dataforgoodfr/13_reveler_inegalites_cinema
Apr 2025 – Apr 2025
1 Month active
Languages Used
DockerfileMarkdownPythonSQL
Technical Skills
Backend DevelopmentCSV ParsingCode RefactoringData EngineeringData SeedingDatabase Management
lina kaci
PROFILE
Lina Kaci
Worked on the dataforgoodfr/13_reveler_inegalites_cinema repository to establish robust data ingestion and search capabilities for film-related datasets. Developed a CSV-based film awards import system, creating initial data models and repositories for awards and related entities using Python, SQL, and SQLAlchemy. Introduced fuzzy film matching leveraging PostgreSQL pg_trgm and unaccent extensions, with supporting database migrations and refactored seeding workflows. Improved code quality by removing unused imports and organizing seed scripts for maintainability. These efforts enhanced data accuracy, streamlined ingestion, and laid a maintainable foundation for future features, aligning technical improvements with business value and ongoing reporting needs.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
9Total
Bugs
1
Commits
9
Features
2
Lines of code
578
Activity Months1
Your Network
12 peopleShared Repositories
12
Audrey DuranMember
FitzfoufouMember
Florian_YunMember
hadrien PoinseauxMember
ndretexMember
Julien-CommesMember
LudivineLacourMember
Nicolas RevelMember
Paul GabrielMember
Work History
April 2025
9 Commits • 2 Features
Apr 1, 2025April 2025 monthly performance summary for dataforgoodfr/13_reveler_inegalites_cinema. Focused on establishing robust data ingestion, quality, and search capabilities for film-related data, with a clear line of sight to business value and maintainability. Key infrastructure and QA improvements align with data accuracy, faster ingestion, and smoother CI/CD.
9 Commits • 2 Features
Apr 1, 2025April 2025 monthly performance summary for dataforgoodfr/13_reveler_inegalites_cinema. Focused on establishing robust data ingestion, quality, and search capabilities for film-related data, with a clear line of sight to business value and maintainability. Key infrastructure and QA improvements align with data accuracy, faster ingestion, and smoother CI/CD.
April 2025
Activity
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Quality Metrics
Correctness86.6%
Maintainability86.6%
Architecture84.4%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
DockerfileMarkdownPythonSQL
Technical Skills
Backend DevelopmentCSV ParsingCode RefactoringData EngineeringData SeedingDatabase ManagementDatabase MigrationsDatabase SeedingDockerDocumentationLintingPostgreSQLPythonSQLSQLAlchemy
Repositories Contributed To
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