GHOST-Science-Club/tree-classification-irim
Mar 2025 – Apr 2025
2 Months active
Languages Used
MarkdownPythonShellYAMLpythonyamlINITOML
Technical Skills
CI/CDCode QualityData AugmentationData HandlingData LoadingDocumentation
Mateusz Konat
PROFILE
Mateusz Konat
Over a two-month period, Polak WMC contributed to the GHOST-Science-Club/tree-classification-irim repository by enhancing the reliability and maintainability of its data pipeline and CI/CD workflows. He implemented robust dataset handling and oversampling tests, corrected configuration issues, and expanded automated test coverage using Python and Pytest. His work included optimizing static type checking with mypy, improving code quality through flake8 compliance, and refining test reliability across Linux, macOS, and Windows environments. By integrating GitHub Actions and strengthening configuration management, Polak WMC enabled faster feedback cycles and safer deployments, demonstrating depth in CI/CD, static analysis, and data preprocessing.
Overall Statistics
Feature vs Bugs
80%Features
Repository Contributions
28Total
Bugs
1
Commits
28
Features
4
Lines of code
1,100
Activity Months2
Your Network
7 peopleSame Organization
@gazeta.pl2
Work History
April 2025
14 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary for GHOST-Science-Club/tree-classification-irim focused on strengthening build reliability, type safety, and test quality through CI/CD enhancements and targeted code quality improvements.
14 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary for GHOST-Science-Club/tree-classification-irim focused on strengthening build reliability, type safety, and test quality through CI/CD enhancements and targeted code quality improvements.
April 2025
March 2025
14 Commits • 2 Features
Mar 1, 2025March 2025 (2025-03) — Focused delivery on data pipeline robustness, correct oversampling behavior, and reliable test/CI visibility for GHOST-Science-Club/tree-classification-irim. The changes improve data loading integrity, fix key configuration issues, and provide clear, production-ready test results to stakeholders.
March 2025
14 Commits • 2 Features
Mar 1, 2025March 2025 (2025-03) — Focused delivery on data pipeline robustness, correct oversampling behavior, and reliable test/CI visibility for GHOST-Science-Club/tree-classification-irim. The changes improve data loading integrity, fix key configuration issues, and provide clear, production-ready test results to stakeholders.
Activity
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Quality Metrics
Correctness86.4%
Maintainability86.4%
Architecture80.8%
Performance72.2%
AI Usage20.0%
Skills & Technologies
Programming Languages
INIMarkdownPythonShellTOMLYAMLpythonyaml
Technical Skills
CI/CDCI/CD ConfigurationCode LintingCode QualityCode RefactoringConfigurationConfiguration ManagementData AugmentationData HandlingData LoadingData VisualizationDependency ManagementDocumentationGitHub ActionsImage Processing
Repositories Contributed To
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