Introduction to pysdmx, key use cases and hands-on demo"

Overview

pysdmx is a pragmatic and opinionated SDMX library written in Python. It focuses on simplicity, providing a subset of SDMX functionalities without requiring advanced knowledge of SDMX. pysdmx is developed as part of the sdmx.io project under the BIS Open Tech initiative.

SDMX boasts a rich information model with various metadata types. These metadata can power diverse statistical processes, including data collection, validation, and mapping. pysdmx provides an opinionated implementation of a subset of the SDMX information model through Python classes. These classes enable the definition of APIs for statistical data processes, such as:

• Generate the Filesystem Layout
• Create the Physical Data Model
• Validate your data
• Map Your Data
• Configure your processes

To efficiently support these processes, pysdmx model classes can be serialized in various formats, such as JSON, YAML, or MessagePack.

The recording is intended for developers, data scientists, and statisticians. More on pysdmx at https://sdmx.io . More on SDMX at https://sdmx.org .

Objectives

By watching this recording, you will learn about:

• key pysdmx use cases for data producers
• hands on demo on how to use pysdmx
• pysdmx roadmap

Resources

YouTube webinar video recording
Jupyter Notebook used