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FinBrain Python SDK 

PyPI version CI License

Official Python client for the FinBrain API.
Fetch deep-learning price predictions, sentiment scores, insider trades, LinkedIn metrics, options data and more — with a single import.

Python ≥ 3.9 • requests & pandas • asyncio optional.


✨ Features

  • One-line auth (FinBrainClient(api_key="…"))
  • Complete endpoint coverage (predictions, sentiments, options, insider, etc.)
  • Transparent retries & custom error hierarchy (FinBrainError)
  • Async parity with finbrain.aio (httpx)
  • CLI (finbrain markets, finbrain predict AAPL)
  • Auto-version from Git tags (setuptools-scm)
  • MIT-licensed, fully unit-tested

🚀 Quick start

Install the SDK:

pip install finbrain-python

Create a client and fetch data:

from finbrain import FinBrainClient

fb = FinBrainClient(api_key="YOUR_KEY")        # create once, reuse below

# ---------- availability ----------
fb.available.markets()                         # list markets
fb.available.tickers("daily", as_dataframe=True)

# ---------- app ratings ----------
fb.app_ratings.ticker("S&P 500", "AMZN",
                      date_from="2025-01-01",
                      date_to="2025-05-31",
                      as_dataframe=True)

# ---------- analyst ratings ----------
fb.analyst_ratings.ticker("S&P 500", "AMZN",
                          date_from="2025-01-01",
                          date_to="2025-05-31",
                          as_dataframe=True)

# ---------- house trades ----------
fb.house_trades.ticker("S&P 500", "AMZN",
                       date_from="2025-01-01",
                       date_to="2025-05-31",
                       as_dataframe=True)

# ---------- insider transactions ----------
fb.insider_transactions.ticker("S&P 500", "AMZN", as_dataframe=True)

# ---------- LinkedIn metrics ----------
fb.linkedin_data.ticker("S&P 500", "AMZN",
                        date_from="2025-01-01",
                        date_to="2025-05-31",
                        as_dataframe=True)

# ---------- options put/call ----------
fb.options.put_call("S&P 500", "AMZN",
                    date_from="2025-01-01",
                    date_to="2025-05-31",
                    as_dataframe=True)

# ---------- price predictions ----------
fb.predictions.market("S&P 500", as_dataframe=True)   # all tickers in market
fb.predictions.ticker("AMZN", as_dataframe=True)      # single ticker

# ---------- news sentiment ----------
fb.sentiments.ticker("S&P 500", "AMZN",
                     date_from="2025-01-01",
                     date_to="2025-05-31",
                     as_dataframe=True)

🔑 Authentication

To call the API you need an API key, obtained by purchasing a FinBrain API subscription.
(The Terminal-only subscription does not include an API key.)

  1. Subscribe at https://www.finbrain.tech → FinBrain API.
  2. Copy the key from your dashboard.
  3. Pass it once when you create the client:
from finbrain import FinBrainClient
fb = FinBrainClient(api_key="YOUR_KEY")

Async(currently under development)

import asyncio, os
from finbrain.aio import FinBrainAsyncClient async
def  main():
	async  with FinBrainAsyncClient(api_key=os.getenv("FINBRAIN_API_KEY")) as fb:
        data = await fb.sentiments.ticker("sp500", "AMZN")
        print(list(data["sentimentAnalysis"].items())[:3])

asyncio.run(main())` 

CLI(currently under development)

export FINBRAIN_API_KEY=your_key
finbrain markets
finbrain predict AAPL --type daily

📚 Supported endpoints

Category Method Path
Availability client.available.markets() /available/markets
client.available.tickers() /available/tickers/{TYPE}
Predictions client.predictions.ticker() /ticker/{TICKER}/predictions/{daily|monthly}
client.predictions.market() /market/{MARKET}/predictions/{daily|monthly}
Sentiments client.sentiments.ticker() /sentiments/{MARKET}/{TICKER}
App ratings client.app_ratings.ticker() /appratings/{MARKET}/{TICKER}
Analyst ratings client.analyst_ratings.ticker() /analystratings/{MARKET}/{TICKER}
House trades client.house_trades.ticker() /housetrades/{MARKET}/{TICKER}
Insider transactions client.insider_transactions.ticker() /insidertransactions/{MARKET}/{TICKER}
LinkedIn client.linkedin_data.ticker() /linkedindata/{MARKET}/{TICKER}
Options – Put/Call client.options.put_call() /putcalldata/{MARKET}/{TICKER}

🛠️ Error-handling

from finbrain.exceptions import BadRequest
try:
    fb.predictions.ticker("MSFT", prediction_type="weekly")
except BadRequest as exc:
	print("Invalid parameters:", exc)` 
HTTP status Exception class Meaning
400 BadRequest The request is invalid or malformed
401 AuthenticationError API key missing or incorrect
403 PermissionDenied Authenticated, but not authorised
404 NotFound Resource or endpoint not found
405 MethodNotAllowed HTTP method not supported on endpoint
500 ServerError FinBrain internal error

🔄 Versioning & release

  • Semantic Versioning (MAJOR.MINOR.PATCH)

  • Version auto-generated from Git tags (setuptools-scm)

git tag -a v0.2.0 -m "Add options.chain endpoint"
git push --tags # GitHub Actions builds & uploads to PyPI

🧑‍💻 Development

git clone https://github.com/finbrain-tech/finbrain-python cd finbrain-python
python -m venv .venv && source .venv/bin/activate
pip install -e .[dev]

ruff check . # lint / format pytest -q # unit tests (mocked) 

Live integration test(currently under development)

Set FINBRAIN_LIVE_KEY, then run:

pytest -m integration

🤝 Contributing

  1. Fork → create a feature branch

  2. Add tests & run ruff --fix

  3. Ensure pytest & CI pass

  4. Open a PR — thanks!


🔒 Security

Please report vulnerabilities to info@finbrain.tech.
We respond within 48 hours.


📜 License

MIT — see LICENSE.


© 2025 FinBrain Technologies — Built with ❤️ for the quant community.

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