nubra_oi_walls

nubra_oi_walls packages the options wall proximity scanner as a reusable Python library on top of the official Nubra Python SDK.

Install

pip install nubra_oi_walls

Usage

from nubra_python_sdk.marketdata.market_data import MarketData
from nubra_python_sdk.start_sdk import InitNubraSdk, NubraEnv
from nubra_oi_walls import run_multi_wall_proximity_scan, run_wall_proximity_scan

nubra = InitNubraSdk(NubraEnv.UAT)
market_data = MarketData(nubra)

summary_df = run_wall_proximity_scan(
    market_data=market_data,
    stocks=["NIFTY", "BANKNIFTY", "RELIANCE", "HDFCBANK"],
    normalize=False,
    exchange="NSE",
)

print(summary_df)

For multi-wall output when top_n > 1:

multi_df = run_multi_wall_proximity_scan(
    market_data=market_data,
    stocks=["NIFTY", "BANKNIFTY", "RELIANCE", "HDFCBANK"],
    normalize=False,
    top_n=3,
    exchange="NSE",
)

print(multi_df)

There is also a ready-to-run example in quickstart.py. That quickstart runs both DataFrame-returning functions.

Authentication and environment

The preferred integration is to pass your existing MarketData object from your main Nubra session into the scan functions.

The scanner defaults to the Nubra UAT environment only when it has to create its own internal client. To switch that fallback behavior to live usage, set:

$env:NUBRA_OI_WALLS_ENV = "PROD"

If you pass market_data, the package will reuse your existing Nubra session instead of creating a new one.

Import shape

from nubra_oi_walls import run_wall_proximity_scan, run_multi_wall_proximity_scan

Returned data

run_wall_proximity_scan(...) returns the classic single-wall summary as a pandas DataFrame.

run_multi_wall_proximity_scan(...) returns the expanded wall candidates as a pandas DataFrame.