Bloomberg Data License Client (BDLC)

This project provides a scalable and automated client to request, retrieve, and store financial data from the Bloomberg Data License (DL) REST API. It is engineered to integrate with enterprise data workflows, fetching instrument data, applying transformation logic, and persisting results into a Microsoft SQL Server database.

Overview

Purpose

This project automates the end-to-end process of:

• Authenticating with Bloomberg’s OAuth2-secured DL API.
• Building and submitting data requests for a universe of financial instruments.
• Listening for Bloomberg’s asynchronous delivery and downloading structured datasets.
• Transforming the data into a usable tabular format.
• Persisting it into a designated SQL Server table.

This client enables quantitative analysts, portfolio managers, and data engineers to automate ingestion of Bloomberg-licensed content into their internal databases.

Source of Data

This project uses the Bloomberg Data License REST API which provides access to high-quality financial data including:

• Historical and current pricing
• Fundamental fields
• Descriptive security information
• Bloomberg-specific identifiers

Bloomberg credentials and terminal identity parameters are required for authentication and data entitlement.

Application Flow

The main orchestration logic is encapsulated in main.py and includes:

1. Initialize Client:

   • Queries Bloomberg-entitled tickers via a SQL query using TickerLoader.
   • Establishes a secure OAuth2 session via Session.

2. Data Request Lifecycle:

   • A Client object composes and sends a data request payload.
   • The request is submitted to the Bloomberg catalog (configured as “scheduled”).
   • A listener polls for asynchronous results and downloads them once ready.

3. Data Transformation:

   • The Agent class applies transformations to the downloaded data.
   • Unwanted or redundant fields are dropped based on the configured ignore list.

4. Database Insertion:

   • Transformed data is inserted into the specified SQL Server table.
   • Options allow for overwriting or appending data with de-duplication logic.

Project Structure

bdlc-main/
├── app/                   # Core Bloomberg DL interaction logic
│   ├── client.py          # Data request and download handling
│   ├── loader.py          # SQL ticker loader
│   └── session.py         # OAuth2 session manager
├── config/                # Logger and environment settings
├── database/              # MSSQL interface
├── transformer/           # Data transformation logic
├── main.py                # Entry point and process orchestrator
├── .env.sample            # Example environment variable template
├── Dockerfile             # Docker setup for containerized execution

Environment Variables

You must provide a .env file based on .env.sample. The following environment variables are required:

Variable	Description
LOG_LEVEL	Logging verbosity level (INFO, DEBUG, etc.)
CREDENTIALS	Path or JSON string with Bloomberg OAuth credentials
TI_USERNUMBER, TI_SERIALNUMBER, TI_WORKSTATION	Bloomberg terminal identity values
IDENTIFIER_TYPE	Type of identifier (e.g., ISIN, BBGID, CUSIP)
DB_IDS_QUERY	SQL query to retrieve instrument identifiers
FIELDS	Comma-separated list of Bloomberg field mnemonics
BBG_REPLY_TIMEOUT_MIN	Timeout (in minutes) to wait for a data response
IGNORE_COLUMNS	Fields to drop during data transformation
OUTPUT_TABLE	Destination MSSQL table
MSSQL_*	SQL Server connection credentials and parameters
INSERTER_MAX_RETRIES, REQUEST_MAX_RETRIES, REQUEST_BACKOFF_FACTOR	Retry behavior settings for resiliency

These values are consumed by the client and injected into the API request payloads and SQL connection logic.

Docker Support

The project is fully containerized for portability.

Build the Image

docker build -t bdlc-client .

Run the Client

docker run --env-file .env bdlc-client

Requirements

Install the required Python dependencies using pip:

pip install -r requirements.txt

The project uses requests-oauthlib, SQLAlchemy, and pandas for API access, SQL integration, and data manipulation.

Running the App

Ensure that your .env is configured correctly and contains valid Bloomberg API credentials.

python main.py

Progress will be logged to the console, including request IDs, catalog lookups, and download status.

License

This project is MIT licensed. Bloomberg API usage is subject to their licensing and compliance requirements. Ensure that your credentials and entitlement allow for the requested data.