# Testing

URL: /docs/usage/testing/
Section: usage
Tags: testing, snapshots, recording, replay

--------------------------------------------------------------------------------

Milo ships with testing utilities purpose-built for the Elm Architecture. Test reducers with action sequences, test views with snapshots, test sagas step-by-step, and record/replay entire sessions. Testing strategies flowchart TB subgraph Unit RS[assert_state] --> Reducer RN[assert_renders] --> Template SG[assert_saga] --> Saga end subgraph Integration Rec[recording_middleware] --> Session[JSONL Session] Session --> Replay[milo replay] end Replay -->|"--assert"| CI[CI Regression] Snapshot testing Render state through a template and compare to a snapshot file: from milo.testing import assert_renders assert_renders( {"count": 5, "label": "Total"}, "counter.kida", snapshot="tests/snapshots/counter_5.txt", ) On first run, the snapshot file is created. On subsequent runs, the output is compared to the stored snapshot. ANSI codes are stripped by default. Update snapshots CI mode MILO_UPDATE_SNAPSHOTS=1 pytest pytest # Fails if snapshots don't match Reducer testing Feed an action sequence through a reducer and assert the final state: from milo.testing import assert_state from milo import Action assert_state( reducer, None, # initial state [Action("@@INIT"), Action("INCREMENT"), Action("INCREMENT")], {"count": 2}, # expected final state ) Note Note assert_state replays actions synchronously — no event loop, no rendering, no sagas. This isolates the reducer logic for fast, deterministic tests. Saga testing Step through a saga generator, asserting each yielded effect: from milo.testing import assert_saga from milo import Call, Put, Action assert_saga( fetch_saga(), [ (Call(fetch_json, ("https://api.example.com",), {}), {"data": 42}), (Put(Action("DATA_LOADED", payload={"data": 42})), None), ], ) Each tuple is (expected_effect, value_to_send_back). The test runner asserts the yielded effect matches, then sends the value back into the generator. Session recording Record every action dispatched during an interactive session: Auto-path Custom path app = App(template="app.kida", reducer=reducer, initial_state=None, record=True) app.run() # Writes to session.jsonl app = App(template="app.kida", reducer=reducer, initial_state=None, record="my_session.jsonl") app.run() The recording middleware captures each action with a state hash in JSONL format. Session replay Replay a recorded session for debugging or CI regression testing: # Normal replay at 2x speed milo replay session.jsonl --speed 2.0 # Show state diffs between actions milo replay session.jsonl --diff # Step-by-step interactive replay milo replay session.jsonl --step # CI mode: assert state hashes match milo replay session.jsonl --assert --reducer myapp:reducer Warning Warning The --assert flag compares state hashes at each step against the recorded values. If you change your reducer logic, recorded sessions will fail hash checks — re-record affected sessions after intentional changes. File Text Recording format Sessions are stored as JSONL (one JSON object per line): {"seq": 0, "type": "@@INIT", "payload": null, "hash": "a1b2c3d4"} {"seq": 1, "type": "@@KEY", "payload": {"char": " ", "name": null, "ctrl": false}, "hash": "e5f6g7h8"} {"seq": 2, "type": "@@KEY", "payload": {"char": "r", "name": null, "ctrl": false}, "hash": "i9j0k1l2"} Each line includes a sequence number, the action, and a hash of the resulting state. This makes recordings both human-readable and machine-verifiable.

--------------------------------------------------------------------------------

Metadata:
- Author: lbliii
- Word Count: 440
- Reading Time: 2 minutes