feat: Phase 3 - Query layer Polars support + benchmarks #1047
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EngCaioFonseca wants to merge 1 commit intopolars/phase-1-setup-and-pilotfrom
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feat: Phase 3 - Query layer Polars support + benchmarks #1047EngCaioFonseca wants to merge 1 commit intopolars/phase-1-setup-and-pilotfrom
EngCaioFonseca wants to merge 1 commit intopolars/phase-1-setup-and-pilotfrom
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…sions Phase 3 - Query Layer: - Add Polars support to cache_facade.py: - retrieve_from_cache() now accepts as_polars=True for Polars output - New retrieve_from_cache_polars() convenience function - Direct Polars DataFrame creation from cursor results Performance Benchmarks: - Add benchmarks/polars_benchmark.py with comprehensive tests: - DataFrame creation comparison - GroupBy aggregation - Filter + Sort operations - Conditional column creation - Vectorized log calculations - Cumsum threshold finding - Open items counting More Module Conversions (Phase 2 continued): - contrib_importance_over_time.py: - Polars for initial datetime processing - Polars groupby + pivot in cntrb_prolificacy_over_time() - Replaced .apply() loop with list comprehension - issues_over_time.py: - Polars for datetime conversion and sorting - Vectorized open count with get_open_vectorized() - pr_over_time.py: - Polars for datetime conversion and sorting - Vectorized open count with get_open_vectorized() Total modules using Polars: 6+ (repo_general_info, code_languages, ossf_scorecard, contrib_importance_over_time, issues_over_time, pr_over_time) Architecture maintained: Polars Core, Pandas Edge
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PR of the series of migrating pandas to polars in 8knot.
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