Agent skill
swift-protocol-di-testing
Protocol-based dependency injection for testable Swift code — mock file system, network, and external APIs using focused protocols and Swift Testing.
Install this agent skill to your Project
npx add-skill https://github.com/x-cmd/skill/tree/main/data/affaanmustafa/swift-protocol-di-testing
SKILL.md
Swift Protocol-Based Dependency Injection for Testing
Patterns for making Swift code testable by abstracting external dependencies (file system, network, iCloud) behind small, focused protocols. Enables deterministic tests without I/O.
When to Activate
- Writing Swift code that accesses file system, network, or external APIs
- Need to test error handling paths without triggering real failures
- Building modules that work across environments (app, test, SwiftUI preview)
- Designing testable architecture with Swift concurrency (actors, Sendable)
Core Pattern
1. Define Small, Focused Protocols
Each protocol handles exactly one external concern.
// File system access
public protocol FileSystemProviding: Sendable {
func containerURL(for purpose: Purpose) -> URL?
}
// File read/write operations
public protocol FileAccessorProviding: Sendable {
func read(from url: URL) throws -> Data
func write(_ data: Data, to url: URL) throws
func fileExists(at url: URL) -> Bool
}
// Bookmark storage (e.g., for sandboxed apps)
public protocol BookmarkStorageProviding: Sendable {
func saveBookmark(_ data: Data, for key: String) throws
func loadBookmark(for key: String) throws -> Data?
}
2. Create Default (Production) Implementations
public struct DefaultFileSystemProvider: FileSystemProviding {
public init() {}
public func containerURL(for purpose: Purpose) -> URL? {
FileManager.default.url(forUbiquityContainerIdentifier: nil)
}
}
public struct DefaultFileAccessor: FileAccessorProviding {
public init() {}
public func read(from url: URL) throws -> Data {
try Data(contentsOf: url)
}
public func write(_ data: Data, to url: URL) throws {
try data.write(to: url, options: .atomic)
}
public func fileExists(at url: URL) -> Bool {
FileManager.default.fileExists(atPath: url.path)
}
}
3. Create Mock Implementations for Testing
public final class MockFileAccessor: FileAccessorProviding, @unchecked Sendable {
public var files: [URL: Data] = [:]
public var readError: Error?
public var writeError: Error?
public init() {}
public func read(from url: URL) throws -> Data {
if let error = readError { throw error }
guard let data = files[url] else {
throw CocoaError(.fileReadNoSuchFile)
}
return data
}
public func write(_ data: Data, to url: URL) throws {
if let error = writeError { throw error }
files[url] = data
}
public func fileExists(at url: URL) -> Bool {
files[url] != nil
}
}
4. Inject Dependencies with Default Parameters
Production code uses defaults; tests inject mocks.
public actor SyncManager {
private let fileSystem: FileSystemProviding
private let fileAccessor: FileAccessorProviding
public init(
fileSystem: FileSystemProviding = DefaultFileSystemProvider(),
fileAccessor: FileAccessorProviding = DefaultFileAccessor()
) {
self.fileSystem = fileSystem
self.fileAccessor = fileAccessor
}
public func sync() async throws {
guard let containerURL = fileSystem.containerURL(for: .sync) else {
throw SyncError.containerNotAvailable
}
let data = try fileAccessor.read(
from: containerURL.appendingPathComponent("data.json")
)
// Process data...
}
}
5. Write Tests with Swift Testing
import Testing
@Test("Sync manager handles missing container")
func testMissingContainer() async {
let mockFileSystem = MockFileSystemProvider(containerURL: nil)
let manager = SyncManager(fileSystem: mockFileSystem)
await #expect(throws: SyncError.containerNotAvailable) {
try await manager.sync()
}
}
@Test("Sync manager reads data correctly")
func testReadData() async throws {
let mockFileAccessor = MockFileAccessor()
mockFileAccessor.files[testURL] = testData
let manager = SyncManager(fileAccessor: mockFileAccessor)
let result = try await manager.loadData()
#expect(result == expectedData)
}
@Test("Sync manager handles read errors gracefully")
func testReadError() async {
let mockFileAccessor = MockFileAccessor()
mockFileAccessor.readError = CocoaError(.fileReadCorruptFile)
let manager = SyncManager(fileAccessor: mockFileAccessor)
await #expect(throws: SyncError.self) {
try await manager.sync()
}
}
Best Practices
- Single Responsibility: Each protocol should handle one concern — don't create "god protocols" with many methods
- Sendable conformance: Required when protocols are used across actor boundaries
- Default parameters: Let production code use real implementations by default; only tests need to specify mocks
- Error simulation: Design mocks with configurable error properties for testing failure paths
- Only mock boundaries: Mock external dependencies (file system, network, APIs), not internal types
Anti-Patterns to Avoid
- Creating a single large protocol that covers all external access
- Mocking internal types that have no external dependencies
- Using
#if DEBUGconditionals instead of proper dependency injection - Forgetting
Sendableconformance when used with actors - Over-engineering: if a type has no external dependencies, it doesn't need a protocol
When to Use
- Any Swift code that touches file system, network, or external APIs
- Testing error handling paths that are hard to trigger in real environments
- Building modules that need to work in app, test, and SwiftUI preview contexts
- Apps using Swift concurrency (actors, structured concurrency) that need testable architecture
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
pufferlib
High-performance reinforcement learning framework optimized for speed and scale. Use when you need fast parallel training, vectorized environments, multi-agent systems, or integration with game environments (Atari, Procgen, NetHack). Achieves 2-10x speedups over standard implementations. For quick prototyping or standard algorithm implementations with extensive documentation, use stable-baselines3 instead.
fluidsim
Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.
metabolomics-workbench-database
Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and biomarker discovery.
geniml
This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.
zinc-database
Access ZINC (230M+ purchasable compounds). Search by ZINC ID/SMILES, similarity searches, 3D-ready structures for docking, analog discovery, for virtual screening and drug discovery.
astropy
Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.
Didn't find tool you were looking for?