name: golang-dependency-injection
description: "Comprehensive guide for dependency injection (DI) in Golang. Covers why DI matters (testability, loose coupling, separation of concerns, lifecycle management), manual constructor injection, and DI library comparison (google/wire, uber-go/dig, uber-go/fx, samber/do). Use this skill when designing service architecture, setting up dependency injection, refactoring tightly coupled code, managing singletons or service factories, or when the user asks about inversion of control, service containers, or wiring dependencies in Go. For a specific DI library, → See samber/cc-skills-golang@golang-google-wire, samber/cc-skills-golang@golang-uber-dig, samber/cc-skills-golang@golang-uber-fx, or samber/cc-skills-golang@golang-samber-do skills."
user-invocable: true
license: MIT
compatibility: Designed for Claude Code or similar AI coding agents, and for projects using Golang.
metadata:
author: samber
version: "1.2.2"
openclaw:
emoji: "🔌"
homepage: https://github.com/samber/cc-skills-golang
requires:
bins:
- go
install: []
allowed-tools: Read Edit Write Glob Grep Bash(go:) Bash(golangci-lint:) Bash(git:*) Agent WebFetch mcp__context7__resolve-library-id mcp__context7__query-docs AskUserQuestion
Persona: You are a Go software architect. You guide teams toward testable, loosely coupled designs — you choose the simplest DI approach that solves the problem, and you never over-engineer.
Orchestration mode: Use ultracode when refactoring a large coupled codebase toward dependency injection — orchestrate the three sub-agents described in Refactor mode (global/init discovery, concrete-dependency mapping, service-locator detection) and consolidate into one migration plan.
Modes:
- Design mode (new project, new service, or adding a service to an existing DI setup): assess the existing dependency graph and lifecycle needs; recommend manual injection or a library from the decision table; then generate the wiring code.
- Refactor mode (existing coupled code): use up to 3 parallel sub-agents — Agent 1 identifies global variables and
init()service setup, Agent 2 maps concrete type dependencies that should become interfaces, Agent 3 locates service-locator anti-patterns (container passed as argument) — then consolidate findings and propose a migration plan.
Community default. A company skill that explicitly supersedes
samber/cc-skills-golang@golang-dependency-injectionskill takes precedence.
Dependency Injection in Go
Dependency injection (DI) means passing dependencies to a component rather than having it create or find them. In Go, this is how you build testable, loosely coupled applications — your services declare what they need, and the caller (or container) provides it.
This skill is not exhaustive. When using a DI library (google/wire, uber-go/dig, uber-go/fx, samber/do), refer to the library's official documentation and code examples for current API signatures.
For interface-based design foundations (accept interfaces, return structs), see the samber/cc-skills-golang@golang-structs-interfaces skill.
Best Practices Summary
- Dependencies MUST be injected via constructors — NEVER use global variables or
init()for service setup - Small projects (< 10 services) SHOULD use manual constructor injection — no library needed
- Interfaces MUST be defined where consumed, not where implemented — accept interfaces, return structs
- NEVER use global registries or package-level service locators
- The DI container MUST only exist at the composition root (
main()or app startup) — NEVER pass the container as a dependency - Prefer lazy initialization — only create services when first requested
- Use singletons for stateful services (DB connections, caches) and transients for stateless ones
- Mock at the interface boundary — DI makes this trivial
- Keep the dependency graph shallow — deep chains signal design problems
- Choose the right DI library for your project size and team — see the decision table below
Why Dependency Injection?
| Problem without DI | How DI solves it |
|---|---|
| Functions create their own dependencies | Dependencies are injected — swap implementations freely |
| Testing requires real databases, APIs | Pass mock implementations in tests |
| Changing one component breaks others | Loose coupling via interfaces — components don't know each other's internals |
| Services initialized everywhere | Centralized container manages lifecycle (singleton, factory, lazy) |
| All services loaded at startup | Lazy loading — services created only when first requested |
Global state and init() functions | Explicit wiring at startup — predictable, debuggable |
DI shines in applications with many interconnected services — HTTP servers, microservices, CLI tools with plugins. For a small script with 2-3 functions, manual wiring is fine. Don't over-engineer.
Manual Constructor Injection (No Library)
For small projects, pass dependencies through constructors. See Manual DI examples for a complete application example.
// ✓ Good — explicit dependencies, testable
type UserService struct {
db UserStore
mailer Mailer
logger *slog.Logger
}
func NewUserService(db UserStore, mailer Mailer, logger *slog.Logger) *UserService {
return &UserService{db: db, mailer: mailer, logger: logger}
}
// main.go — manual wiring
func main() {
logger := slog.Default()
db := postgres.NewUserStore(connStr)
mailer := smtp.NewMailer(smtpAddr)
userSvc := NewUserService(db, mailer, logger)
orderSvc := NewOrderService(db, logger)
api := NewAPI(userSvc, orderSvc, logger)
api.ListenAndServe(":8080")
}
// ✗ Bad — hardcoded dependencies, untestable
type UserService struct {
db *sql.DB
}
func NewUserService() *UserService {
db, _ := sql.Open("postgres", os.Getenv("DATABASE_URL")) // hidden dependency
return &UserService{db: db}
}
Manual DI breaks down when:
- You have 15+ services with cross-dependencies
- You need lifecycle management (health checks, graceful shutdown)
- You want lazy initialization or scoped containers
- Wiring order becomes fragile and hard to maintain
DI Library Comparison
Go has three main approaches to DI libraries:
- google/wire examples — Compile-time code generation
- uber-go/dig + fx examples — Reflection-based framework
- samber/do examples — Generics-based, no code generation
Decision Table
| Criteria | Manual | google/wire | uber-go/dig + fx | samber/do |
|---|---|---|---|---|
| Project size | Small (< 10 services) | Medium-Large | Large | Any size |
| Type safety | Compile-time | Compile-time (codegen) | Runtime (reflection) | Compile-time (generics) |
| Code generation | None | Required (wire_gen.go) | None | None |
| Reflection | None | None | Yes | None |
| API style | N/A | Provider sets + build tags | Struct tags + decorators | Simple, generic functions |
| Lazy loading | Manual | N/A (all eager) | Built-in (fx) | Built-in |
| Singletons | Manual | Built-in | Built-in | Built-in |
| Transient/factory | Manual | Manual | Built-in | Built-in |
| Scopes/modules | Manual | Provider sets | Module system (fx) | Built-in (hierarchical) |
| Health checks | Manual | Manual | Manual | Built-in interface |
| Graceful shutdown | Manual | Manual | Built-in (fx) | Built-in interface |
| Container cloning | N/A | N/A | N/A | Built-in |
| Debugging | Print statements | Compile errors | fx.Visualize() | ExplainInjector(), web interface |
| Go version | Any | Any | Any | 1.18+ (generics) |
| Learning curve | None | Medium | High | Low |
Quick Comparison: Same App, Four Ways
The dependency graph: Config -> Database -> UserStore -> UserService -> API
Manual:
cfg := NewConfig()
db := NewDatabase(cfg)
store := NewUserStore(db)
svc := NewUserService(store)
api := NewAPI(svc)
api.Run()
// No automatic shutdown, health checks, or lazy loading
google/wire:
// wire.go — then run: wire ./...
func InitializeAPI() (*API, error) {
wire.Build(NewConfig, NewDatabase, NewUserStore, NewUserService, NewAPI)
return nil, nil
}
// No lifecycle hooks (OnStart/OnStop) or health checks; cleanup via returned func() from providers
uber-go/fx:
app := fx.New(
fx.Provide(NewConfig, NewDatabase, NewUserStore, NewUserService),
fx.Invoke(func(api *API) { api.Run() }),
)
app.Run() // manages lifecycle, but reflection-based
samber/do:
i := do.New()
do.Provide(i, NewConfig)
do.Provide(i, NewDatabase) // auto shutdown + health check
do.Provide(i, NewUserStore)
do.Provide(i, NewUserService)
api := do.MustInvoke[*API](i)
api.Run()
// defer i.Shutdown() — handles all cleanup automatically
Testing with DI
DI makes testing straightforward — inject mocks instead of real implementations:
// Define a mock
type MockUserStore struct {
users map[string]*User
}
func (m *MockUserStore) FindByID(ctx context.Context, id string) (*User, error) {
u, ok := m.users[id]
if !ok {
return nil, ErrNotFound
}
return u, nil
}
// Test with manual injection
func TestUserService_GetUser(t *testing.T) {
mock := &MockUserStore{
users: map[string]*User{"1": {ID: "1", Name: "Alice"}},
}
svc := NewUserService(mock, nil, slog.Default())
user, err := svc.GetUser(context.Background(), "1")
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if user.Name != "Alice" {
t.Errorf("got %q, want %q", user.Name, "Alice")
}
}
Testing with samber/do — Clone and Override
Container cloning creates an isolated copy where you override only the services you need to mock:
func TestUserService_WithDo(t *testing.T) {
// Create a test injector with mock implementation
testInjector := do.New()
// Provide the mock UserStore interface
do.OverrideValue[UserStore](testInjector, &MockUserStore{
users: map[string]*User{"1": {ID: "1", Name: "Alice"}},
})
// Provide other real services as needed
do.Provide[*slog.Logger](testInjector, func(i *do.Injector) (*slog.Logger, error) {
return slog.Default(), nil
})
svc := do.MustInvoke[*UserService](testInjector)
user, err := svc.GetUser(context.Background(), "1")
// ... assertions
}
This is particularly useful for integration tests where you want most services to be real but need to mock a specific boundary (database, external API, mailer).
When to Adopt a DI Library
| Signal | Action |
|---|---|
| < 10 services, simple dependencies | Stay with manual constructor injection |
| 10-20 services, some cross-cutting concerns | Consider a DI library |
| 20+ services, lifecycle management needed | Strongly recommended |
| Need health checks, graceful shutdown | Use a library with built-in lifecycle support |
| Team unfamiliar with DI concepts | Start manual, migrate incrementally |
Common Mistakes
| Mistake | Fix |
|---|---|
| Global variables as dependencies | Pass through constructors or DI container |
init() for service setup | Explicit initialization in main() or container |
| Depending on concrete types | Accept interfaces at consumption boundaries |
| Passing the container everywhere (service locator) | Inject specific dependencies, not the container |
| Deep dependency chains (A->B->C->D->E) | Flatten — most services should depend on repositories and config directly |
| Creating a new container per request | One container per application; use scopes for request-level isolation |
Cross-References
- → See
samber/cc-skills-golang@golang-samber-doskill for detailed samber/do usage patterns - → See
samber/cc-skills-golang@golang-structs-interfacesskill for interface design and composition - → See
samber/cc-skills-golang@golang-testingskill for testing with dependency injection - → See
samber/cc-skills-golang@golang-project-layoutskill for DI initialization placement