Implement LRU caching and sync.Pool pooling for Go FHIRPath expressions.
npx skills add https://github.com/gofhir/validator --skill go-caching
Please help me install this Agent Skill. Skill: go-caching Source: https://github.com/gofhir/validator/tree/main/.claude/skills/go-caching Command: npx skills add https://github.com/gofhir/validator --skill go-caching
This Skill helps developers optimize Go applications by implementing efficient caching and pooling strategies, reducing memory allocations and improving performance for expensive operations.
sync.Pool for reusable objects like collections, minimizing garbage collection overhead.Use the go-caching skill to understand how to implement an LRU cache for compiled FHIRPath expressions in Go.
High-intent search queries and answers about installing and using this skill.
LRU caching for compiled FHIRPath expressions in Go stores previously evaluated results to speed up repeated processing. This prevents redundant compilation overhead and significantly accelerates complex expression evaluations against multiple resources.
Reducing memory allocations in Go is achieved by implementing object pooling with sync.Pool for reusable collections and caching immutable values. These strategies minimize garbage collection overhead and lower memory pressure during intensive computations.
Use sync.Pool for object pooling in Golang when frequently allocating and discarding temporary objects like intermediate collections. Reusing these objects instead of allocating new ones minimizes garbage collection overhead and reduces memory pressure.
Caching StructureDefinitions and regular expressions in Go avoids repeated compilation and parsing overhead. By storing these immutable objects in memory, applications speed up repeated computations and reduce allocation overhead during resource processing.
Caching small, immutable integer values in Go avoids new object creation by reusing existing cached instances. This value caching technique prevents unnecessary memory allocations during frequent numeric operations and processing.
Object pooling with sync.Pool reduces garbage collection overhead by reusing allocated objects, but it does not eliminate it entirely. Pooling minimizes memory pressure for intermediate results, yet final object cleanup still requires some garbage collection.
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