April 2026: Delivered STAC Pydantic Data Models by introducing the stac-pydantic package for conda-forge/staged-recipes, enabling validated, STAC-compliant data structures for geospatial workflows. This work improves data quality, reliability, and interoperability across downstream pipelines, and establishes a scalable foundation for future validation and schema evolution.

March 2026 monthly summary for CS-SI/eodag focusing on stabilizing and extending EODAG's handling of external collections and product types by merging develop into main. This merge aligns development work with the main branch, enabling enhanced data-source interoperability and more flexible product type management, setting the stage for future ingestion improvements and analytics workflows.

Monthly summary for 2025-08: Consolidated EODAG core changes by merging development updates into the main branch, preparing the project for upcoming releases. The merge represents a critical integration step that aligns ongoing improvements with the stable main branch, enabling safer feature delivery and faster time to production.

May 2025 monthly summary for CS-SI/eodag highlighting release workflow improvements and automation work focused on PyPI publish toggle. No major bugs fixed this period. The effort improves release reliability, artifact governance, and automation efficiency.

March 2025 monthly summary for CS-SI/stac-fastapi-eodag: Delivered measurable improvements in test coverage, standardized testing workflows, and a critical bug fix that unblocked search functionality. These changes reduce regression risk, speed up release cycles, and enhance product reliability for users accessing landing pages, downloads, and search endpoints.

February 2025 monthly summary for CS-SI/stac-fastapi-eodag: Delivered platform upgrades, test optimizations, and search reliability fixes that improve performance, stability, and developer productivity. Key outcomes include Python 3.9 compatibility and stac-fastapi v4+ upgrade with Ruff integration, faster and more reliable tests, and robust search error handling with correct aggregation and reset of persistent date filters.