November 2025 monthly summary for keboola/platform-libraries. Focused on delivering core API capabilities, improving data-model consistency, and strengthening test coverage to boost reliability and developer experience. Highlights include Apps API integration with a simplified App model, expanded test suites for sanitizers and the sandboxes client, and documentation cleanup to reflect API changes. These efforts drive faster, safer integrations for apps and sandboxes in production.

Concise monthly summary for 2025-10 focused on delivering data-integrity enhancements through sanitizer integration, stabilizing tests and CI, and refining test coverage for webalization scenarios. The month emphasized business value by hardening data pipelines and improving maintainability across the platform-libraries repository.

Month: 2025-09 — Delivered a production-ready Keboola Query Service API client and stabilized CI/CD for the Keboola Platform Libraries. This work enables external integrations, accelerates deployments, and improves release reliability through automated testing, packaging, and containerization.

August 2025: Delivered a new LoadTableQueue API method to retrieve load table tasks with added unit tests, and fixed a bug to ensure reliable task retrieval.

July 2025 monthly summary for keboola/connection-docs focusing on Conditional Flows documentation. Delivered comprehensive docs, clarified dynamic branching, and improved assets. Despite feature not yet surfaced in the UI, documentation now provides complete access/build/config guidance, with robust asset referencing and corrected URL structure. Minor doc polish ready for release to public docs site.

Month: 2024-11 – keboola/connection-docs Key features delivered: - Data Apps Docker image modernization: Upgraded the data-apps Dockerfile to Python 3.10-slim with pre-installed data science and Streamlit packages, boosting robustness, compatibility, and deployment consistency for data applications. Major bugs fixed: - No major bugs fixed in keboola/connection-docs this month. Overall impact and accomplishments: - Environment upgrade reduces runtime failures and simplifies onboarding/maintenance for data apps in the Docs repository. - Documentation clearly states the base image (Python 3.10-slim), reducing drift and support overhead. Technologies/skills demonstrated: - Dockerfile/base image management, Python 3.10-slim - Data science and Streamlit package integration - Documentation maintenance and commit traceability