home / skills / zenobi-us / dotfiles / bats-testing
This skill helps you write robust shell-native end-to-end tests for CLI tools, Bash libraries, and REST APIs using Bats.
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---
name: bats-testing
description: Use when writing shell-native tests for CLI tools, sourced Bash libraries, or REST APIs, especially when process boundaries, shell state, and exit/output behavior must be verified end-to-end.
---
# Testing with Bats
## Overview
Bats is best when correctness depends on real shell behavior: exit codes, stdout/stderr, sourced functions, and external commands.
Core principle: **test behavior at the shell boundary, not implementation details.**
## When to Use
Use this skill when you need to:
- Write e2e tests for CLI tools
- Test Bash libraries that are `source`d (not executed)
- Use Bats as a shell-native REST API test runner with `curl` + `jq`
Typical symptoms:
- "My script works manually but fails in CI"
- "I can test command output, but not sourced function behavior"
- "I need lightweight API tests from shell pipelines"
## Project Setup
Recommended layout:
```text
test/
helpers/
test_helper.bash
cli_*.bats
lib_*.bats
api_*.bats
```
`test/helpers/test_helper.bash`:
```bash
#!/usr/bin/env bash
load 'test_helper/bats-support/load'
load 'test_helper/bats-assert/load'
setup_test_tmp() {
export TEST_TMPDIR="$(mktemp -d)"
}
teardown_test_tmp() {
rm -rf "$TEST_TMPDIR"
}
```
## Pattern 1: CLI e2e Tests
Test real invocation and output contracts.
```bash
#!/usr/bin/env bats
load './helpers/test_helper.bash'
setup() {
setup_test_tmp
export HOME="$TEST_TMPDIR/home"
mkdir -p "$HOME"
}
teardown() {
teardown_test_tmp
}
@test "todoctl add persists item" {
run todoctl add "buy milk"
assert_success
assert_output --partial "added"
run todoctl list --json
assert_success
echo "$output" | jq -e 'any(.[]; .text == "buy milk")'
}
@test "todoctl add rejects empty text" {
run todoctl add ""
assert_failure
assert_output --partial "text is required"
}
```
### Notes
- Always isolate runtime directories (`HOME`, config/data dirs).
- Assert both exit status and output.
- Include at least one negative-path test per command surface.
## Pattern 2: Sourced Bash Libraries
For libs, distinguish:
1. **Process-level assertions** (`run bash -c 'source ...'`)
2. **In-shell state assertions** (direct call, no `run`)
`run` executes in a subshell. Side effects on variables do **not** persist to the test shell.
```bash
#!/usr/bin/env bats
load './helpers/test_helper.bash'
setup() {
# shellcheck disable=SC1091
source "${BATS_TEST_DIRNAME}/../lib/string_utils.sh"
}
@test "library can be sourced cleanly" {
run bash -c 'source "./lib/string_utils.sh"'
assert_success
assert_output ""
}
@test "trim returns normalized value" {
run trim " hello "
assert_success
assert_output "hello"
}
@test "function can mutate caller state (non-run path)" {
value=" hello world "
trim_in_place value # this function edits variable by name
[ "$value" = "hello world" ]
}
```
### Notes
- Use `run` for output/status checks.
- Use direct invocation for in-shell state mutation tests.
- Source once in `setup` unless isolation requires per-test sourcing.
## Pattern 3: REST API Testing with Bats
Use helpers so each test focuses on intent.
```bash
#!/usr/bin/env bats
load './helpers/test_helper.bash'
request_json() {
local method="$1"; shift
local url="$1"; shift
local body_file="$BATS_TEST_TMPDIR/response.json"
HTTP_STATUS="$({
curl -sS \
-X "$method" \
-H 'Accept: application/json' \
-H 'Content-Type: application/json' \
-o "$body_file" \
-w '%{http_code}' \
"$url" "$@"
})"
HTTP_BODY="$(cat "$body_file")"
}
@test "GET /health is healthy" {
[ -n "${API_BASE_URL:-}" ] || skip "API_BASE_URL is required"
request_json GET "${API_BASE_URL%/}/health"
[ "$HTTP_STATUS" -eq 200 ]
echo "$HTTP_BODY" | jq -e '.status | IN("ok", "healthy", "up")'
}
@test "POST /users creates user" {
[ -n "${API_BASE_URL:-}" ] || skip "API_BASE_URL is required"
local email="[email protected]"
request_json POST "${API_BASE_URL%/}/users" \
--data "$(jq -nc --arg email "$email" '{name:"Bats User", email:$email}')"
[ "$HTTP_STATUS" -eq 201 ]
echo "$HTTP_BODY" | jq -e --arg email "$email" '.email == $email and .id != null'
}
```
### Notes
- Prefer `jq` over regex for JSON assertions.
- Generate unique test data to avoid collisions.
- For stateful APIs, add explicit cleanup calls or disposable environments.
## Common Mistakes
- **Parsing JSON with `grep` only** → brittle checks; use `jq -e`.
- **Only happy-path tests** → add negative-path assertions for each command/endpoint.
- **Using `run` for stateful sourced-function tests** → side effects disappear (subshell).
- **Leaking local machine state** (`HOME`, config dirs) → isolate with temp dirs.
## Quick Checklist
Before claiming tests are done:
- [ ] Exit code and output are both asserted
- [ ] At least one failure-path test exists
- [ ] Sourced-library tests include non-`run` state checks when relevant
- [ ] API JSON assertions use `jq`
- [ ] Test state is isolated and reproducible
This skill teaches how to write shell-native tests using Bats to verify real shell behavior: exit codes, stdout/stderr, sourced functions, and interactions with external commands or REST endpoints. It focuses on testing at the shell boundary so tests validate observable behavior rather than internal implementation. Practical patterns cover CLI end-to-end tests, sourced Bash library checks, and lightweight API tests driven from shell pipelines.
The skill provides patterns and helper conventions to run commands under test, capture exit status and output using Bats' run helper, and isolate runtime state with temporary directories. For sourced libraries, it shows when to invoke functions directly (to test in-shell mutation) versus using run (to test process-level exit/output). For REST APIs, it demonstrates a request_json helper that captures HTTP status and body and uses jq for reliable JSON assertions.
When should I source a library in setup versus inside each test?
Source once in setup if functions are pure and tests don't conflict. Source per-test when you need isolation or tests change global state that could affect others.
Why prefer jq over grep for JSON?
jq parses JSON structurally and fails on invalid JSON; grep is brittle and may pass or fail incorrectly when formatting changes.