neo4j/graph-data-science-client
May 2025 – Dec 2025
2 Months active
Languages Used
adocpythonPython
Technical Skills
documentationversion controlApache SparkJupyterdata sciencegraph analytics
Max Kießling
PROFILE
Max Kießling
Contributed to the neo4j/graph-data-science-client repository by enhancing documentation for Apache Spark-based graph analytics workflows in Jupyter notebooks, clarifying usage and improving onboarding for data scientists and developers. Focused on Python and adoc to deliver notebook-ready guidance that accelerates experimentation and reduces support overhead. Additionally, addressed release hygiene by reverting a previous release preparation, updating version numbers, changelog entries, and configuration files to ensure artifact consistency across packaging and CI/CD workflows. This work emphasized careful version control and documentation practices, supporting stable releases and clear user guidance while collaborating across teams to improve both developer productivity and release reliability.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
2Total
Bugs
1
Commits
2
Features
1
Lines of code
56
Activity Months2
Work History
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025 monthly summary for neo4j/graph-data-science-client: Delivered Graph Analytics Notebook Documentation Enhancement for Apache Spark-based graph analytics in Jupyter notebooks. The update clarifies usage, improves readability, and accelerates onboarding for data scientists and developers. No major bugs fixed this month; focus remains on documentation quality and user guidance. This work reduces support time and enables faster experimentation with graph analytics in Spark.
1 Commits • 1 Features
Dec 1, 2025December 2025 monthly summary for neo4j/graph-data-science-client: Delivered Graph Analytics Notebook Documentation Enhancement for Apache Spark-based graph analytics in Jupyter notebooks. The update clarifies usage, improves readability, and accelerates onboarding for data scientists and developers. No major bugs fixed this month; focus remains on documentation quality and user guidance. This work reduces support time and enables faster experimentation with graph analytics in Spark.
December 2025
May 2025
1 Commits
May 1, 2025May 2025 monthly summary for neo4j/graph-data-science-client focused on release hygiene and stability. Key actions include reverting the previously prepared release (1.15.1) and aligning versioning, changelog entries, and configuration files with a new release candidate/preview. No new features were shipped this month; the primary work centered on ensuring accurate artifacts, preventing mislabeling of builds, and improving release process clarity across packaging and CI/CD workflows. This reduces release risk and improves consistency for downstream consumers.
May 2025
1 Commits
May 1, 2025May 2025 monthly summary for neo4j/graph-data-science-client focused on release hygiene and stability. Key actions include reverting the previously prepared release (1.15.1) and aligning versioning, changelog entries, and configuration files with a new release candidate/preview. No new features were shipped this month; the primary work centered on ensuring accurate artifacts, preventing mislabeling of builds, and improving release process clarity across packaging and CI/CD workflows. This reduces release risk and improves consistency for downstream consumers.
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Pythonadocpython
Technical Skills
Apache SparkJupyterdata sciencedocumentationgraph analyticsversion control
Repositories Contributed To
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