Project ‘LinkageX’ is the Swiss Army knife for SDMX. Aimed at data scientists and developers, LinkageX simplifies the use of SDMX data and metadata, enabling seamless integration and full utilization of the SDMX metamodel. This powerful Python-based toolkit streamlines SDMX-related workflows, enhancing data synchronization and harmonization efficiency and effectiveness.
Project LinkageX is a collection of Python libraries and tools, that are built on top of SDMX to allow utilizing the SDMX features, without having to deal with the technicalities and complexity of the standard. These libraries are based on existing developed SDMX code or APIs to provide a pythonic view of SDMX data and metadata leveraging the richness of SDMX. Thus, they can be integrated with existing SDMX tools, like the FMR or other SDMX API compatible services. Project LinkageX includes the following:
pysdmx: a pragmatic and opinionated library written in Python. It focuses on simplicity, providing a subset of SDMX functionalities without requiring advanced knowledge of SDMX. More
gingado: a machine learning library focused on economics and finance use cases. This package aims to be suitable for beginners and advanced users alike. Use cases may range from programmatic data retrievals using SDMX to experimentation with machine learning-based econometric estimators to more complex forecasting pipelines used in production. More
more to come …