metapyle 0.1.1

Unified interface for querying financial time-series data

Metapyle

Early-stage research framework — Not for production use.

A unified interface for querying financial time-series data from multiple sources.

Requires Python 3.12+

Overview

Financial data lives in many places—Bloomberg terminals, internal APIs, CSV exports—each with its own ticker syntax, authentication, and quirks. Metapyle provides a YAML-based catalog that maps human-readable names to source-specific details, giving you a single client.get() interface regardless of where the data comes from.

Currently supports Bloomberg (via xbbg), Macrobond (via macrobond-data-api), and local files (CSV/Parquet).

Installation

uv add metapyle[bloomberg]

Or with pip:

pip install metapyle[bloomberg]

For Macrobond support:

pip install metapyle[macrobond]

Note: Bloomberg requires a Bloomberg Terminal. Macrobond requires desktop app or API credentials.

Quick Start

1. Create a catalog file (catalog.yaml):

- my_name: sp500_close
  source: bloomberg
  symbol: SPX Index
  field: PX_LAST

- my_name: gdp_us
  source: localfile
  symbol: GDP_US          # column name in the file
  path: /data/macro.csv   # file path

2. Query data:

from metapyle import Client

with Client(catalog="catalog.yaml") as client:
    # end defaults to today
    df = client.get(["sp500_close"], start="2024-01-01")

Documentation

See the User Guide for complete documentation, including:

• Catalog configuration
• Frequency alignment
• Caching
• Available data sources
• Error handling

License

MIT License - see LICENSE for details.