Update nsepython.py

nsepython.py

@@ -1,61 +1,29 @@
-# ===============================================================
-# Core imports (kept exactly as requested)
-# ===============================================================
 import os, sys, requests, pandas as pd, json, random, datetime, time, logging, re, urllib.parse
 from collections import Counter
 
+mode = 'local'
 
-# ===============================================================
-# Runtime mode
-#   - "local": direct requests.Session
-#   - "vpn"  : curl + cookie based access
-# ===============================================================
-mode = "local"
-
-
-# ===============================================================
-# NSE FETCH HANDLER
-#   Single unified fetch function
-#   Auto-handles cookies, headers, and retries
-# ===============================================================
-
+# ------------------------- NSE FETCH -------------------------
 if mode == "vpn":
-
     def nsefetch(payload):
-        """
-        NSE fetch using curl + cookies (VPN-safe mode)
-        """
-
-        def encode(url):
-            return url if "%26" in url or "%20" in url else urllib.parse.quote(url, safe=":/?&=")
-
+        def encode(url): return url if "%26" in url or "%20" in url else urllib.parse.quote(url, safe=":/?&=")
         def refresh_cookies():
             os.popen(f'curl -c cookies.txt "https://www.nseindia.com" {curl_headers}').read()
             os.popen(f'curl -b cookies.txt -c cookies.txt "https://www.nseindia.com/option-chain" {curl_headers}').read()
 
-        if not os.path.exists("cookies.txt"):
-            refresh_cookies()
-
+        if not os.path.exists("cookies.txt"): refresh_cookies()
         encoded = encode(payload)
         cmd = f'curl -b cookies.txt "{encoded}" {curl_headers}'
         raw = os.popen(cmd).read()
-
-        try:
-            return json.loads(raw)
+        try: return json.loads(raw)
         except:
             refresh_cookies()
             raw = os.popen(cmd).read()
-            try:
-                return json.loads(raw)
-            except:
-                return {}
-
-else:
+            try: return json.loads(raw)
+            except: return {}
 
+if mode == 'local':
     def nsefetch(payload):
-        """
-        NSE fetch using requests.Session (local / HF safe)
-        """
         try:
             s = requests.Session()
             s.get("https://www.nseindia.com", headers=headers, timeout=10)
@@ -64,229 +32,185 @@ else:
         except:
             return {}
 
-
-# ===============================================================
-# HTTP HEADERS
-# ===============================================================
-
+# ------------------------- HEADERS -------------------------
 headers = {
-    "accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8",
-    "accept-language": "en-US,en;q=0.9,en-IN;q=0.8",
+    "accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7",
+    "accept-language": "en-US,en;q=0.9,en-IN;q=0.8,en-GB;q=0.7",
     "cache-control": "max-age=0",
-    "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64)"
+    "priority": "u=0, i",
+    "sec-ch-ua": '"Microsoft Edge";v="129","Not=A?Brand";v="8","Chromium";v="129"',
+    "sec-ch-ua-mobile": "?0",
+    "sec-ch-ua-platform": '"Windows"',
+    "sec-fetch-dest": "document",
+    "sec-fetch-mode": "navigate",
+    "sec-fetch-site": "none",
+    "sec-fetch-user": "?1",
+    "upgrade-insecure-requests": "1",
+    "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36 Edg/129.0.0.0"
 }
 
 niftyindices_headers = {
-    "Accept": "application/json,text/javascript,*/*;q=0.01",
-    "Content-Type": "application/json; charset=UTF-8",
-    "Origin": "https://niftyindices.com",
-    "Referer": "https://niftyindices.com/reports/historical-data",
-    "User-Agent": "Mozilla/5.0"
+    'Connection': 'keep-alive',
+    'sec-ch-ua': '"Not;A Brand";v="99","Google Chrome";v="91","Chromium";v="91"',
+    'Accept': 'application/json,text/javascript,*/*;q=0.01',
+    'DNT': '1',
+    'X-Requested-With': 'XMLHttpRequest',
+    'sec-ch-ua-mobile': '?0',
+    'User-Agent': 'Mozilla/5.0',
+    'Content-Type': 'application/json; charset=UTF-8',
+    'Origin': 'https://niftyindices.com',
+    'Sec-Fetch-Site': 'same-origin',
+    'Sec-Fetch-Mode': 'cors',
+    'Sec-Fetch-Dest': 'empty',
+    'Referer': 'https://niftyindices.com/reports/historical-data',
+    'Accept-Language': 'en-US,en;q=0.9,hi;q=0.8'
 }
 
-curl_headers = '''
--H "authority: beta.nseindia.com"
--H "cache-control: max-age=0"
--H "user-agent: Mozilla/5.0"
--H "accept: */*"
---compressed
-'''
-
+curl_headers = ''' -H "authority: beta.nseindia.com" -H "cache-control: max-age=0" -H "dnt: 1" -H "upgrade-insecure-requests: 1" -H "user-agent: Mozilla/5.0" -H "sec-fetch-user: ?1" -H "accept: */*" -H "sec-fetch-site: none" -H "accept-language: en-US,en;q=0.9" --compressed'''
 
-# ===============================================================
-# Runtime metadata
-# ===============================================================
 run_time = datetime.datetime.now()
-indices = ["NIFTY", "FINNIFTY", "BANKNIFTY"]
-
-
-# ===============================================================
-# Helper utilities
-# ===============================================================
-
-def nsesymbolpurify(s):
-    """Encode special NSE symbols"""
-    return s.replace("&", "%26")
+indices = ['NIFTY','FINNIFTY','BANKNIFTY']
 
+# ------------------------- HELPERS -------------------------
+def nsesymbolpurify(s): return s.replace('&','%26')
 
 def flatten_dict(d, parent="", sep="."):
-    """Flatten nested dictionaries"""
-    items = {}
-    for k, v in d.items():
+    items={}
+    for k,v in d.items():
         nk = f"{parent}{sep}{k}" if parent else k
-        if isinstance(v, dict):
-            items.update(flatten_dict(v, nk, sep))
-        else:
-            items[nk] = v
+        if isinstance(v, dict): items.update(flatten_dict(v, nk, sep))
+        else: items[nk] = v
     return items
 
-
 def flatten_nested(d, prefix=""):
-    """Flatten dicts + lists (deep NSE JSON support)"""
-    flat = {}
-    for k, v in d.items():
-        nk = f"{prefix}{k}" if prefix == "" else f"{prefix}.{k}"
+    flat={}
+    for k,v in d.items():
+        nk = f"{prefix}{k}" if prefix=="" else f"{prefix}.{k}"
         if isinstance(v, dict):
             flat.update(flatten_nested(v, nk))
         elif isinstance(v, list):
             if v and isinstance(v[0], dict):
-                for i, x in enumerate(v):
-                    flat.update(flatten_nested(x, f"{nk}.{i}"))
-            else:
-                flat[nk] = v
-        else:
-            flat[nk] = v
+                for i,x in enumerate(v): flat.update(flatten_nested(x, f"{nk}.{i}"))
+            else: flat[nk]=v
+        else: flat[nk]=v
     return flat
 
-
 def rename_col(cols):
-    """Resolve duplicate column names after flattening"""
-    child = [c.split(".")[-1] for c in cols]
-    cnt = Counter(child)
-    new = []
-    for c, ch in zip(cols, child):
-        if cnt[ch] == 1:
-            new.append(ch)
+    child=[c.split('.')[-1] for c in cols]
+    cnt=Counter(child)
+    new=[]
+    for c,ch in zip(cols,child):
+        if cnt[ch]==1: new.append(ch)
         else:
-            p = c.split(".")
-            new.append(f"{p[-1]}_{p[-2]}" if len(p) >= 2 else p[-1])
+            p=c.split('.')
+            new.append(f"{p[-1]}_{p[-2]}" if len(p)>=2 else p[-1])
     return new
 
-
 def df_from_data(data):
-    """Convert NSE JSON array into clean DataFrame"""
-    rows = [flatten_nested(x) if isinstance(x, dict) else {"value": x} for x in data]
-    df = pd.DataFrame(rows)
-    df.columns = rename_col(df.columns)
+    rows=[ flatten_nested(x) if isinstance(x,dict) else {"value":x} for x in data ]
+    df=pd.DataFrame(rows)
+    df.columns=rename_col(df.columns)
     return df
 
-
-# ===============================================================
-# API WRAPPERS (No name changes)
-# ===============================================================
-
+# ------------------------- API FUNCTIONS -------------------------
 def indices():
-    p = nsefetch("https://www.nseindia.com/api/allIndices")
-    return {
-        "data": pd.DataFrame(p.pop("data")),
-        "dates": pd.DataFrame([p.pop("dates")]),
-        "indices": pd.DataFrame([p])
-    }
-
+    p=nsefetch("https://www.nseindia.com/api/allIndices")
+    return {"data":pd.DataFrame(p.pop("data")), "dates":pd.DataFrame([p.pop("dates")]), "indices":pd.DataFrame([p])}
 
 def eq(symbol):
-    symbol = nsesymbolpurify(symbol)
-    df = nsefetch(f"https://www.nseindia.com/api/quote-equity?symbol={symbol}")
-    pre = df.pop("preOpenMarket")
-
-    return {
+    symbol=nsesymbolpurify(symbol)
+    df=nsefetch(f'https://www.nseindia.com/api/quote-equity?symbol={symbol}')
+    pre=df.pop('preOpenMarket')
+    out={
         "securityInfo": pd.DataFrame([df["securityInfo"]]),
         "priceInfo": pd.DataFrame([flatten_dict(df["priceInfo"])]),
         "industryInfo": pd.DataFrame([df["industryInfo"]]),
         "pdSectorIndAll": pd.DataFrame([df["metadata"].pop("pdSectorIndAll")]),
         "metadata": pd.DataFrame([df["metadata"]]),
         "info": pd.DataFrame([df["info"]]),
-        "preOpen": pd.DataFrame(pre.pop("preopen")),
+        "preOpen": pd.DataFrame(pre.pop('preopen')),
         "preOpenMarket": pd.DataFrame([pre])
     }
+    return out
 
+def eq_fno(): return nsefetch('https://www.nseindia.com/api/equity-stockIndices?index=SECURITIES%20IN%20F%26O')
+def eq_der(symbol): return nsefetch('https://www.nseindia.com/api/quote-derivative?symbol='+nsesymbolpurify(symbol))
+def index_chain(symbol): return nsefetch('https://www.nseindia.com/api/option-chain-indices?symbol='+nsesymbolpurify(symbol))
+def eq_chain(symbol): return nsefetch('https://www.nseindia.com/api/option-chain-equities?symbol='+nsesymbolpurify(symbol))
+def nse_holidays(t="trading"): return nsefetch('https://www.nseindia.com/api/holiday-master?type='+t)
 
-def eq_fno():
-    return nsefetch("https://www.nseindia.com/api/equity-stockIndices?index=SECURITIES%20IN%20F%26O")
-
-
-def eq_der(symbol):
-    return nsefetch("https://www.nseindia.com/api/quote-derivative?symbol=" + nsesymbolpurify(symbol))
-
-
-def index_chain(symbol):
-    return nsefetch("https://www.nseindia.com/api/option-chain-indices?symbol=" + nsesymbolpurify(symbol))
-
-
-def eq_chain(symbol):
-    return nsefetch("https://www.nseindia.com/api/option-chain-equities?symbol=" + nsesymbolpurify(symbol))
-
-
-def nse_holidays(t="trading"):
-    return nsefetch("https://www.nseindia.com/api/holiday-master?type=" + t)
-
-
-def nse_results(index="equities", period="Quarterly"):
-    if index in ["equities", "debt", "sme"] and period in ["Quarterly", "Annual", "Half-Yearly", "Others"]:
-        return pd.json_normalize(
-            nsefetch(f"https://www.nseindia.com/api/corporates-financial-results?index={index}&period={period}")
-        )
+def nse_results(index="equities",period="Quarterly"):
+    if index in ["equities","debt","sme"] and period in ["Quarterly","Annual","Half-Yearly","Others"]:
+        return pd.json_normalize(nsefetch(f'https://www.nseindia.com/api/corporates-financial-results?index={index}&period={period}'))
     print("Invalid Input")
 
-
-def nse_events():
-    return pd.json_normalize(nsefetch("https://www.nseindia.com/api/event-calendar"))
-
-
-def nse_past_results(symbol):
-    return nsefetch("https://www.nseindia.com/api/results-comparision?symbol=" + nsesymbolpurify(symbol))
-
-
-def nse_blockdeal():
-    return nsefetch("https://nseindia.com/api/block-deal")
-
-
-def nse_marketStatus():
-    return nsefetch("https://nseindia.com/api/marketStatus")
-
-
+def nse_events(): return pd.json_normalize(nsefetch('https://www.nseindia.com/api/event-calendar'))
+def nse_past_results(symbol): return nsefetch('https://www.nseindia.com/api/results-comparision?symbol='+nsesymbolpurify(symbol))
+def nse_blockdeal(): return nsefetch('https://nseindia.com/api/block-deal')
+def nse_marketStatus(): return nsefetch('https://nseindia.com/api/marketStatus')
 def nse_circular(mode="latest"):
-    return nsefetch(
-        "https://www.nseindia.com/api/latest-circular"
-        if mode == "latest"
-        else "https://www.nseindia.com/api/circulars"
-    )
-
+    return nsefetch('https://www.nseindia.com/api/latest-circular' if mode=="latest" else 'https://www.nseindia.com/api/circulars')
 
 def nse_fiidii(mode="pandas"):
-    return pd.DataFrame(nsefetch("https://www.nseindia.com/api/fiidiiTradeReact"))
-
+    
+    p=nsefetch('https://www.nseindia.com/api/fiidiiTradeReact')
+    return pd.DataFrame(p)
 
 def nsetools_get_quote(symbol):
-    p = nsefetch("https://www.nseindia.com/api/equity-stockIndices?index=SECURITIES%20IN%20F%26O")
-    for x in p["data"]:
-        if x["symbol"] == symbol.upper():
-            return x
-
+    p=nsefetch('https://www.nseindia.com/api/equity-stockIndices?index=SECURITIES%20IN%20F%26O')
+    for x in p['data']:
+        if x['symbol']==symbol.upper(): return x
 
 def nse_index():
-    p = nsefetch("https://iislliveblob.niftyindices.com/jsonfiles/LiveIndicesWatch.json")
-    return pd.DataFrame(p["data"])
+    p=nsefetch('https://iislliveblob.niftyindices.com/jsonfiles/LiveIndicesWatch.json')
+    return pd.DataFrame(p['data'])
 
+def index_history(sym,sd,ed):
+    d={'cinfo':f"{{'name':'{sym}','startDate':'{sd}','endDate':'{ed}','indexName':'{sym}'}}"}
+    p=json.loads(requests.post('https://niftyindices.com/Backpage.aspx/getHistoricaldatatabletoString', headers=niftyindices_headers, json=d).json()["d"])
+    return pd.DataFrame.from_records(p)
 
-# ===============================================================
-# Historical / CSV endpoints
-# ===============================================================
+def index_pe_pb_div(sym,sd,ed):
+    d={'cinfo':f"{{'name':'{sym}','startDate':'{sd}','endDate':'{ed}','indexName':'{sym}'}}"}
+    p=json.loads(requests.post('https://niftyindices.com/Backpage.aspx/getpepbHistoricaldataDBtoString', headers=niftyindices_headers, json=d).json()["d"])
+    return pd.DataFrame.from_records(p)
 
-def nse_bhavcopy(d):
-    return pd.read_csv(
-        "https://archives.nseindia.com/products/content/sec_bhavdata_full_" + d.replace("-", "") + ".csv"
-    )
+def index_total_returns(sym,sd,ed):
+    d={'cinfo':f"{{'name':'{sym}','startDate':'{sd}','endDate':'{ed}','indexName':'{sym}'}}"}
+    p=json.loads(requests.post('https://niftyindices.com/Backpage.aspx/getTotalReturnIndexString', headers=niftyindices_headers, json=d).json()["d"])
+    return pd.DataFrame.from_records(p)
 
+def nse_bhavcopy(d): return pd.read_csv("https://archives.nseindia.com/products/content/sec_bhavdata_full_"+d.replace("-","")+".csv")
+def nse_bulkdeals(): return pd.read_csv("https://archives.nseindia.com/content/equities/bulk.csv")
+def nse_blockdeals(): return pd.read_csv("https://archives.nseindia.com/content/equities/block.csv")
 
-def nse_highlow(d: str) -> pd.DataFrame:
-    date_str = d.replace("-", "")
-    url = f"https://archives.nseindia.com/content/CM_52_wk_High_low_{date_str}.csv"
-    df = pd.read_csv(url, skiprows=2, engine="python")
-    df.columns = df.columns.str.strip()
-    return df
+def nse_preopen(key="NIFTY"):
+    p=nsefetch("https://www.nseindia.com/api/market-data-pre-open?key="+key)
+    return {"data":df_from_data(p.pop("data")), "rem":df_from_data([p])}
 
+def nse_most_active(t="securities",s="value"):
+    return pd.DataFrame(nsefetch(f"https://www.nseindia.com/api/live-analysis-most-active-{t}?index={s}")["data"])
 
-def nse_bulkdeals():
-    return pd.read_csv("https://archives.nseindia.com/content/equities/bulk.csv")
+def nse_eq_symbols():
+    return pd.read_csv('https://archives.nseindia.com/content/equities/EQUITY_L.csv')['SYMBOL'].tolist()
 
+def nse_price_band_hitters(b="both",v="AllSec"):
+    p=nsefetch("https://www.nseindia.com/api/live-analysis-price-band-hitter")
+    return {"data":pd.DataFrame(p[b][v]["data"]), "count":pd.DataFrame([p['count']])}
+
+def nse_largedeals(mode="bulk_deals"):
+    p=nsefetch('https://www.nseindia.com/api/snapshot-capital-market-largedeal')
+    return pd.DataFrame(p["BULK_DEALS_DATA" if mode=="bulk_deals" else "SHORT_DEALS_DATA" if mode=="short_deals" else "BLOCK_DEALS_DATA"])
+
+def nse_largedeals_historical(f,t,mode="bulk_deals"):
+    m = "bulk-deals" if mode=="bulk_deals" else "short-selling" if mode=="short_deals" else "block-deals"
+    p=nsefetch(f'https://www.nseindia.com/api/historical/{m}?from={f}&to={t}')
+    return pd.DataFrame(p["data"])
 
-def nse_blockdeals():
-    return pd.read_csv("https://archives.nseindia.com/content/equities/block.csv")
 def nse_stock_hist(f,t,symbol,series="ALL"):
     url=f"https://www.nseindia.com/api/historical/securityArchives?from={f}&to={t}&symbol={symbol.upper()}&dataType=priceVolumeDeliverable&series={series}"
-    payload=nsefetch(url)
-    print(payload)
-    df=pd.DataFrame(payload["data"])
-    return df
-    
+    return pd.DataFrame(nsefetch(url)['data'])
+
+def nse_index_live(name="NIFTY 50"):
+    p=nsefetch(f"https://www.nseindia.com/api/equity-stockIndices?index={name.replace(' ','%20')}")
+    return {"data":df_from_data(p.pop("data")) if "data" in p else pd.DataFrame(), "rem":df_from_data([p])}