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import os, sys, requests, pandas as pd, json, random, datetime, time, logging, re, urllib.parse |
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from collections import Counter |
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mode = 'local' |
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if mode == "vpn": |
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def nsefetch(payload): |
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def encode(url): return url if "%26" in url or "%20" in url else urllib.parse.quote(url, safe=":/?&=") |
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def refresh_cookies(): |
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os.popen(f'curl -c cookies.txt "https://www.nseindia.com" {curl_headers}').read() |
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os.popen(f'curl -b cookies.txt -c cookies.txt "https://www.nseindia.com/option-chain" {curl_headers}').read() |
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if not os.path.exists("cookies.txt"): refresh_cookies() |
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encoded = encode(payload) |
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cmd = f'curl -b cookies.txt "{encoded}" {curl_headers}' |
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raw = os.popen(cmd).read() |
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try: return json.loads(raw) |
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except: |
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refresh_cookies() |
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raw = os.popen(cmd).read() |
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try: return json.loads(raw) |
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except: return {} |
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if mode == 'local': |
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def nsefetch(payload): |
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try: |
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s = requests.Session() |
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s.get("https://www.nseindia.com", headers=headers, timeout=10) |
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s.get("https://www.nseindia.com/option-chain", headers=headers, timeout=10) |
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return s.get(payload, headers=headers, timeout=10).json() |
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except: |
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return {} |
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headers = { |
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"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", |
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"accept-language": "en-US,en;q=0.9,en-IN;q=0.8,en-GB;q=0.7", |
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"cache-control": "max-age=0", |
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"priority": "u=0, i", |
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"sec-ch-ua": '"Microsoft Edge";v="129","Not=A?Brand";v="8","Chromium";v="129"', |
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"sec-ch-ua-mobile": "?0", |
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"sec-ch-ua-platform": '"Windows"', |
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"sec-fetch-dest": "document", |
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"sec-fetch-mode": "navigate", |
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"sec-fetch-site": "none", |
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"sec-fetch-user": "?1", |
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"upgrade-insecure-requests": "1", |
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"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" |
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} |
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niftyindices_headers = { |
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'Connection': 'keep-alive', |
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'sec-ch-ua': '"Not;A Brand";v="99","Google Chrome";v="91","Chromium";v="91"', |
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'Accept': 'application/json,text/javascript,*/*;q=0.01', |
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'DNT': '1', |
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'X-Requested-With': 'XMLHttpRequest', |
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'sec-ch-ua-mobile': '?0', |
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'User-Agent': 'Mozilla/5.0', |
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'Content-Type': 'application/json; charset=UTF-8', |
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'Origin': 'https://niftyindices.com', |
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'Sec-Fetch-Site': 'same-origin', |
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'Sec-Fetch-Mode': 'cors', |
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'Sec-Fetch-Dest': 'empty', |
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'Referer': 'https://niftyindices.com/reports/historical-data', |
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'Accept-Language': 'en-US,en;q=0.9,hi;q=0.8' |
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} |
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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''' |
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run_time = datetime.datetime.now() |
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indices = ['NIFTY','FINNIFTY','BANKNIFTY'] |
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def nsesymbolpurify(s): return s.replace('&','%26') |
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def flatten_dict(d, parent="", sep="."): |
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items={} |
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for k,v in d.items(): |
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nk = f"{parent}{sep}{k}" if parent else k |
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if isinstance(v, dict): items.update(flatten_dict(v, nk, sep)) |
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else: items[nk] = v |
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return items |
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def flatten_nested(d, prefix=""): |
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flat={} |
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for k,v in d.items(): |
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nk = f"{prefix}{k}" if prefix=="" else f"{prefix}.{k}" |
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if isinstance(v, dict): |
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flat.update(flatten_nested(v, nk)) |
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elif isinstance(v, list): |
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if v and isinstance(v[0], dict): |
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for i,x in enumerate(v): flat.update(flatten_nested(x, f"{nk}.{i}")) |
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else: flat[nk]=v |
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else: flat[nk]=v |
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return flat |
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def rename_col(cols): |
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child=[c.split('.')[-1] for c in cols] |
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cnt=Counter(child) |
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new=[] |
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for c,ch in zip(cols,child): |
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if cnt[ch]==1: new.append(ch) |
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else: |
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p=c.split('.') |
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new.append(f"{p[-1]}_{p[-2]}" if len(p)>=2 else p[-1]) |
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return new |
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def df_from_data(data): |
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rows=[ flatten_nested(x) if isinstance(x,dict) else {"value":x} for x in data ] |
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df=pd.DataFrame(rows) |
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df.columns=rename_col(df.columns) |
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return df |
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def indices(): |
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p=nsefetch("https://www.nseindia.com/api/allIndices") |
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return {"data":pd.DataFrame(p.pop("data")), "dates":pd.DataFrame([p.pop("dates")]), "indices":pd.DataFrame([p])} |
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def eq(symbol): |
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symbol=nsesymbolpurify(symbol) |
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df=nsefetch(f'https://www.nseindia.com/api/quote-equity?symbol={symbol}') |
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pre=df.pop('preOpenMarket') |
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out={ |
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"securityInfo": pd.DataFrame([df["securityInfo"]]), |
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"priceInfo": pd.DataFrame([flatten_dict(df["priceInfo"])]), |
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"industryInfo": pd.DataFrame([df["industryInfo"]]), |
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"pdSectorIndAll": pd.DataFrame([df["metadata"].pop("pdSectorIndAll")]), |
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"metadata": pd.DataFrame([df["metadata"]]), |
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"info": pd.DataFrame([df["info"]]), |
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"preOpen": pd.DataFrame(pre.pop('preopen')), |
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"preOpenMarket": pd.DataFrame([pre]) |
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} |
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return out |
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def eq_fno(): return nsefetch('https://www.nseindia.com/api/equity-stockIndices?index=SECURITIES%20IN%20F%26O') |
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def eq_der(symbol): return nsefetch('https://www.nseindia.com/api/quote-derivative?symbol='+nsesymbolpurify(symbol)) |
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def index_chain(symbol): return nsefetch('https://www.nseindia.com/api/option-chain-indices?symbol='+nsesymbolpurify(symbol)) |
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def eq_chain(symbol): return nsefetch('https://www.nseindia.com/api/option-chain-equities?symbol='+nsesymbolpurify(symbol)) |
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def nse_holidays(t="trading"): return nsefetch('https://www.nseindia.com/api/holiday-master?type='+t) |
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def nse_results(index="equities",period="Quarterly"): |
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if index in ["equities","debt","sme"] and period in ["Quarterly","Annual","Half-Yearly","Others"]: |
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return pd.json_normalize(nsefetch(f'https://www.nseindia.com/api/corporates-financial-results?index={index}&period={period}')) |
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print("Invalid Input") |
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def nse_events(): return pd.json_normalize(nsefetch('https://www.nseindia.com/api/event-calendar')) |
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def nse_past_results(symbol): return nsefetch('https://www.nseindia.com/api/results-comparision?symbol='+nsesymbolpurify(symbol)) |
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def nse_blockdeal(): return nsefetch('https://nseindia.com/api/block-deal') |
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def nse_marketStatus(): return nsefetch('https://nseindia.com/api/marketStatus') |
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def nse_circular(mode="latest"): |
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return nsefetch('https://www.nseindia.com/api/latest-circular' if mode=="latest" else 'https://www.nseindia.com/api/circulars') |
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def nse_fiidii(mode="pandas"): |
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p=nsefetch('https://www.nseindia.com/api/fiidiiTradeReact') |
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return pd.DataFrame(p) |
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def nsetools_get_quote(symbol): |
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p=nsefetch('https://www.nseindia.com/api/equity-stockIndices?index=SECURITIES%20IN%20F%26O') |
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for x in p['data']: |
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if x['symbol']==symbol.upper(): return x |
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def nse_index(): |
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p=nsefetch('https://iislliveblob.niftyindices.com/jsonfiles/LiveIndicesWatch.json') |
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return pd.DataFrame(p['data']) |
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def index_history(sym,sd,ed): |
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d={'cinfo':f"{{'name':'{sym}','startDate':'{sd}','endDate':'{ed}','indexName':'{sym}'}}"} |
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p=json.loads(requests.post('https://niftyindices.com/Backpage.aspx/getHistoricaldatatabletoString', headers=niftyindices_headers, json=d).json()["d"]) |
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return pd.DataFrame.from_records(p) |
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def index_pe_pb_div(sym,sd,ed): |
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d={'cinfo':f"{{'name':'{sym}','startDate':'{sd}','endDate':'{ed}','indexName':'{sym}'}}"} |
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p=json.loads(requests.post('https://niftyindices.com/Backpage.aspx/getpepbHistoricaldataDBtoString', headers=niftyindices_headers, json=d).json()["d"]) |
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return pd.DataFrame.from_records(p) |
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def index_total_returns(sym,sd,ed): |
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d={'cinfo':f"{{'name':'{sym}','startDate':'{sd}','endDate':'{ed}','indexName':'{sym}'}}"} |
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p=json.loads(requests.post('https://niftyindices.com/Backpage.aspx/getTotalReturnIndexString', headers=niftyindices_headers, json=d).json()["d"]) |
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return pd.DataFrame.from_records(p) |
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def nse_bulkdeals(): return pd.read_csv("https://archives.nseindia.com/content/equities/bulk.csv") |
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def nse_blockdeals(): return pd.read_csv("https://archives.nseindia.com/content/equities/block.csv") |
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def nse_bhavcopy(d): return pd.read_csv("https://archives.nseindia.com/products/content/sec_bhavdata_full_"+d.replace("-","")+".csv") |
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def nse_highlow(d: str) -> pd.DataFrame: |
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""" |
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NSE 52-week High/Low CSV |
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Real header starts from row 3 |
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""" |
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date_str = d.replace("-", "") |
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url = f"https://archives.nseindia.com/content/CM_52_wk_High_low_{date_str}.csv" |
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df = pd.read_csv( |
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url, |
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skiprows=2, |
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engine="python" |
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) |
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df.columns = df.columns.str.strip() |
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return df |
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def nse_preopen(key="NIFTY"): |
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p=nsefetch("https://www.nseindia.com/api/market-data-pre-open?key="+key) |
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return {"data":df_from_data(p.pop("data")), "rem":df_from_data([p])} |
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def nse_most_active(t="securities",s="value"): |
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return pd.DataFrame(nsefetch(f"https://www.nseindia.com/api/live-analysis-most-active-{t}?index={s}")["data"]) |
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def nse_eq_symbols(): |
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return pd.read_csv('https://archives.nseindia.com/content/equities/EQUITY_L.csv')['SYMBOL'].tolist() |
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def nse_price_band_hitters(b="both",v="AllSec"): |
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p=nsefetch("https://www.nseindia.com/api/live-analysis-price-band-hitter") |
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return {"data":pd.DataFrame(p[b][v]["data"]), "count":pd.DataFrame([p['count']])} |
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def nse_largedeals(mode="bulk_deals"): |
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p=nsefetch('https://www.nseindia.com/api/snapshot-capital-market-largedeal') |
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return pd.DataFrame(p["BULK_DEALS_DATA" if mode=="bulk_deals" else "SHORT_DEALS_DATA" if mode=="short_deals" else "BLOCK_DEALS_DATA"]) |
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def nse_largedeals_historical(f,t,mode="bulk_deals"): |
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m = "bulk-deals" if mode=="bulk_deals" else "short-selling" if mode=="short_deals" else "block-deals" |
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p=nsefetch(f'https://www.nseindia.com/api/historical/{m}?from={f}&to={t}') |
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return pd.DataFrame(p["data"]) |
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def nse_stock_hist(f,t,symbol,series="ALL"): |
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url=f"https://www.nseindia.com/api/historical/securityArchives?from={f}&to={t}&symbol={symbol.upper()}&dataType=priceVolumeDeliverable&series={series}" |
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return pd.DataFrame(nsefetch(url)['data']) |
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def nse_index_live(name="NIFTY 50"): |
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p=nsefetch(f"https://www.nseindia.com/api/equity-stockIndices?index={name.replace(' ','%20')}") |
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return {"data":df_from_data(p.pop("data")) if "data" in p else pd.DataFrame(), "rem":df_from_data([p])} |
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