API Data pull from Global Data Feeds for Nifty -Option Chain & Future data, and Nifty 50 Stocks Cash data

Important Note:

Experienced in Phthon Programming & API building & Data Call.

Detail Requirement:

Nifty Future & Options data AND Nifty 50 Stock Data pull from Global Data Feeds


 End to end programming (Each and every point/ requirement of this document to be captured)

 Software, Program installation

 Testing & Bug Fixing. Till Successful Test completion

 Program Documentation


1.1 Option Chain data Pull for the NIFTY Index

 Option Chain data for the next 3 expiries (current Expiry, Current +1, Current +2)

 Data for the ATM +/- 16 Strike Prices (if ATM is 17600, then data required for strike prices; starting from 16800 to 18400).

 For each Strike prices data required for both the CE & PE sides.

 Data required are:

• OI


• Traded Volume (cumulative)

• Number of Trades executed (cumulative)

• Avg Traded Price (Last Candle)

• Low Price (Last Candle)

• High Price (Last Candle)

• Last Traded Price (Last Candle)

• Total Turnover

• IV (implied Volatility)

1.2. Future Data for the NIFTY Index

 Index Future data for 3 expiries

 Last Traded Prices (Last Candle)

 Open Interests (Last Candle)

 Underlying Value

 Total Buy Qty

 Total Sell Qty

 Time Stamp

1.3. Cash data Requirement for Nifty 50 Stocks

Cash Data for Nifty Top 25 Stocks (from List)

Cash data required for every completed Candle

 Stock wise Data Points required are,

• Symbol

• Open Price

• High Price

• Low Price

• Close price


• Total Traded Quantity

• Deliverable Qty

2. Technical Requirements

A. Programming in Python

B. Program shall be scheduled through Task Scheduler, for ensuring data pull with a specified frequency

C. After the data file preparations, it will call an excel macro for further calculations. So Program should have Provision for calling the Excel Macro.

D. After successful completion of Program execution, it will issue a message, which will be a written as well as a voice message.

E. Each and every exceptional/ error messages (API returns) are to be voice message

F. After completion of all activities, Downloaded file is to be saved in an archive folder. File name with extension of DATE & TIME

G. In the Program Proper comments for the Steps, sub-steps, Activity, File reference, Excel file cell reference etc. as applicable to be provided. Which would be useful for debug OR futuristic change.

H. A programming doc/ user guide.

3. Reference data Points/ Excel inputs:

 Required data to be saved in a Macro enabled Excel file (in specified format).

 Name of the Excel file to be taken from input file (Input File Name: IntraDayDataPoints). In this single file all the data (Option, Future & Cash) to be saved in separate sheets (details given below)

 For the Option Chain:

Reference Price Point’ shall be taken from an Excel file. API should bring data from this price point to next 33 Price Points

Data to be taken for 3 Expiries; (current Expiry, Current +1, Current +2).

Data of 3 expiries to be saved in 3 sheets. Sheet names to be taken from the Excel. In the sheet names last 9 char, represents the Expiry dates.

 For the Future data, sheet name to be taken from Reference Excel

 For the Nifty 50 Stocks, asymbols to be taken from excel

 Login Credentials and the Access Keys etc. are to be taken from this Input File

4. Program Installation & Testing Requirements

A. Support for Program, software (Python, Compiler/ editor) installation

B. Basic testing you can do before release

C. Final testing to be done; where data correctness shall be compared with the NSE data (Option & Future Data) and Cash data with Charts (from ZERODHA, Investing)

D. If any bug comes during the Testing, to be corrected.

After successful testing completion & Product delivery, payment shall be released.

Available over Google Meet for testing & bug fixing during market hout (IST)

Refer enclosed Doc for details, formats etc. For API details refer: //[login to view URL]

Habilidades: Autotask, Excel Macros, Python, RESTful API

Sobre o Cliente:
( 0 comentários ) Kolkata, India

ID do Projeto: #34376864

6 freelancers estão ofertando em média ₹19750 nesse trabalho


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