OpenBB: The Open-Source Financial Platform Revolutionizing Investment Research

When conducting quantitative analysis or investment research, the most frustrating part is often not strategy development, but data acquisition and processing.

High-quality data comes with an annual subscription fee of tens of thousands of US dollars, which directly discourages most of us.

As a compromise, we turn to data scraping or various free APIs. However, each interface has a different format, and the returned fields are even more disorganized.

Data cleaning alone takes up more than 80% of our time, leaving only 20% of our energy for the actual data analysis.

Until recently, I discovered an open-source financial platform on GitHub called OpenBB, which is attempting to end this chaos.

It is not just a simple web scraping tool, but more like a “unified interface layer” for financial data, and also the first AI financial workstation that combines data with AI.

Its goal is clear: to enable everyone to easily conduct professional-level investment research anywhere.

Currently, the project has gained over 54,000 stars on GitHub, with a very active community.

The predecessor of the project is quite robust. Initially named Gamestonk Terminal, it was a product of the period when Reddit retail investors fought against Wall Street.

After years of continuous iteration, it has now evolved into an Open Data Platform (ODP).

Simply put, it helps us connect all various financial data sources.

It supports the integration of proprietary data, authorized data, and public data sources, encapsulating them into a set of standardized interfaces.

This means we no longer need to manually scrape data from dozens of different API documents as mentioned earlier.

For example, if we want to get Apple’s historical stock prices, we can now do it with just one line of code:

from openbb import obb # Get Apple's historical stock prices with one line of code output = obb.equity.price.historical("AAPL") # Directly convert to Pandas DataFrame for subsequent analysis df = output.to_dataframe()

Moreover, the data obtained is in a standardized format.

We can directly feed it into large models for backtesting, saving a great deal—even most—of the data cleaning work.

Additionally, a major recent move by OpenBB is its full embrace of AI Agents.

We also discussed MCP (Model Context Protocol) in previous articles, and OpenBB’s current positioning is the “financial data arsenal” for AI.

Its architectural design philosophy is “connect once, use everywhere.”

Through its interfaces, we can enable Claude or ChatGPT to have the ability to obtain real-time financial data.

Previously, when asking AI “What’s Apple’s stock price today?”, it might give nonsense or say it doesn’t know.

Now, with OpenBB, AI can directly call the underlying data. It can even help us generate a simple research report with charts.

For those who want to develop AI financial assistants, this is definitely an indispensable infrastructure.

In addition to being used as a Python library, it also provides a very professional web workspace—OpenBB Workspace.

This makes it highly flexible. If we are geeks who like coding, we can use CLI or even Vim-style operations for market monitoring.

If we are analysts, we can also use the web interface to drag and drop charts.

Installation is also very hassle-free.

As long as our environment is between Python 3.9 and 3.12, we can install it directly with pip:

pip install openbb

If we want to experience its command-line interactive mode, we can also install the dedicated CLI package:

pip install openbb-cli

In summary, OpenBB is like a “Swiss Army knife” in the field of financial data.

Through open-source, it has significantly lowered the originally high and closed threshold for financial data.

This allows ordinary developers to have access to institutional-level analysis tools.