go-test-table-driven
Deep dive on table-driven tests in Go: when to use them, when to avoid them, struct design, subtest naming, advanced patterns like test matrices and shared setup, and refactoring bloated tables into clean ones. Use when writing table-driven tests, refactoring test tables, reviewing table test structure, or deciding whether table-driven is the right approach. Trigger examples: "table-driven test", "table test", "test cases struct", "test matrix", "parametrize tests", "data-driven test", "refactor test table". Not for: general test strategy, mocks, golden files, fuzzing (go-test-quality), benchmarks (go-performance-review).
How do I install this agent skill?
npx skills add https://github.com/eduardo-sl/go-agent-skills --skill go-test-table-drivenIs this agent skill safe to install?
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The skill provides comprehensive and safe guidance for writing and refactoring table-driven tests in Go. No security issues or malicious patterns were detected.
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What does this agent skill do?
Go Table-Driven Tests
Table-driven tests are a powerful Go idiom — when used correctly. Most codebases either underuse them (10 copy-paste tests) or overuse them (complex branching logic in a 200-line struct). This skill covers the sweet spot.
Detailed reference material, loaded on demand:
references/patterns.md— full worked examples: canonical tables,wantErr/wantErrIs, parallel tables, map-based tables, error-only tables, struct alignment for readability.references/refactoring.md— recognizing bloated tables and rewriting them as explicit subtests, with before/after examples.
Read a reference file only when the summary below is not enough for the task at hand.
1. When Table-Driven Tests Shine
Use a table only when ALL of these are true:
- Same function under test across all cases
- Same assertion pattern — input in, output out, compare
- Cases differ only in data, not in setup or verification logic
- 3+ cases — fewer than 3, explicit tests are clearer
Canonical use case: pure functions, parsers, validators, formatters.
func TestParseSize(t *testing.T) {
tests := []struct {
name string
input string
want int64
wantErr bool
}{
{name: "plain bytes", input: "1024", want: 1024},
{name: "kilobytes suffix", input: "4KB", want: 4096},
{name: "empty string", input: "", wantErr: true},
{name: "negative size", input: "-1", wantErr: true},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
got, err := ParseSize(tt.input)
if tt.wantErr {
require.Error(t, err)
return
}
require.NoError(t, err)
assert.Equal(t, tt.want, got)
})
}
}
Every case has the same shape, the loop body is a few lines, and adding a case is one struct literal. No branching, no conditionals.
2. When NOT to Use Table-Driven Tests
- Complex per-case setup —
setupMock/setupFuncfunction fields in the struct mean the table is hiding complexity. Write explicit subtests. - Fewer than 3 cases — the struct definition is more code than two plain test functions.
- Multiple branching paths —
if tt.shouldError/if tt.wantRedirectin the loop body means each branch is a different test pretending to share a structure. Split it.
See references/refactoring.md for before/after rewrites of each smell.
3. Struct Design Rules
- Every field must vary between at least 2 cases. A field with the same value everywhere is setup — move it outside the table.
- Name the
namefield as a short sentence describing the scenario:"returns error for negative amount", not"case1"or"success". wantErr boolfor "should it error?" — check it first andreturnearly in the loop body.wantErrIs errorwith a sentinel when the caller must detect a specific error; assert withrequire.ErrorIs.- ≤5 fields. More means the scenario is too complex for a table — split into separate test functions.
Full field-pattern examples are in references/patterns.md.
4. The Loop Body Must Be Trivial
The point of a table test is identical execution logic for every case. Keep the loop body under ~10 lines: call, error check, comparison. If it accumulates conditionals or per-case setup, the table has outgrown its usefulness — refactor into explicit subtests.
5. Parallel Table Tests
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
t.Parallel()
got := Transform(tt.input)
assert.Equal(t, tt.want, got)
})
}
- Go 1.22+ scopes the loop variable per iteration —
tt := ttcapture is unnecessary. For Go <1.22 the capture is still required. - Only use
t.Parallel()when the function under test has no side effects and no shared mutable state.
6. Refactoring Bloated Tables
| Symptom | Fix |
|---|---|
| Struct has 8+ fields | Split into multiple test functions by scenario |
setupFunc field in struct | Extract to separate subtests with explicit setup |
if tt.shouldX in loop body | Each branch is a different test — split it |
| Same 3 fields identical in every case | Move to shared setup outside the table |
| Adding a case requires understanding all others | Table has grown beyond its useful life |
Decision Flowchart
-
Is the function pure (input → output, no side effects)? Yes → table test is probably ideal. Go to 2. No → consider explicit subtests first.
-
Do all cases share the exact same assertion pattern? Yes → table test. Go to 3. No → explicit subtests.
-
Can each case be expressed in ≤5 struct fields? Yes → table test. No → split by scenario into separate test functions.
-
Is the loop body ≤10 lines? Yes → you're golden. No → the table is hiding complexity. Refactor.
Verification Checklist
- Table struct has only fields that vary between cases
- Every case has a descriptive
namefield - Loop body is ≤10 lines with no branching
- No
setupFuncormockFuncfields in the struct wantErris a simple bool or sentinel, not a string match- Cases cover: happy path, error path, edge cases (empty, nil, zero, max)
t.Runwraps each case for named subtestst.Parallel()used only when function is side-effect-free
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
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