gooddata/gooddata-python-sdk
Sep 2025 – Jan 2026
2 Months active
Languages Used
PythonYAML
Technical Skills
API IntegrationBackend DevelopmentData ModelingPythonTestingAPI development
Pavel Cerny
PROFILE
Pavel Cerny
Worked on the gooddata/gooddata-python-sdk repository, focusing on enhancing data modeling and backend reliability for analytics workflows. Delivered support for alternative data source IDs, updating both entity and declarative models to allow flexible data source configuration and streamline pipeline management. Addressed a key bug affecting the loading of aggregated facts in entity datasets by refining API side-loading patterns and updating integration tests to mirror API responses. Used Python and YAML to implement these changes, emphasizing robust API integration and comprehensive testing. The work improved data accuracy, reduced configuration friction, and strengthened the SDK’s compatibility with evolving data management requirements.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
3Total
Bugs
1
Commits
3
Features
1
Lines of code
4,334
Activity Months2
Your Network
74 peopleSame Organization
@gooddata.com45
Adam FiedlerMember
alexole01Member
Andy ChumakMember
Anna BenkeMember
Auto ImplementerMember
GoodData AutomationMember
nknbichMember
Christopher BonillaMember
Dan HomolaMember
Shared Repositories
29
Adam FiedlerMember
alexole01Member
Marcelo G. AlmironMember
Anna BenkeMember
Auto ImplementerMember
GoodData AutomationMember
Christopher BonillaMember
Dan HomolaMember
dkalocGDMember
Work History
January 2026
1 Commits • 1 Features
Jan 1, 20262026-01 monthly summary for gooddata/gooddata-python-sdk: Key feature delivered is Alternative Data Source ID Support, extending both the data source entity model and the declarative model to allow specifying an alternative data source ID. This enables greater flexibility in data source configuration and supports varied data management scenarios. Implemented in commit 218fe17df54efa78e7846f85ba2bcef7d4e536de (feat: add support for data source alternative ds id; CQ-1832; risk: low). Major bugs fixed: none reported this month. Overall impact: reduces configuration friction, accelerates data source setup, and improves reliability of data pipelines by supporting diverse data source identifiers. Technologies/skills demonstrated: Python SDK development, data model enhancements (entity and declarative), data source management, and traceable commits/issue tracking.
1 Commits • 1 Features
Jan 1, 20262026-01 monthly summary for gooddata/gooddata-python-sdk: Key feature delivered is Alternative Data Source ID Support, extending both the data source entity model and the declarative model to allow specifying an alternative data source ID. This enables greater flexibility in data source configuration and supports varied data management scenarios. Implemented in commit 218fe17df54efa78e7846f85ba2bcef7d4e536de (feat: add support for data source alternative ds id; CQ-1832; risk: low). Major bugs fixed: none reported this month. Overall impact: reduces configuration friction, accelerates data source setup, and improves reliability of data pipelines by supporting diverse data source identifiers. Technologies/skills demonstrated: Python SDK development, data model enhancements (entity and declarative), data source management, and traceable commits/issue tracking.
January 2026
September 2025
2 Commits
Sep 1, 2025September 2025 performance summary for gooddata/gooddata-python-sdk focusing on data correctness, stability, and test coverage. Key bug fix delivered to improve data loading for entity datasets and ensure API side-loads are respected across the client state. Key features delivered: - Fix loading aggregated facts for entity datasets by introducing _relation_entity_from_side_loads and updating include for aggregatedFacts. - Ensure CatalogDataset's facts and aggregated_facts are populated from API side-loads, aligning client state with API responses. Major bugs fixed: - Correct loading of aggregated facts and related entities in entity datasets; updated integration test data to reflect API responses. Overall impact and accomplishments: - Improved data accuracy and reliability for downstream analytics; reduced risk of inconsistent facts aggregation. - Strengthened test coverage and API compatibility, enabling safer refactors and future enhancements. Technologies/skills demonstrated: - Python SDK development, API side-loading patterns, integration testing, and repository maintenance (gooddata/gooddata-python-sdk).
September 2025
2 Commits
Sep 1, 2025September 2025 performance summary for gooddata/gooddata-python-sdk focusing on data correctness, stability, and test coverage. Key bug fix delivered to improve data loading for entity datasets and ensure API side-loads are respected across the client state. Key features delivered: - Fix loading aggregated facts for entity datasets by introducing _relation_entity_from_side_loads and updating include for aggregatedFacts. - Ensure CatalogDataset's facts and aggregated_facts are populated from API side-loads, aligning client state with API responses. Major bugs fixed: - Correct loading of aggregated facts and related entities in entity datasets; updated integration test data to reflect API responses. Overall impact and accomplishments: - Improved data accuracy and reliability for downstream analytics; reduced risk of inconsistent facts aggregation. - Strengthened test coverage and API compatibility, enabling safer refactors and future enhancements. Technologies/skills demonstrated: - Python SDK development, API side-loading patterns, integration testing, and repository maintenance (gooddata/gooddata-python-sdk).
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture80.0%
Performance76.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonYAML
Technical Skills
API IntegrationAPI developmentBackend DevelopmentData ModelingPythonTestingbackend developmentdata modeling
Repositories Contributed To
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