diff --git a/.coveragerc b/.coveragerc new file mode 100644 index 00000000..26e44f99 --- /dev/null +++ b/.coveragerc @@ -0,0 +1,3 @@ +[run] +concurrency = multiprocessing,thread +source = optuna_dashboard/ diff --git a/.github/workflows/python-coverage.yml b/.github/workflows/python-coverage.yml new file mode 100644 index 00000000..4bda6350 --- /dev/null +++ b/.github/workflows/python-coverage.yml @@ -0,0 +1,48 @@ +name: python coverage + +on: + push: + branches: + - master + pull_request: {} + +jobs: + coverage: + runs-on: ubuntu-latest + + # Not intended for forks. + if: github.repository == 'optuna/optuna-dashboard' + + steps: + - name: Checkout + uses: actions/checkout@v3 + + - name: Setup Python + uses: actions/setup-python@v4 + with: + python-version: '3.10' + architecture: x64 + + - name: Install dependencies + run: | + python -m pip install --progress-bar off --upgrade pip setuptools + pip install --progress-bar off .[optional] + pip install --progress-bar off .[test] + pip install --progress-bar off "optuna>=3.0.0" + pip install --progress-bar off . + echo 'import coverage; coverage.process_startup()' > sitecustomize.py + - name: Tests + env: + PYTHONPATH: . # To invoke sitecutomize.py + COVERAGE_PROCESS_START: .coveragerc # https://coverage.readthedocs.io/en/6.4.1/subprocess.html + COVERAGE_COVERAGE: yes # https://github.com/nedbat/coveragepy/blob/65bf33fc03209ffb01bbbc0d900017614645ee7a/coverage/control.py#L255-L261 + run: | + coverage run --source=optuna_dashboard -m pytest python_tests + coverage combine + coverage xml + - name: Upload coverage to Codecov + uses: codecov/codecov-action@v3 + with: + token: ${{ secrets.CODECOV_TOKEN }} + file: ./coverage.xml + fail_ci_if_error: true diff --git a/.github/workflows/python-tests.yml b/.github/workflows/python-tests.yml index 612ddb59..8fee4e44 100644 --- a/.github/workflows/python-tests.yml +++ b/.github/workflows/python-tests.yml @@ -45,7 +45,8 @@ jobs: # python_tests requires optuna>=3.0.0 since it imports FloatDistribution run: | python -m pip install --progress-bar off --upgrade pip setuptools - pip install streamlit boto3 moto[s3] pytest + pip install --progress-bar off .[optional] + pip install --progress-bar off .[test] pip install --progress-bar off "optuna>=3.0.0" pip install --progress-bar off . - run: pytest python_tests @@ -61,7 +62,8 @@ jobs: - name: Install dependencies run: | python -m pip install --progress-bar off --upgrade pip setuptools - pip install streamlit boto3 moto[s3] pytest + pip install --progress-bar off .[optional] + pip install --progress-bar off .[test] pip install --progress-bar off . python -m pip install --progress-bar off --upgrade git+https://github.com/optuna/optuna.git - run: pytest python_tests diff --git a/.gitignore b/.gitignore index 50ea6367..49c137e0 100644 --- a/.gitignore +++ b/.gitignore @@ -28,6 +28,11 @@ docs/_generated/ rustlib/target/ rustlib/pkg/ +# Test +.coverage +.coverage.* +coverage.xml + # Others .envrc .idea/ diff --git a/Makefile b/Makefile index f925bb78..4094fd57 100644 --- a/Makefile +++ b/Makefile @@ -45,7 +45,7 @@ docs: docs/conf.py $(RST_FILES) .PHONY: fmt fmt: npm run fmt - black ./optuna_dashboard/ ./python_tests/ + black ./optuna_dashboard/ ./python_tests/ ./e2e_tests/ isort . .PHONY: clean diff --git a/e2e_tests/__init__.py b/e2e_tests/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/e2e_tests/conftest.py b/e2e_tests/conftest.py index 8d8eac3b..ad1190cb 100644 --- a/e2e_tests/conftest.py +++ b/e2e_tests/conftest.py @@ -1,251 +1,6 @@ -import socket -import threading -from wsgiref.simple_server import make_server - -import optuna -from optuna_dashboard import wsgi import pytest -study_names = [ - "single", - "single-trial", - "single-1-param", - "single-dynamic", - "single-inf", - "multi-objective", - "multi-dynamic", - "single-pruned-without-report", - "single-inf-report", - "issue-410", - "single-no-trials", - "multi-no-trials", -] - - -def make_dummy_storage(study_name: str) -> optuna.storages.InMemoryStorage: - storage = optuna.storages.InMemoryStorage() - sampler = optuna.samplers.RandomSampler(seed=0) - - # Sinble objective study - if study_name == "single": - study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - def objective_single(trial: optuna.Trial) -> float: - x1 = trial.suggest_float("x1", 0, 10) - x2 = trial.suggest_float("x2", 0, 10) - return (x1 - 2) ** 2 + (x2 - 5) ** 2 - - study.optimize(objective_single, n_trials=50) - - # A single objective study with a single trial - # Refs: https://github.com/optuna/optuna-dashboard/issues/401 - elif study_name == "single-trial": - study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - def objective_single(trial: optuna.Trial) -> float: - x1 = trial.suggest_float("x1", 0, 10) - x2 = trial.suggest_float("x2", 0, 10) - return (x1 - 2) ** 2 + (x2 - 5) ** 2 - - study.optimize(objective_single, n_trials=1) - - # Single-objective study with 1 parameter - elif study_name == "single-1-param": - study = optuna.create_study( - study_name=study_name, storage=storage, direction="maximize", sampler=sampler - ) - - def objective_single_with_1param(trial: optuna.Trial) -> float: - x1 = trial.suggest_float("x1", 0, 10) - return -((x1 - 2) ** 2) - - study.optimize(objective_single_with_1param, n_trials=50) - - # Single-objective study with dynamic search space - elif study_name == "single-dynamic": - study = optuna.create_study( - study_name=study_name, storage=storage, direction="maximize", sampler=sampler - ) - - def objective_single_dynamic(trial: optuna.Trial) -> float: - category = trial.suggest_categorical("category", ["foo", "bar"]) - if category == "foo": - return (trial.suggest_float("x1", 0, 10) - 2) ** 2 - else: - return -((trial.suggest_float("x2", -10, 0) + 5) ** 2) - - study.optimize(objective_single_dynamic, n_trials=50) - - # Single objective study with 'inf', '-inf', or 'nan' value - elif study_name == "single-inf": - study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - def objective_single_inf(trial: optuna.Trial) -> float: - x = trial.suggest_float("x", -10, 10) - if trial.number % 3 == 0: - return float("inf") - elif trial.number % 3 == 1: - return float("-inf") - else: - return x**2 - - study.optimize(objective_single_inf, n_trials=50) - - # Multi-objective study - elif study_name == "multi-objective": - study = optuna.create_study( - study_name=study_name, - storage=storage, - directions=["minimize", "minimize"], - sampler=sampler, - ) - - def objective_multi(trial: optuna.Trial) -> tuple[float, float]: - x = trial.suggest_float("x", 0, 5) - y = trial.suggest_float("y", 0, 3) - v0 = 4 * x**2 + 4 * y**2 - v1 = (x - 5) ** 2 + (y - 5) ** 2 - return v0, v1 - - study.optimize(objective_multi, n_trials=50) - - # Multi-objective study with dynamic search space - elif study_name == "multi-dynamic": - study = optuna.create_study( - study_name=study_name, - storage=storage, - directions=["minimize", "minimize"], - sampler=sampler, - ) - - def objective_multi_dynamic(trial: optuna.Trial) -> tuple[float, float]: - category = trial.suggest_categorical("category", ["foo", "bar"]) - if category == "foo": - x = trial.suggest_float("x1", 0, 5) - y = trial.suggest_float("y1", 0, 3) - v0 = 4 * x**2 + 4 * y**2 - v1 = (x - 5) ** 2 + (y - 5) ** 2 - return v0, v1 - else: - x = trial.suggest_float("x2", 0, 5) - y = trial.suggest_float("y2", 0, 3) - v0 = 2 * x**2 + 2 * y**2 - v1 = (x - 2) ** 2 + (y - 3) ** 2 - return v0, v1 - - study.optimize(objective_multi_dynamic, n_trials=50) - - # Pruning with no intermediate values - elif study_name == "single-pruned-without-report": - study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - def objective_prune_without_report(trial: optuna.Trial) -> float: - x = trial.suggest_float("x", -15, 30) - y = trial.suggest_float("y", -15, 30) - v = x**2 + y**2 - if v > 100: - raise optuna.TrialPruned() - return v - - study.optimize(objective_prune_without_report, n_trials=100) - - # Single objective pruned after reported 'inf', '-inf', or 'nan' - elif study_name == "single-inf-report": - study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - def objective_single_inf_report(trial: optuna.Trial) -> float: - x = trial.suggest_float("x", -10, 10) - if trial.number % 3 == 0: - trial.report(float("inf"), 1) - elif trial.number % 3 == 1: - trial.report(float("-inf"), 1) - else: - trial.report(float("nan"), 1) - - if x > 0: - raise optuna.TrialPruned() - else: - return x**2 - - study.optimize(objective_single_inf_report, n_trials=50) - - # Issue 410 - elif study_name == "issue-410": - study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - def objective_issue_410(trial: optuna.Trial) -> float: - trial.suggest_categorical("resample_rate", ["50ms"]) - trial.suggest_categorical("channels", ["all"]) - trial.suggest_categorical("window_size", [256]) - if trial.number > 15: - raise Exception("Unexpected error") - trial.suggest_categorical("cbow", [True]) - trial.suggest_categorical("model", ["m1"]) - - trial.set_user_attr("epochs", 0) - trial.set_user_attr("deterministic", True) - if trial.number > 10: - raise Exception("unexpeccted error") - trial.set_user_attr("folder", "/path/to/folder") - trial.set_user_attr("resample_type", "foo") - trial.set_user_attr("run_id", "0001") - return 1.0 - - study.optimize(objective_issue_410, n_trials=20, catch=(Exception,)) - - # No trials single-objective study - elif study_name == "single-no-trials": - optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - # No trials multi-objective study - elif study_name == "multi-no-trials": - optuna.create_study( - study_name=study_name, - storage=storage, - directions=["minimize", "maximize"], - sampler=sampler, - ) - else: - assert False, f"No study configuration of {study_name} in conftest.py" - - return storage - - -def get_free_port() -> int: - tcp = socket.socket(socket.AF_INET, socket.SOCK_STREAM) - tcp.bind(("", 0)) - _, port = tcp.getsockname() - tcp.close() - return port - - -@pytest.fixture(scope="session", params=study_names) -def storage(request: pytest.FixtureRequest) -> optuna.storages.InMemoryStorage: - study_name = request.param - storage = make_dummy_storage(study_name) - return storage - - -@pytest.fixture(scope="session") -def server_url(request: pytest.FixtureRequest, storage: optuna.storages.InMemoryStorage) -> str: - addr = "127.0.0.1" - port = get_free_port() - app = wsgi(storage) - httpd = make_server(addr, port, app) - thread = threading.Thread(target=httpd.serve_forever) - thread.start() - - def stop_server() -> None: - httpd.shutdown() - httpd.server_close() - thread.join() - - request.addfinalizer(stop_server) - - return f"http://{addr}:{port}/dashboard" - - @pytest.fixture(scope="session") def browser_context_args(browser_context_args: dict) -> dict: return { diff --git a/e2e_tests/test_server.py b/e2e_tests/test_server.py new file mode 100644 index 00000000..b6d14734 --- /dev/null +++ b/e2e_tests/test_server.py @@ -0,0 +1,35 @@ +import socket +import threading +from wsgiref.simple_server import make_server + +import optuna +from optuna_dashboard import wsgi +import pytest + + +def get_free_port() -> int: + tcp = socket.socket(socket.AF_INET, socket.SOCK_STREAM) + tcp.bind(("", 0)) + _, port = tcp.getsockname() + tcp.close() + return port + + +def make_test_server( + request: pytest.FixtureRequest, storage: optuna.storages.InMemoryStorage +) -> str: + addr = "127.0.0.1" + port = get_free_port() + app = wsgi(storage) + httpd = make_server(addr, port, app) + thread = threading.Thread(target=httpd.serve_forever) + thread.start() + + def stop_server() -> None: + httpd.shutdown() + httpd.server_close() + thread.join() + + request.addfinalizer(stop_server) + + return f"http://{addr}:{port}/dashboard" diff --git a/e2e_tests/test_usecases/__init__.py b/e2e_tests/test_usecases/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/e2e_tests/test_usecases/test_study_history.py b/e2e_tests/test_usecases/test_study_history.py index f34d35e6..e37b8f5a 100644 --- a/e2e_tests/test_usecases/test_study_history.py +++ b/e2e_tests/test_usecases/test_study_history.py @@ -1,5 +1,35 @@ import optuna from playwright.sync_api import Page +import pytest + +from ..test_server import make_test_server + + +def make_test_storage() -> optuna.storages.InMemoryStorage: + storage = optuna.storages.InMemoryStorage() + sampler = optuna.samplers.RandomSampler(seed=0) + + study = optuna.create_study(study_name="single", storage=storage, sampler=sampler) + + def objective_single(trial: optuna.Trial) -> float: + x1 = trial.suggest_float("x1", 0, 10) + x2 = trial.suggest_float("x2", 0, 10) + return (x1 - 2) ** 2 + (x2 - 5) ** 2 + + study.optimize(objective_single, n_trials=50) + + return storage + + +@pytest.fixture +def storage() -> optuna.storages.InMemoryStorage: + storage = make_test_storage() + return storage + + +@pytest.fixture +def server_url(request: pytest.FixtureRequest, storage: optuna.storages.InMemoryStorage) -> str: + return make_test_server(request, storage) def test_history_xaxis_click( diff --git a/e2e_tests/visual_regression_test.py b/e2e_tests/visual_regression_test.py index 706ec2f3..d83fbb5f 100644 --- a/e2e_tests/visual_regression_test.py +++ b/e2e_tests/visual_regression_test.py @@ -1,15 +1,274 @@ +from typing import Callable + import optuna from playwright.sync_api import Page +import pytest + +from .test_server import make_test_server +@pytest.fixture +def storage() -> optuna.storages.InMemoryStorage: + storage = optuna.storages.InMemoryStorage() + return storage + + +@pytest.fixture +def server_url(request: pytest.FixtureRequest, storage: optuna.storages.InMemoryStorage) -> str: + return make_test_server(request, storage) + + +def run_single_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study(study_name="single", storage=storage, sampler=sampler) + + def objective(trial: optuna.Trial) -> float: + x1 = trial.suggest_float("x1", 0, 10) + x2 = trial.suggest_float("x2", 0, 10) + return (x1 - 2) ** 2 + (x2 - 5) ** 2 + + study.optimize(objective, n_trials=50) + return study + + +def run_single_trial_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + # A single objective study with a single trial + # Refs: https://github.com/optuna/optuna-dashboard/issues/401 + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study(study_name="single-trial", storage=storage, sampler=sampler) + + def objective(trial: optuna.Trial) -> float: + x1 = trial.suggest_float("x1", 0, 10) + x2 = trial.suggest_float("x2", 0, 10) + return (x1 - 2) ** 2 + (x2 - 5) ** 2 + + study.optimize(objective, n_trials=1) + return study + + +def run_single_1param_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study( + study_name="single-1-param", storage=storage, direction="maximize", sampler=sampler + ) + + def objective(trial: optuna.Trial) -> float: + x1 = trial.suggest_float("x1", 0, 10) + return -((x1 - 2) ** 2) + + study.optimize(objective, n_trials=50) + return study + + +def run_single_dynamic_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + # Single-objective study with dynamic search space + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study( + study_name="single-dynamic", storage=storage, direction="maximize", sampler=sampler + ) + + def objective(trial: optuna.Trial) -> float: + category = trial.suggest_categorical("category", ["foo", "bar"]) + if category == "foo": + return (trial.suggest_float("x1", 0, 10) - 2) ** 2 + else: + return -((trial.suggest_float("x2", -10, 0) + 5) ** 2) + + study.optimize(objective, n_trials=50) + return study + + +def run_single_inf_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + # Single objective study with 'inf', '-inf', or 'nan' value + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study(study_name="single-inf", storage=storage, sampler=sampler) + + def objective(trial: optuna.Trial) -> float: + x = trial.suggest_float("x", -10, 10) + if trial.number % 3 == 0: + return float("inf") + elif trial.number % 3 == 1: + return float("-inf") + else: + return x**2 + + study.optimize(objective, n_trials=50) + return study + + +def run_multi_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + # Multi-objective study + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study( + study_name="multi-objective", + storage=storage, + directions=["minimize", "minimize"], + sampler=sampler, + ) + + def objective(trial: optuna.Trial) -> tuple[float, float]: + x = trial.suggest_float("x", 0, 5) + y = trial.suggest_float("y", 0, 3) + v0 = 4 * x**2 + 4 * y**2 + v1 = (x - 5) ** 2 + (y - 5) ** 2 + return v0, v1 + + study.optimize(objective, n_trials=50) + return study + + +def run_multi_dynamic_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + # Multi-objective study with dynamic search space + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study( + study_name="multi-dynamic", + storage=storage, + directions=["minimize", "minimize"], + sampler=sampler, + ) + + def objective(trial: optuna.Trial) -> tuple[float, float]: + category = trial.suggest_categorical("category", ["foo", "bar"]) + if category == "foo": + x = trial.suggest_float("x1", 0, 5) + y = trial.suggest_float("y1", 0, 3) + v0 = 4 * x**2 + 4 * y**2 + v1 = (x - 5) ** 2 + (y - 5) ** 2 + return v0, v1 + else: + x = trial.suggest_float("x2", 0, 5) + y = trial.suggest_float("y2", 0, 3) + v0 = 2 * x**2 + 2 * y**2 + v1 = (x - 2) ** 2 + (y - 3) ** 2 + return v0, v1 + + study.optimize(objective, n_trials=50) + return study + + +def run_single_pruned_without_report_objective_study( + storage: optuna.storages.InMemoryStorage, +) -> optuna.Study: + # Pruning with no intermediate values + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study( + study_name="single-pruned-without-report", storage=storage, sampler=sampler + ) + + def objective(trial: optuna.Trial) -> float: + x = trial.suggest_float("x", -15, 30) + y = trial.suggest_float("y", -15, 30) + v = x**2 + y**2 + if v > 100: + raise optuna.TrialPruned() + return v + + study.optimize(objective, n_trials=100) + return study + + +def run_single_inf_report_objective_study( + storage: optuna.storages.InMemoryStorage, +) -> optuna.Study: + # Single objective pruned after reported 'inf', '-inf', or 'nan' + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study(study_name="single-inf-report", storage=storage, sampler=sampler) + + def objective(trial: optuna.Trial) -> float: + x = trial.suggest_float("x", -10, 10) + if trial.number % 3 == 0: + trial.report(float("inf"), 1) + elif trial.number % 3 == 1: + trial.report(float("-inf"), 1) + else: + trial.report(float("nan"), 1) + + if x > 0: + raise optuna.TrialPruned() + else: + return x**2 + + study.optimize(objective, n_trials=50) + return study + + +def run_issue_410_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + # Issue 410 + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study(study_name="issue-410", storage=storage, sampler=sampler) + + def objective(trial: optuna.Trial) -> float: + trial.suggest_categorical("resample_rate", ["50ms"]) + trial.suggest_categorical("channels", ["all"]) + trial.suggest_categorical("window_size", [256]) + if trial.number > 15: + raise Exception("Unexpected error") + trial.suggest_categorical("cbow", [True]) + trial.suggest_categorical("model", ["m1"]) + + trial.set_user_attr("epochs", 0) + trial.set_user_attr("deterministic", True) + if trial.number > 10: + raise Exception("unexpeccted error") + trial.set_user_attr("folder", "/path/to/folder") + trial.set_user_attr("resample_type", "foo") + trial.set_user_attr("run_id", "0001") + return 1.0 + + study.optimize(objective, n_trials=20, catch=(Exception,)) + return study + + +def run_single_no_trials_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + # No trials single-objective study + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study(study_name="single-no-trials", storage=storage, sampler=sampler) + + return study + + +def run_multi_no_trials_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + # No trials multi-objective study + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study( + study_name="multi-no-trials", + storage=storage, + directions=["minimize", "maximize"], + sampler=sampler, + ) + return study + + +parameterize_studies = pytest.mark.parametrize( + "run_study", + [ + run_single_objective_study, + run_single_trial_objective_study, + run_single_1param_objective_study, + run_single_dynamic_objective_study, + run_single_inf_objective_study, + run_multi_objective_study, + run_multi_dynamic_objective_study, + run_single_pruned_without_report_objective_study, + run_single_inf_report_objective_study, + run_issue_410_objective_study, + run_single_no_trials_objective_study, + run_multi_no_trials_objective_study, + ], +) + + +@parameterize_studies def test_study_list( page: Page, storage: optuna.storages.InMemoryStorage, server_url: str, + run_study: Callable[[optuna.storages.InMemoryStorage], optuna.Study], ) -> None: - summaries = optuna.get_all_study_summaries(storage) - study_id = summaries[0]._study_id - study_name = summaries[0].study_name + study = run_study(storage) + + study_id = study._study_id + study_name = study.study_name page.goto(server_url) page.click(f"a[href='/dashboard/studies/{study_id}']") @@ -22,14 +281,17 @@ def test_study_list( assert study_name in title +@parameterize_studies def test_study_analytics( page: Page, storage: optuna.storages.InMemoryStorage, server_url: str, + run_study: Callable[[optuna.storages.InMemoryStorage], optuna.Study], ) -> None: - summaries = optuna.get_all_study_summaries(storage) - study_id = summaries[0]._study_id - study_name = summaries[0].study_name + study = run_study(storage) + + study_id = study._study_id + study_name = study.study_name url = f"{server_url}/studies/{study_id}" page.goto(url) @@ -43,14 +305,17 @@ def test_study_analytics( assert study_name in title +@parameterize_studies def test_trial_list( page: Page, storage: optuna.storages.InMemoryStorage, server_url: str, + run_study: Callable[[optuna.storages.InMemoryStorage], optuna.Study], ) -> None: - summaries = optuna.get_all_study_summaries(storage) - study_id = summaries[0]._study_id - study_name = summaries[0].study_name + study = run_study(storage) + + study_id = study._study_id + study_name = study.study_name url = f"{server_url}/studies/{study_id}" page.goto(url) @@ -64,14 +329,17 @@ def test_trial_list( assert study_name in title +@parameterize_studies def test_trial_table( page: Page, storage: optuna.storages.InMemoryStorage, server_url: str, + run_study: Callable[[optuna.storages.InMemoryStorage], optuna.Study], ) -> None: - summaries = optuna.get_all_study_summaries(storage) - study_id = summaries[0]._study_id - study_name = summaries[0].study_name + study = run_study(storage) + + study_id = study._study_id + study_name = study.study_name url = f"{server_url}/studies/{study_id}" page.goto(url) @@ -85,14 +353,17 @@ def test_trial_table( assert study_name in title +@parameterize_studies def test_trial_note( page: Page, storage: optuna.storages.InMemoryStorage, server_url: str, + run_study: Callable[[optuna.storages.InMemoryStorage], optuna.Study], ) -> None: - summaries = optuna.get_all_study_summaries(storage) - study_id = summaries[0]._study_id - study_name = summaries[0].study_name + study = run_study(storage) + + study_id = study._study_id + study_name = study.study_name url = f"{server_url}/studies/{study_id}" page.goto(url) diff --git a/pyproject.toml b/pyproject.toml index d9c0082c..0555f701 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -41,6 +41,18 @@ docs = [ "sphinx_rtd_theme", ] +test = [ + "coverage", + "pytest", + "moto[s3]", +] + +optional = [ + "streamlit", + "boto3", +] + + [project.scripts] optuna-dashboard = "optuna_dashboard._cli:main"