openbb-adanos 2.0.0

Market sentiment data from Reddit, News, X/Twitter, and Polymarket for OpenBB

openbb-adanos

Adanos market-sentiment integration for the OpenBB Platform.

The package now exposes two layers:

• Standard OpenBB provider commands for quick cross-platform sentiment lookups.
• A full obb.adanos.<platform>.* router surface for all Adanos stock endpoints.
• An OpenBB Workspace app backend in workspace_app/ for dashboards and widgets.

Links:

• Source: https://github.com/adanos-software/openbb-adanos
• API docs: https://api.adanos.org/docs
• Homepage: https://adanos.org

Installation

pip install openbb-adanos

Setup

Get an API key at api.adanos.org, then configure OpenBB:

from openbb import obb

obb.user.credentials.adanos_api_key = "sk_live_..."

You can also use OPENBB_ADANOS_API_KEY.

OpenBB Workspace App

The workspace_app/ directory contains a FastAPI backend for OpenBB Workspace Data Connectors. It exposes /widgets.json, /apps.json, and Adanos sentiment endpoints for a ready-made dashboard.

Run it locally from the repository root:

pip install -e .
pip install -r workspace_app/requirements.txt
uvicorn workspace_app.main:app --reload --host 0.0.0.0 --port 7779

Then add http://localhost:7779 in OpenBB Workspace Data Connectors. For live data, add the custom connector header X-API-Key: sk_live_... or set ADANOS_API_KEY on the backend.

Quick Start

Standard OpenBB provider flow

from openbb import obb

# Single symbol, detailed sentiment
obb.equity.sentiment(symbol="AAPL", provider="adanos")

# Cross-platform support
obb.equity.sentiment(symbol="TSLA", source="x", provider="adanos")
obb.equity.sentiment(symbol="NVDA", source="news", provider="adanos")
obb.equity.sentiment(symbol="SPY", source="polymarket", provider="adanos")

# Trending list
obb.equity.sentiment.trending(provider="adanos")
obb.equity.sentiment.trending(source="news", days=3, limit=50, provider="adanos")

# Compact comparison
obb.equity.sentiment.compare(symbols="AAPL,MSFT,NVDA", provider="adanos")

Full Adanos endpoint surface inside OpenBB

from openbb import obb

# Reddit
obb.adanos.reddit.trending(days=1, limit=25)
obb.adanos.reddit.stock(symbol="TSLA", days=7)
obb.adanos.reddit.market_sentiment(days=7)
obb.adanos.reddit.explain(symbol="TSLA")
obb.adanos.reddit.search(query="tesla")
obb.adanos.reddit.compare(symbols=["TSLA", "NVDA", "AMD"])
obb.adanos.reddit.stats()
obb.adanos.reddit.health()

# News
obb.adanos.news.trending(days=3, source="reuters")
obb.adanos.news.trending_sectors(days=7, source="bloomberg")
obb.adanos.news.trending_countries(days=7)
obb.adanos.news.stock(symbol="AAPL", days=14)
obb.adanos.news.market_sentiment(days=7)
obb.adanos.news.explain(symbol="AAPL")

# X / Twitter
obb.adanos.x.trending(days=1, asset_type="stock")
obb.adanos.x.stock(symbol="TSLA", days=7)
obb.adanos.x.market_sentiment(days=7)
obb.adanos.x.explain(symbol="TSLA")
obb.adanos.x.search(query="nvidia")

# Polymarket
obb.adanos.polymarket.trending(days=7)
obb.adanos.polymarket.stock(symbol="NVDA", days=14)
obb.adanos.polymarket.market_sentiment(days=7)
obb.adanos.polymarket.compare(symbols="NVDA,TSLA,AMD")

Supported Endpoints

Provider commands

• obb.equity.sentiment(..., provider="adanos")
• obb.equity.sentiment.trending(..., provider="adanos")
• obb.equity.sentiment.compare(..., provider="adanos")

Router commands

• obb.adanos.reddit.{trending,trending_sectors,trending_countries,stock,market_sentiment,explain,search,compare,stats,health}
• obb.adanos.news.{trending,trending_sectors,trending_countries,stock,market_sentiment,explain,search,compare,stats,health}
• obb.adanos.x.{trending,trending_sectors,trending_countries,stock,market_sentiment,explain,search,compare,stats,health}
• obb.adanos.polymarket.{trending,trending_sectors,trending_countries,stock,market_sentiment,search,compare,stats,health}

Notes

• Provider-level source supports reddit, news, x, and polymarket.
• Trending defaults to days=1, matching the API behavior.
• Full stock detail remains platform-specific through obb.adanos.*.stock(...), so users get fields like top_tweets, source_distribution, or top_mentions instead of a flattened lowest-common-denominator response.