nsepython.py

import os, sys, requests, pandas as pd, json, random, datetime, time, logging, re, urllib.parse
from collections import Counter

mode = 'local'

# ------------------------- NSE FETCH -------------------------
if mode == "vpn":
    def nsefetch(payload):
        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()
        encoded = encode(payload)
        cmd = f'curl -b cookies.txt "{encoded}" {curl_headers}'
        raw = os.popen(cmd).read()
        try: return json.loads(raw)
        except:
            refresh_cookies()
            raw = os.popen(cmd).read()
            try: return json.loads(raw)
            except: return {}

if mode == 'local':
    def nsefetch(payload):
        try:
            s = requests.Session()
            s.get("https://www.nseindia.com", headers=headers, timeout=10)
            s.get("https://www.nseindia.com/option-chain", headers=headers, timeout=10)
            return s.get(payload, headers=headers, timeout=10).json()
        except:
            return {}

# ------------------------- HEADERS -------------------------
headers = {
    "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",
    "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 = {
    '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 "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'''

run_time = datetime.datetime.now()
indices = ['NIFTY','FINNIFTY','BANKNIFTY']

# ------------------------- HELPERS -------------------------
def nsesymbolpurify(s): return s.replace('&','%26')

def flatten_dict(d, parent="", sep="."):
    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
    return items

def flatten_nested(d, prefix=""):
    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
    return flat

def rename_col(cols):
    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])
    return new

def df_from_data(data):
    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 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])}

def eq(symbol):
    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')),
        "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 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_circular(mode="latest"):
    return nsefetch('https://www.nseindia.com/api/latest-circular' if mode=="latest" else 'https://www.nseindia.com/api/circulars')

def nse_fiidii(mode="pandas"):
    try:
        p=nsefetch('https://www.nseindia.com/api/fiidiiTradeReact')
        return pd.DataFrame(p) if mode=="pandas" else p
    except:
        return nsefetch('https://www.nseindia.com/api/fiidiiTradeReact')

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

def nse_index():
    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)

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 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 get_bhavcopy(d): return pd.read_csv("https://archives.nseindia.com/products/content/sec_bhavdata_full_"+d.replace("-","")+".csv")
def get_bulkdeals(): return pd.read_csv("https://archives.nseindia.com/content/equities/bulk.csv")
def get_blockdeals(): return pd.read_csv("https://archives.nseindia.com/content/equities/block.csv")

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_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 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}"
    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])}
import json
import pandas as pd
from nsepython import *

def build_indices_html2():

    p = indices()

    data_df = p["data"]
    dates_df = p["dates"]

    data_json = json.dumps(data_df.to_dict(orient="records"), ensure_ascii=False)
    dates_json = json.dumps(dates_df.to_dict(orient="records"), ensure_ascii=False)

    DEFAULT_KEY = "INDICES ELIGIBLE IN DERIVATIVES"
    DEFAULT_SYMBOL = "NIFTY 50"

    html = f"""
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<title>NSE Indices Dashboard</title>

<style>
body {{
    font-family: Arial, sans-serif;
    padding: 20px;
}}

button {{
    padding: 7px 14px;
    margin-bottom: 10px;
    cursor: pointer;
}}

.scroll-table {{
    width: 100%;
    overflow: auto;
    border: 1px solid #ccc;
    max-height: 450px;
    margin-bottom: 20px;
}}

table {{
    border-collapse: collapse;
    width: max-content;
    min-width: 100%;
}}

th, td {{
    border: 1px solid #ddd;
    padding: 8px;
    white-space: nowrap;
}}

th {{
    background-color: #007bff;
    color: white;
    position: sticky;
    top: 0;
    z-index: 5;
}}

.chart-grid {{
    display: grid;
    grid-template-columns: 1fr 1fr;
    grid-template-rows: 200px 200px;
    gap: 20px;
}}

.chart-box {{
    width: 100%;
    height: 100%;
    border: 1px solid #ccc;
}}

#chart365 {{
    grid-column: 1 / 3;
}}

select {{
    padding: 6px;
    margin: 8px 0;
}}
</style>

</head>
<body>

<h2>NSE Indices Dashboard</h2>

<script>
const records = {data_json};
const dates = {dates_json};
const DEFAULT_KEY = "{DEFAULT_KEY}";
const DEFAULT_SYMBOL = "{DEFAULT_SYMBOL}";
</script>

<!-- MAIN TABLE -->
<h3>Main Full Indices Table</h3>
<button onclick="toggleMainTable()">Show / Hide Main Table</button>

<div id="mainTableSection" class="scroll-table" style="display:none;">
    <table id="mainTable"></table>
</div>

<hr>

<!-- FILTERED TABLE -->
<h3>Filter Table by Category</h3>

<label><b>Select Index Category:</b></label>
<select id="keyDropdown"></select>

<div id="altTableSection" class="scroll-table">
    <table id="altTable"></table>
</div>

<hr>

<!-- CHARTS -->
<h3>Charts Based on Index</h3>

<label><b>Select Index:</b></label>
<select id="chartDropdown"></select>

<div class="chart-grid">
    <iframe id="chartToday" class="chart-box"></iframe>
    <iframe id="chart30" class="chart-box"></iframe>
    <iframe id="chart365" class="chart-box"></iframe>
</div>

<script>

// ================= MAIN TABLE =================

function buildMainTable() {{
    const table = document.getElementById("mainTable");
    const cols = Object.keys(records[0]);

    let header = "<tr>";
    cols.forEach(c => header += `<th>${{c}}</th>`);
    header += "</tr>";

    let rows = "";
    records.forEach(r => {{
        rows += "<tr>";
        cols.forEach(c => rows += `<td>${{r[c]}}</td>`);
        rows += "</tr>";
    }});

    table.innerHTML = header + rows;
}}

function toggleMainTable() {{
    const sec = document.getElementById("mainTableSection");
    sec.style.display = sec.style.display === "none" ? "block" : "none";
}}

buildMainTable();


// ================= FILTERED TABLE =================

const keyDropdown = document.getElementById("keyDropdown");
const chartDropdown = document.getElementById("chartDropdown");

const keyList = [...new Set(records.map(r => r.key))];
keyList.forEach(k => {{
    const opt = document.createElement("option");
    opt.value = k;
    opt.textContent = k;
    if (k === DEFAULT_KEY) opt.selected = true;
    keyDropdown.appendChild(opt);
}});

function buildAltTable(keyName) {{
    const table = document.getElementById("altTable");

    const filtered = records.filter(r => r.key === keyName);

    if (!filtered.length) {{
        table.innerHTML = "<tr><td>No Data</td></tr>";
        return;
    }}

    const hiddenCols = [
        "key","chartTodayPath","chart30dPath","chart30Path","chart365dPath",
        "date365dAgo","date30dAgo","previousDay","oneWeekAgo","oneMonthAgoVal",
        "oneWeekAgoVal","oneYearAgoVal","index","indicativeClose"
    ];

    const cols = Object.keys(filtered[0]).filter(c => !hiddenCols.includes(c));

    let header = "<tr>";
    cols.forEach(c => header += `<th>${{c}}</th>`);
    header += "</tr>";

    let rows = "";
    filtered.forEach(obj => {{
        rows += "<tr>";
        cols.forEach(c => rows += `<td>${{obj[c]}}</td>`);
        rows += "</tr>";
    }});

    table.innerHTML = header + rows;
}}


// ================= CHARTS =================

function populateChartDropdown(keyVal) {{
    chartDropdown.innerHTML = "";

    records.filter(r => r.key === keyVal).forEach(r => {{
        const opt = document.createElement("option");
        opt.value = r.indexSymbol;
        opt.textContent = r.index;
        chartDropdown.appendChild(opt);
    }});

    // auto select default
    [...chartDropdown.options].forEach(opt => {{
        if (opt.textContent.toUpperCase().includes(DEFAULT_SYMBOL.toUpperCase()))
            opt.selected = true;
    }});
}}

function loadCharts(symbol) {{
    const row = records.find(r => r.indexSymbol === symbol);
    if (!row) return;

    document.getElementById("chartToday").src = row.chartTodayPath;
    document.getElementById("chart30").src = row.chart30dPath || row.chart30Path;
    document.getElementById("chart365").src = row.chart365dPath;
}}


// ================= EVENT HANDLERS =================

keyDropdown.addEventListener("change", () => {{
    const keyVal = keyDropdown.value;
    buildAltTable(keyVal);
    populateChartDropdown(keyVal);
    loadCharts(chartDropdown.value);
}});

chartDropdown.addEventListener("change", () => {{
    loadCharts(chartDropdown.value);
}});


// ================= INITIAL LOAD =================

buildAltTable(DEFAULT_KEY);
populateChartDropdown(DEFAULT_KEY);

let initial = records.find(
    r => r.index.toUpperCase().includes(DEFAULT_SYMBOL.toUpperCase())
);

if (!initial) initial = records[0];

loadCharts(initial.indexSymbol);

</script>

</body>
</html>
"""
    return html