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build/lib/mcxpy/__init__.py

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+from .mcx import mcx_bhavcopy, mcx_marketwatch, mcx_circulars, mcx_topgainers, mcx_toploosers, mcx_mostactiveoptions, mcx_mostactivecontracts, mcx_heatmap, mcx_optionchain, mcx_pcr, mcx_expiry
+
+__all__ = ['mcx_bhavcopy', 'mcx_marketwatch', 'mcx_circulars', 'mcx_topgainers', 'mcx_toploosers', 'mcx_mostactiveoptions', 'mcx_mostactivecontracts', 'mcx_heatmap', 'mcx_optionchain', 'mcx_pcr', 'mcx_expiry']

build/lib/mcxpy/__init__.pyi

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+from .mcx import mcx_bhavcopy as mcx_bhavcopy, mcx_circulars as mcx_circulars, mcx_expiry as mcx_expiry, mcx_heatmap as mcx_heatmap, mcx_marketwatch as mcx_marketwatch, mcx_mostactivecontracts as mcx_mostactivecontracts, mcx_mostactiveoptions as mcx_mostactiveoptions, mcx_optionchain as mcx_optionchain, mcx_pcr as mcx_pcr, mcx_topgainers as mcx_topgainers, mcx_toploosers as mcx_toploosers

build/lib/mcxpy/mcx.py

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+import requests
+import pandas as pd
+from datetime import datetime, date, timedelta
+import re
+from typing import Literal, Union, NewType, List, Tuple
+
+DateFormat = NewType(name="%d-%m-%Y", tp=str)
+DateFormat_2 = NewType(name="%Y%m%d", tp=str)
+DateFormat_3 = NewType(name="%d%b%Y", tp=str)
+
+urls = {
+    "base_url" : "https://www.mcxindia.com",
+    "routes" : {
+        "bhavcopy" : "/backpage.aspx/GetDateWiseBhavCopy",
+        "marketwatch" : "/backpage.aspx/GetMarketWatch",
+        "circulars" : "/backpage.aspx/GetCircularAdvanceSearch",
+        "gainers" : "/backpage.aspx/GetGainer",
+        "losers" : "/backpage.aspx/GetLosers",
+        "activeoptions" : "/backpage.aspx/GetMostActiveOptionsContractsByValue",
+        "activecontracts" : "/backpage.aspx/GetMostActiveContractByValueFilter",
+        "heatmap" : "/backpage.aspx/GetHeatMap",
+        "optionchain" : "/backpage.aspx/GetOptionChain",
+        "pcr" : "/backpage.aspx/GetCommoditywisePutCallRatio",
+        "pcr_expirywise" : "/backpage.aspx/GetExpirywisePutCallRatio"
+    },
+}
+
+
+headers = {
+    "Accept": "application/json, text/javascript, */*; q=0.01",
+    "Accept-Language": "en-GB,en-US;q=0.9,en;q=0.8",
+    "Cache-Control": "no-cache",
+    "Connection": "keep-alive",
+    "Content-Type": "application/json",
+    "Origin": "https://www.mcxindia.com",
+    "Referer": "https://www.mcxindia.com",
+    "Pragma": "no-cache",
+    "Sec-Fetch-Dest": "empty",
+    "Sec-Fetch-Mode": "cors",
+    "Sec-Fetch-Site": "same-origin",
+    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36",
+    "X-Requested-With": "XMLHttpRequest",
+    "sec-ch-ua": "^\"Not.A/Brand^\";v=^\"8^\", ^\"Chromium^\";v=^\"114^\", ^\"Google Chrome^\";v=^\"114^\"",
+    "sec-ch-ua-mobile": "?0",
+    "sec-ch-ua-platform": "^\"Windows^\"",
+}
+
+
+
+def format_date(dateobj: Union[DateFormat, datetime, date], 
+                isExpiry=False
+                ) -> Union[DateFormat_2, DateFormat_3]:
+
+    if isinstance(dateobj, str):
+        try:
+            if isExpiry:
+                dt = datetime.strptime(dateobj, "%d-%m-%Y")
+                return dt.strftime("%d%b%Y").upper()
+            dt = datetime.strptime(dateobj, "%d-%m-%Y")
+            return dt.strftime("%Y%m%d")
+        except ValueError as e:
+            print(f"Format Date String Error :: {e}")
+            return
+    elif isinstance(dateobj, datetime) or isinstance(dateobj, date):
+        if isExpiry:
+            return dateobj.strftime("%d%b%Y").upper()
+        return dateobj.strftime("%Y%m%d")
+    else:
+        print("Invalid input type. Expected str(dd-mm-yyyy), date or datetime.")
+
+def convert_to_ist(timestamp_str: str) -> datetime:
+    try:
+        match_str = re.search(r'\((-?\d+)\)', timestamp_str)
+        if match_str:
+            timestamp_ms = int(match_str.group(1))
+
+            if timestamp_ms <= 0:
+                return None
+
+            ist_datetime = datetime.utcfromtimestamp(timestamp_ms / 1000) + timedelta(hours=5, minutes=30)
+            return ist_datetime
+        return None
+    except Exception as e:
+        print(f"Error :: {e}")
+
+def mcxfetch(config_key: Literal["bhavcopy","marketwatch","circulars","gainers","losers","activeoptions",
+                                 "activecontracts","heatmap","optionchain","pcr", "pcr_expirywise"],
+            data: dict=None) -> dict:
+    try:
+        base_url = urls['base_url']
+        url = base_url + urls['routes'][config_key]
+        response = requests.post(url, headers=headers, json=data)
+        response.raise_for_status()
+        if response.status_code == 200:
+            res_data = response.json()
+            return res_data
+    except (requests.HTTPError,Exception) as e:
+        print(f"Error :: {e}")
+
+def mcx_bhavcopy(bhavdate: Union[DateFormat, datetime, date]) -> pd.DataFrame:    
+    try:
+        fdate = format_date(bhavdate)
+
+        data = {
+            "Date": fdate,
+            "InstrumentName": "ALL"
+        }
+
+        res = mcxfetch(config_key='bhavcopy',data=data)
+        df = pd.DataFrame(res["d"]["Data"])
+        selected_columns = [
+                    'DateDisplay', 'InstrumentName', 'Symbol', 'ExpiryDate', 'OptionType', 'StrikePrice',
+                    'Open', 'High', 'Low', 'Close', 'PreviousClose', 'Volume', 'VolumeInThousands',
+                    'Value', 'OpenInterest'
+                ]
+        df = df[selected_columns]
+        df = df.rename(columns={
+            'DateDisplay' : 'Date', 
+            'InstrumentName' : 'Instrument Name', 
+            'ExpiryDate' : 'Expiry Date', 
+            'OptionType' : 'Option Type', 
+            'StrikePrice' : 'Strike Price',
+            'PreviousClose' : 'Previous Close', 
+            'Volume' : 'Volume(Lots)', 
+            'Value' : 'Value(Lacs)', 
+            'OpenInterest' : 'Open Interest(Lots)'
+        })
+        df['Date'] = pd.to_datetime(df['Date'], format='mixed',dayfirst=True)
+        df['Expiry Date'] = pd.to_datetime(df['Expiry Date'], format='mixed',dayfirst=True)
+        return df
+    except Exception as e:
+        print(f"Error :: {e}")
+
+def mcx_marketwatch() -> pd.DataFrame:
+    try:
+        res = mcxfetch(config_key='marketwatch')
+        df = pd.DataFrame(res["d"]["Data"])
+        df = df.drop(columns=['__type'])
+        df = df.replace('-', '')
+        df = df.rename(columns={
+        'ProductCode': 'Product',
+        'ExpiryDate': 'Expiry',
+        'BuyQuantity': 'BuyQty',
+        'SellQuantity': 'SellQty'
+        })
+        df['Expiry'] = pd.to_datetime(df['Expiry'], format='mixed',dayfirst=True)
+        df['UnderlineContract'] = pd.to_datetime(df['UnderlineContract'], format='mixed', dayfirst=True)
+        df['LTT'] = df['LTT'].apply(convert_to_ist)
+        return df
+    except Exception as e:
+        print(f"Error :: {e}")
+
+def mcx_circulars(from_date: Union[DateFormat, datetime, date] =(datetime.now()-timedelta(days=4)),
+                  to_date: Union[DateFormat, datetime, date]=datetime.now()
+                  ) -> pd.DataFrame:    
+    try:
+        date1 = format_date(from_date)
+        date2 = format_date(to_date) 
+
+        data = {
+            'CircularType':'ALL',
+            'CircularNo':'',
+            'Title':'',
+            'FromDate': date1,
+            'ToDate': date2
+            }
+
+        res = mcxfetch(config_key='circulars', data=data)
+        df= pd.DataFrame(res['d'])
+        df = df.drop(columns=['__type', 'CircularDate','CircularMonth','CircularYear','CircularTypes', 'CircularNumber'])
+        df['DisplayCircularDate'] = pd.to_datetime(df['DisplayCircularDate'], format='mixed', dayfirst=True)
+        df['CompareDate'] = pd.to_datetime(df['CompareDate'], format="%Y%m%d", yearfirst=True)
+        df = df.rename(columns={
+            'DisplayCircularDate': 'Date'
+            })
+        return df
+    except Exception as e:
+        print(f"Error :: {e}")
+
+def mcx_topgainers() -> pd.DataFrame:    
+    try:
+        res = mcxfetch(config_key='gainers')
+        df = pd.DataFrame(res["d"]["Data"])
+        df = df.drop(columns=['ExtensionData', 'EngSymbol'])  
+        df['LTT'] = df['LTT'].apply(convert_to_ist)
+        df['ExpiryDate'] = pd.to_datetime(df['ExpiryDate'], format='%d%b%Y', dayfirst=True)
+        reorderd_columns = ['Symbol', 'LTT', 'ExpiryDate','PreviousClosed', 'LTP', 
+                      'AbsoluteChange', 'PercentChange']
+        df = df[reorderd_columns]
+        return df
+    except Exception as e:
+        print(f"Error :: {e}")
+
+def mcx_toploosers() -> pd.DataFrame:    
+    try:
+        res = mcxfetch(config_key='losers')
+        df = pd.DataFrame(res["d"]["Data"])
+        df = df.drop(columns=['ExtensionData', 'EngSymbol'])  
+        df['LTT'] = df['LTT'].apply(convert_to_ist)
+        df['ExpiryDate'] = pd.to_datetime(df['ExpiryDate'], format='%d%b%Y', dayfirst=True)
+        reorderd_columns = ['Symbol', 'LTT', 'ExpiryDate','PreviousClosed', 'LTP', 
+                      'AbsoluteChange', 'PercentChange']
+        df = df[reorderd_columns]
+        return df
+    except Exception as e:
+        print(f"Error :: {e}")
+
+def mcx_mostactiveoptions() -> pd.DataFrame:    
+    try:
+        option_list = ['CE', 'PE']
+        inst_list = ['OPTFUT', 'OPTCOM']
+
+        res_list = []
+        for opt in option_list:
+            for inst in inst_list:
+                data = {
+                    'OptionType':opt,
+                    'Product':'ALL',
+                    'InstrumentType':inst
+                    }
+                res = mcxfetch(config_key="activeoptions", data=data)
+                res_data = res["d"]["Data"]
+                res_list.append(res_data)
+        dfs = [pd.DataFrame(sublist) for sublist in res_list]
+        df = pd.concat(dfs)
+        df = df.drop(columns=['ExtensionData', 'EngSymbol'])
+        df['LTT'] = df['LTT'].apply(convert_to_ist)  
+        df['ExpiryDate'] = pd.to_datetime(df['ExpiryDate'], format='mixed', dayfirst=True)
+        reorderd_columns = ['Symbol', 'LTT', 'ExpiryDate', 'InstrumentType', 'OptionType', 'StrikePrice', 'LTP','OpenInterest', 
+                      'Volume', 'PremiumValueInLacs','NotionalValueInLacs', 'ValueOfUnderlying']
+        df = df[reorderd_columns]
+        return df
+    except Exception as e:
+        print(f"Error :: {e}")
+
+def mcx_mostactivecontracts() -> pd.DataFrame:
+    try:
+        data = {
+            "InstrumentType": "ALL"
+            }
+        res = mcxfetch(config_key='activecontracts', data=data)
+        df = pd.DataFrame(res["d"]["Data"])
+        df = df.drop(columns=['ExtensionData', 'EngSymbol'])
+        df['Date'] = df['Date'].apply(convert_to_ist)
+        df['ExpiryDate'] = pd.to_datetime(df['ExpiryDate'], format='mixed', dayfirst=True)
+        reorderd_columns = ['Symbol', 'Date', 'ExpiryDate', 'InstrumentName', 'OptionType', 'StrikePrice', 'LTP',
+                            'PercentageChange','OpenInterest', 'Volume', 'Value','NotionalValue', 'PremiumValue',
+                            'UnderlineValue', 'Unit']
+        df = df[reorderd_columns]
+        return df
+    except Exception as e:
+        print(f"Error :: {e}")
+
+def mcx_heatmap() -> pd.DataFrame:    
+    try:
+        res = mcxfetch(config_key='heatmap')
+        df = pd.DataFrame(res["d"]["Data"])
+        df = df.drop(columns=['__type'])
+        df['Dttm'] = df['Dttm'].apply(convert_to_ist)
+        df['ExpiryDate'] = pd.to_datetime(df['ExpiryDate'], format='mixed', dayfirst=True)
+        return df
+    except Exception as e:
+        print(f"Error :: {e}")
+
+def mcx_optionchain(commodity: Literal['COPPER', 'CRUDEOIL', 'GOLD', 'GOLDM', 'NATURALGAS', 
+                                       'NICKEL', 'SILVER', 'SILVERM','ZINC'],
+                    expiry: Union[DateFormat, datetime, date]
+                    ) -> pd.DataFrame:
+    try:
+        exp_date = format_date(dateobj=expiry, isExpiry=True)
+        data = {
+            'Commodity': commodity,
+            'Expiry': exp_date
+            }
+        res = mcxfetch(config_key='optionchain', data=data) 
+        df = pd.DataFrame(res["d"]["Data"])
+        df = df.drop(columns=['ExtensionData'])
+        df['LTT'] = df['LTT'].apply(convert_to_ist)
+        df['CE_LTT'] = df['CE_LTT'].apply(convert_to_ist)
+        df['PE_LTT'] = df['PE_LTT'].apply(convert_to_ist)
+        df['Symbol'] = commodity
+        df['Expiry'] = datetime.strptime(exp_date, "%d%b%Y")
+        return df
+    except Exception as e:
+        print(f"Error :: {e}")
+
+def mcx_pcr(expirywise: bool=False) -> pd.DataFrame:    
+    try:
+        if expirywise:
+            res = mcxfetch(config_key='pcr_expirywise')
+        else:
+            res = mcxfetch(config_key='pcr')        
+
+        df = pd.DataFrame(res["d"]["Data"])
+        df = df.drop(columns=['ExtensionData'])
+        df['Date'] = df['Date'].apply(convert_to_ist)
+        if expirywise:
+            df['Expiry'] = pd.to_datetime(df['Expiry'], format="%d%b%Y", dayfirst=True, errors="coerce")
+        reorderd_columns = ['Symbol', 'Date', 'Expiry', 'Ratio']
+        df = df[reorderd_columns]
+        return df
+    except Exception as e:
+        print(f"Error :: {e}")
+
+def mcx_expiry(commodity: Literal['COPPER', 'CRUDEOIL', 'GOLD', 'GOLDM', 'NATURALGAS', 
+                                  'NICKEL', 'SILVER', 'SILVERM','ZINC']='CRUDEOIL',
+                expirytype : Literal['current', 'next', 'far', 'all']='current'
+                ) -> Union[datetime,List[datetime]]:
+    try:
+        exp_df = mcx_pcr(expirywise=True)
+        com_df = exp_df[exp_df['Symbol'] == commodity]
+        exp_list = sorted(com_df['Expiry'].unique().tolist())
+        exp_list = [item.to_pydatetime() for item in exp_list]
+        if expirytype == "current":
+            return exp_list[0]
+        elif expirytype == "next":
+            return exp_list[1]
+        elif expirytype == "far":
+            return exp_list[2]
+        elif expirytype == "all":
+            return exp_list
+        else:
+            print("Please input correct parameters.")
+    except Exception as e:
+        print(f"Error :: {e}")
+

mcxpy.egg-info/PKG-INFO

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+Metadata-Version: 2.1
+Name: mcxpy
+Version: 0.0.1
+Summary: For fetching mcx data
+Author: Tapan Hazarika

mcxpy.egg-info/SOURCES.txt

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+setup.py
+mcxpy/__init__.py
+mcxpy/__init__.pyi
+mcxpy/mcx.py
+mcxpy/py.typed
+mcxpy.egg-info/PKG-INFO
+mcxpy.egg-info/SOURCES.txt
+mcxpy.egg-info/dependency_links.txt
+mcxpy.egg-info/top_level.txt

mcxpy.egg-info/dependency_links.txt

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+

mcxpy.egg-info/top_level.txt

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+mcxpy

setup.py

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+from setuptools import setup
+
+setup(
+   name='mcxpy',
+   version='0.0.1',
+   description='For fetching mcx data',
+   author='Tapan Hazarika',
+   packages=['mcxpy'],
+   package_data={'mcxpy': ['py.typed', '__init__.pyi', 'mcxpy.pyi']}
+)
+