neo4j/graph-data-science-client
Aug 2025 – Oct 2025
2 Months active
Languages Used
PythonreStructuredText
Technical Skills
API DesignDocumentation
Alfred Clemedtson
PROFILE
Alfred Clemedtson
Worked on the neo4j/graph-data-science-client repository, delivering two core features over two months focused on API design and documentation. Developed the clique counting API surface, including endpoints for mutate, stream, stats, and write, and implemented memory estimation to support proactive resource planning for large-scale graph analytics. Enhanced the developer experience by providing clear, standards-aligned documentation and improving onboarding workflows. Later, produced comprehensive documentation for the Max-Flow algorithm API, outlining function signatures and usage patterns. All work was completed using Python and reStructuredText, emphasizing maintainability and discoverability without requiring major bug fixes during the development period.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
2
Lines of code
144
Activity Months2
Your Network
60 peopleWork History
October 2025
1 Commits • 1 Features
Oct 1, 2025October 2025: Delivered Max-Flow Algorithm API Documentation for neo4j/graph-data-science-client, including API outline and function signatures for mutate, stats, stream, and write operations. This improves API discoverability and accelerates developer onboarding. No major bugs fixed this period.
1 Commits • 1 Features
Oct 1, 2025October 2025: Delivered Max-Flow Algorithm API Documentation for neo4j/graph-data-science-client, including API outline and function signatures for mutate, stats, stream, and write operations. This improves API discoverability and accelerates developer onboarding. No major bugs fixed this period.
October 2025
August 2025
2 Commits • 1 Features
Aug 1, 2025August 2025: Delivered the clique counting API surface and memory estimation in the Graph Data Science Client, enabling proactive resource planning and safer execution of clique-based analytics. Documented API endpoints (mutate, stream, stats, write) and added memory estimation to forecast resource needs before running the clique counting algorithm. This work enhances operability in production by reducing unexpected resource consumption and improving capacity planning for large graphs. No major bugs reported or fixed this month; focus was on feature delivery, documentation, and onboarding for the neo4j/graph-data-science-client repo.
August 2025
2 Commits • 1 Features
Aug 1, 2025August 2025: Delivered the clique counting API surface and memory estimation in the Graph Data Science Client, enabling proactive resource planning and safer execution of clique-based analytics. Documented API endpoints (mutate, stream, stats, write) and added memory estimation to forecast resource needs before running the clique counting algorithm. This work enhances operability in production by reducing unexpected resource consumption and improving capacity planning for large graphs. No major bugs reported or fixed this month; focus was on feature delivery, documentation, and onboarding for the neo4j/graph-data-science-client repo.
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance73.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonreStructuredText
Technical Skills
API DesignDocumentation
Repositories Contributed To
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