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
During April 2025, Lina Kaci developed robust data ingestion and search capabilities for the dataforgoodfr/13_reveler_inegalites_cinema repository, focusing on film-related data. She implemented a CSV-based film awards import system, establishing new data models and repositories to support awards and related entities. Leveraging Python, SQLAlchemy, and PostgreSQL, Lina introduced fuzzy film matching using pg_trgm and unaccent extensions, enhancing data deduplication and search accuracy. She also refactored the seeding workflow, organized scripts for maintainability, and improved documentation. Her work addressed data quality and ingestion speed, while code cleanup and linting improvements contributed to a more reliable CI/CD pipeline.
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
Overview of all repositories you've contributed to across your timeline