(data.get("stocks", []))
-    meta = pd.json_normalize(data.get("info", {}))
-
-    html = ""
-    html += _to_html("Futures Data", futures)
-    html += _to_html("Metadata", meta)
-    return html
-
-
-# ================================
-# 4. 52-Week High / Low
-# ================================
-def nse_high_low():
-    url = "https://www.nseindia.com/api/market-data-52Week"
-    data = _get_json(url)
-
-    if "error" in data:
-        return f"<p>Error fetching high-low: {data['error']}</p>"
-
-    high = pd.DataFrame(data.get("FiftyTwoWeekHigh", []))
-    low = pd.DataFrame(data.get("FiftyTwoWeekLow", []))
-
-    html = ""
-    html += _to_html("52 Week High", high)
-    html += _to_html("52 Week Low", low)
-    return html
-
-
-# ================================
-# 5. Bhavcopy (date format flexible)
-# ================================
-def nse_bhav(date_str):
-    """
-    date_str: DD-MM-YYYY, DD/MM/YYYY, or DDMMYYYY
-    """
-    try:
-        if "-" in date_str:
-            dt = datetime.strptime(date_str, "%d-%m-%Y")
-        elif "/" in date_str:
-            dt = datetime.strptime(date_str, "%d/%m/%Y")
-        elif len(date_str) == 8:
-            dt = datetime.strptime(date_str, "%d%m%Y")
-        else:
-            return f"<p>Invalid date format: {date_str}</p>"
-    except Exception as e:
-        return f"<p>Error parsing date: {e}</p>"
-
-    date_api = dt.strftime("%d-%m-%Y")
-    url = f"https://www.nseindia.com/api/reports?archives=true&date={date_api}&type=equities&mode=single"
-    data = _get_json(url)
-
-    if "error" in data:
-        return f"<p>Error fetching bhavcopy: {data['error']}</p>"
-
-    df = pd.DataFrame(data.get("data", []))
-    return _to_html(f"Bhavcopy {date_api}", df)
-
-
-# ================================
-# 6. All NSE Indices
-# ================================
-def nse_indices():
-    url = "https://www.nseindia.com/api/allIndices"
-    data = _get_json(url)
-
-    if "error" in data:
-        return f"<p>Error fetching indices: {data['error']}</p>"
-
-    df = pd.DataFrame(data.get("data", []))
-    return _to_html("All NSE Indices", df)
-
-
-# ================================
-# 7. NSE Open Market Data
-# ================================
-def nse_open(index_name="NIFTY 50"):
-    url = f"https://www.nseindia.com/api/equity-stockIndices?index={index_name.replace(' ', '%20')}"
-    data = _get_json(url)
-
-    if "error" in data:
-        return f"<p>Error fetching open data: {data['error']}</p>"
-
-    meta = pd.json_normalize(data.get("metadata", {}))
-    df = pd.DataFrame(data.get("data", []))
-
-    html = ""
-    html += _to_html("Index Metadata", meta)
-    html += _to_html("Index Open Data", df)
-    return html
-
-
-# ================================
-# 8. NSE Pre-Open Market Data
-# ================================
-def nse_preopen(index_name="NIFTY 50"):
-    url = "https://www.nseindia.com/api/market-data-pre-open?key=NIFTY"
-    data = _get_json(url)
-
-    if "error" in data:
-        return f"<p>Error fetching preopen: {data['error']}</p>"
-
-    df = pd.DataFrame(data.get("data", []))
-    meta = pd.json_normalize(data.get("metadata", {}))
-
-    html = ""
-    html += _to_html("Pre-Open Metadata", meta)
-    html += _to_html("Pre-Open Market Data", df)
-    return html