sickn33/antigravity-awesome-skills/fp-data-transforms
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Everyday data transformations using functional patterns - arrays, objects, grouping, aggregation, and null-safe access
Install
npx vskill@latest install sickn33/antigravity-awesome-skills/fp-data-transformsSKILL.md
Practical Data Transformations
This skill covers the data transformations you do every day: working with arrays, reshaping objects, normalizing API responses, grouping data, and safely accessing nested values. Each section shows the imperative approach first, then the functional equivalent, with honest assessments of when each approach shines.
Detailed Guide
Read the detailed guide before executing this skill. It retains the complete procedure and reference material. Treat its safety, prerequisites, and validation requirements as mandatory. For focused work, load the relevant sections; for end-to-end work, read the guide completely.
When to Use
- You need to transform arrays, objects, grouped data, or nested values in TypeScript.
- The task involves reshaping API responses, null-safe access, aggregation, or normalization.
- You want practical functional patterns for everyday data work instead of low-level loops.
6. Real-World Examples
Example 1: Transform API Response to UI-Ready Data
Example 2: Merge User Settings with Defaults
Example 3: Group Orders by Customer with Totals
Example 4: Safely Access Deeply Nested Config
7. When to Use What
Use Native Methods When:
- Simple transformations:
.map(),.filter(),.reduce()are perfectly good - No composition needed: You're doing a one-off transformation
- Team familiarity: Everyone knows native methods
- Optional chaining suffices:
obj?.prop?.value ?? defaulthandles your null-safety needs
Use fp-ts When:
- Chaining operations that might fail: Multiple steps where each can return nothing
- Composing transformations: Building reusable transformation pipelines
- Type-safe error handling: You want the compiler to track potential failures
- Complex data pipelines: Many steps that benefit from explicit composition
Use Custom Utilities When:
- Domain-specific operations:
groupBy,countBy,sumByfor your data - Repeated patterns: You find yourself writing the same transformation many times
- Team conventions: Establishing consistent patterns across the codebase
Performance Considerations
- Chaining creates intermediate arrays:
arr.filter().map()creates one array, then another - For hot paths, consider `reduce`: One pass through the data
- Measure before optimizing: The readability cost of optimization is often not worth it
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/fp-data-transforms/SKILL.md
Popularity
- Repository stars
- 25,646
- Repository forks
- 4,384
- Repository npm downloads, 7 days
- 11,772
- 7-day trend score
- 72
Stars and forks are for the whole GitHub repository, not this skill alone. Downloads are for the repository's npm package. Refreshed 19 Mar 2026, 7 months ago.
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