MAINT: Pytest refactoring

src/zipline/examples/dual_ema_talib.py

@@ -23,7 +23,7 @@
 momentum).
 
 """
-
+import os
 from zipline.api import order, record, symbol
 from zipline.finance import commission, slippage
 
@@ -127,6 +127,9 @@ def analyze(context=None, results=None):
 
     plt.show()
 
+    if "PYTEST_CURRENT_TEST" in os.environ:
+        plt.close("all")
+
 
 def _test_args():
     """Extra arguments to use when zipline's automated tests run this example."""

src/zipline/examples/dual_moving_average.py

@@ -21,7 +21,7 @@
 its shares once the averages cross again (indicating downwards
 momentum).
 """
-
+import os
 from zipline.api import order_target, record, symbol
 from zipline.finance import commission, slippage
 
@@ -114,6 +114,9 @@ def analyze(context=None, results=None):
 
     plt.show()
 
+    if "PYTEST_CURRENT_TEST" in os.environ:
+        plt.close("all")
+
 
 def _test_args():
     """Extra arguments to use when zipline's automated tests run this example."""

src/zipline/testing/core.py

@@ -129,7 +129,9 @@ def assert_single_position(test, zipline):
             test.zipline_test_config["expected_transactions"], transaction_count
         )
     else:
-        test.assertEqual(test.zipline_test_config["order_count"], transaction_count)
+        test.assertEqual(
+            test.zipline_test_config["order_count"], transaction_count
+        )
 
     # the final message is the risk report, the second to
     # last is the final day's results. Positions is a list of
@@ -149,7 +151,9 @@ def assert_single_position(test, zipline):
     for order in orders_by_id.value():
         test.assertEqual(order["status"], ORDER_STATUS.FILLED, "")
 
-    test.assertEqual(len(closing_positions), 1, "Portfolio should have one position.")
+    test.assertEqual(
+        len(closing_positions), 1, "Portfolio should have one position."
+    )
 
     sid = test.zipline_test_config["sid"]
     test.assertEqual(
@@ -181,7 +185,8 @@ def security_list_copy():
 def add_security_data(adds, deletes):
     if not hasattr(security_list, "using_copy"):
         raise Exception(
-            "add_security_data must be used within " "security_list_copy context"
+            "add_security_data must be used within "
+            "security_list_copy context"
         )
     directory = os.path.join(
         security_list.SECURITY_LISTS_DIR, "leveraged_etf_list/20150127/20150125"
@@ -270,7 +275,9 @@ def make_trade_data_for_asset_info(
     sids = asset_info.index
 
     price_sid_deltas = np.arange(len(sids), dtype=float64) * price_step_by_sid
-    price_date_deltas = np.arange(len(dates), dtype=float64) * price_step_by_date
+    price_date_deltas = (
+        np.arange(len(dates), dtype=float64) * price_step_by_date
+    )
     prices = (price_sid_deltas + as_column(price_date_deltas)) + price_start
 
     volume_sid_deltas = np.arange(len(sids)) * volume_step_by_sid
@@ -301,7 +308,9 @@ def make_trade_data_for_asset_info(
     return trade_data
 
 
-def check_allclose(actual, desired, rtol=1e-07, atol=0, err_msg="", verbose=True):
+def check_allclose(
+    actual, desired, rtol=1e-07, atol=0, err_msg="", verbose=True
+):
     """
     Wrapper around np.testing.assert_allclose that also verifies that inputs
     are ndarrays.
@@ -439,10 +448,17 @@ def write_daily_data(tempdir, sim_params, sids, trading_calendar):
 
 
 def create_data_portal(
-    asset_finder, tempdir, sim_params, sids, trading_calendar, adjustment_reader=None
+    asset_finder,
+    tempdir,
+    sim_params,
+    sids,
+    trading_calendar,
+    adjustment_reader=None,
 ):
     if sim_params.data_frequency == "daily":
-        daily_path = write_daily_data(tempdir, sim_params, sids, trading_calendar)
+        daily_path = write_daily_data(
+            tempdir, sim_params, sids, trading_calendar
+        )
 
         equity_daily_reader = BcolzDailyBarReader(daily_path)
 
@@ -458,7 +474,9 @@ def create_data_portal(
             sim_params.first_open, sim_params.last_close
         )
 
-        minute_path = write_minute_data(trading_calendar, tempdir, minutes, sids)
+        minute_path = write_minute_data(
+            trading_calendar, tempdir, minutes, sids
+        )
 
         equity_minute_reader = BcolzMinuteBarReader(minute_path)
 
@@ -478,9 +496,16 @@ def write_bcolz_minute_data(trading_calendar, days, path, data):
 
 
 def create_minute_df_for_asset(
-    trading_calendar, start_dt, end_dt, interval=1, start_val=1, minute_blacklist=None
+    trading_calendar,
+    start_dt,
+    end_dt,
+    interval=1,
+    start_val=1,
+    minute_blacklist=None,
 ):
-    asset_minutes = trading_calendar.minutes_for_sessions_in_range(start_dt, end_dt)
+    asset_minutes = trading_calendar.minutes_for_sessions_in_range(
+        start_dt, end_dt
+    )
     minutes_count = len(asset_minutes)
 
     if interval > 1:
@@ -579,7 +604,10 @@ def create_data_portal_from_trade_history(
     if sim_params.data_frequency == "daily":
         path = os.path.join(tempdir.path, "testdaily.bcolz")
         writer = BcolzDailyBarWriter(
-            path, trading_calendar, sim_params.start_session, sim_params.end_session
+            path,
+            trading_calendar,
+            sim_params.start_session,
+            sim_params.end_session,
         )
         writer.write(
             trades_by_sid_to_dfs(trades_by_sid, sim_params.sessions),
@@ -644,7 +672,9 @@ def create_data_portal_from_trade_history(
 
 
 class FakeDataPortal(DataPortal):
-    def __init__(self, asset_finder, trading_calendar=None, first_trading_day=None):
+    def __init__(
+        self, asset_finder, trading_calendar=None, first_trading_day=None
+    ):
         if trading_calendar is None:
             trading_calendar = get_calendar("NYSE")
 
@@ -665,7 +695,14 @@ def get_scalar_asset_spot_value(self, asset, field, dt, data_frequency):
             return 1.0
 
     def get_history_window(
-        self, assets, end_dt, bar_count, frequency, field, data_frequency, ffill=True
+        self,
+        assets,
+        end_dt,
+        bar_count,
+        frequency,
+        field,
+        data_frequency,
+        ffill=True,
     ):
         end_idx = self.trading_calendar.all_sessions.searchsorted(end_dt)
         days = self.trading_calendar.all_sessions[
@@ -712,7 +749,9 @@ def get_spot_value(self, asset, field, dt, data_frequency):
     # XXX: These aren't actually the methods that are used by the superclasses,
     # so these don't do anything, and this class will likely produce unexpected
     # results for history().
-    def _get_daily_window_for_sid(self, asset, field, days_in_window, extra_slot=True):
+    def _get_daily_window_for_sid(
+        self, asset, field, days_in_window, extra_slot=True
+    ):
         return np.arange(days_in_window, dtype=np.float64)
 
     def _get_minute_window_for_asset(self, asset, field, minutes_for_window):
@@ -740,7 +779,9 @@ class tmp_assets_db(object):
 
     _default_equities = sentinel("_default_equities")
 
-    def __init__(self, url="sqlite:///:memory:", equities=_default_equities, **frames):
+    def __init__(
+        self, url="sqlite:///:memory:", equities=_default_equities, **frames
+    ):
         self._url = url
         self._eng = None
         if equities is self._default_equities:
@@ -1326,14 +1367,16 @@ def read_compressed(path):
         return f.read()
 
 
-zipline_git_root = abspath(
-    join(realpath(dirname(__file__)), "..", ".."),
+zipline_reloaded_git_root = abspath(
+    join(realpath(dirname(__file__)), "..", "..", ".."),
 )
 
 
 # @nottest
 def test_resource_path(*path_parts):
-    return os.path.join(zipline_git_root, "tests", "resources", *path_parts)
+    return os.path.join(
+        zipline_reloaded_git_root, "tests", "resources", *path_parts
+    )
 
 
 @contextmanager
@@ -1672,7 +1715,9 @@ def simulate_minutes_for_day(
 
     min_ = min(close, open_)
     where = values < min_
-    values[where] = (values[where] - min_) * (low - min_) / (values.min() - min_) + min_
+    values[where] = (values[where] - min_) * (low - min_) / (
+        values.min() - min_
+    ) + min_
 
     if not (np.allclose(values.max(), high) and np.allclose(values.min(), low)):
         return simulate_minutes_for_day(
@@ -1757,7 +1802,10 @@ def exchange_info_for_domains(domains):
     """
     return pd.DataFrame.from_records(
         [
-            {"exchange": domain.calendar.name, "country_code": domain.country_code}
+            {
+                "exchange": domain.calendar.name,
+                "country_code": domain.country_code,
+            }
             for domain in domains
         ]
     )

tests/pipeline/test_domain.py

@@ -64,7 +64,7 @@
 )
 from zipline.pipeline.factors import CustomFactor
 import zipline.testing.fixtures as zf
-from zipline.testing.core import parameter_space, powerset
+from zipline.testing.core import powerset
 from zipline.testing.predicates import assert_equal, assert_messages_equal
 from zipline.utils.pandas_utils import days_at_time
 import pytest
@@ -117,8 +117,8 @@ def run(ts):
             assert_equal(result, expected)
 
 
-class SpecializeTestCase(zf.ZiplineTestCase):
-    @parameter_space(domain=BUILT_IN_DOMAINS)
+class TestSpecialize:
+    @pytest.mark.parametrize("domain", BUILT_IN_DOMAINS)
     def test_specialize(self, domain):
         class MyData(DataSet):
             col1 = Column(dtype=float)
@@ -166,7 +166,7 @@ def do_checks(cls, colnames):
         do_checks(MyData, ["col1", "col2", "col3"])
         do_checks(MyDataSubclass, ["col1", "col2", "col3", "col4"])
 
-    @parameter_space(domain=BUILT_IN_DOMAINS)
+    @pytest.mark.parametrize("domain", BUILT_IN_DOMAINS)
     def test_unspecialize(self, domain):
         class MyData(DataSet):
             col1 = Column(dtype=float)
@@ -197,7 +197,7 @@ def do_checks(cls, colnames):
         do_checks(MyData, ["col1", "col2", "col3"])
         do_checks(MyDataSubclass, ["col1", "col2", "col3", "col4"])
 
-    @parameter_space(domain_param=[BE_EQUITIES, CA_EQUITIES, CH_EQUITIES])
+    @pytest.mark.parametrize("domain_param", [BE_EQUITIES, CA_EQUITIES, CH_EQUITIES])
     def test_specialized_root(self, domain_param):
         different_domain = GB_EQUITIES
 
@@ -253,7 +253,7 @@ class D(DataSet):
     c3 = Column(object)
 
 
-class InferDomainTestCase(zf.ZiplineTestCase):
+class TestInferDomain:
     def check(self, inputs, expected):
         result = infer_domain(inputs)
         assert result is expected
@@ -274,15 +274,15 @@ def test_all_generic(self):
         self.check([D.c1, D.c2, D.c3], GENERIC)
         self.check([D.c1.latest, D.c2.latest, D.c3.latest], GENERIC)
 
-    @parameter_space(domain=[US_EQUITIES, GB_EQUITIES])
+    @pytest.mark.parametrize("domain", [US_EQUITIES, GB_EQUITIES])
     def test_all_non_generic(self, domain):
         D_s = D.specialize(domain)
         self.check([D_s.c1], domain)
         self.check([D_s.c1, D_s.c2], domain)
         self.check([D_s.c1, D_s.c2, D_s.c3], domain)
         self.check([D_s.c1, D_s.c2, D_s.c3.latest], domain)
 
-    @parameter_space(domain=[US_EQUITIES, GB_EQUITIES])
+    @pytest.mark.parametrize("domain", [US_EQUITIES, GB_EQUITIES])
     def test_mix_generic_and_specialized(self, domain):
         D_s = D.specialize(domain)
         self.check([D.c1, D_s.c3], domain)
@@ -332,7 +332,7 @@ def test_ambiguous_domain_repr(self):
         assert_messages_equal(result, expected)
 
 
-class DataQueryCutoffForSessionTestCase(zf.ZiplineTestCase):
+class TestDataQueryCutoffForSession:
     def test_generic(self):
         sessions = pd.date_range("2014-01-01", "2014-06-01")
         with pytest.raises(NotImplementedError):
@@ -441,7 +441,7 @@ def test_equity_calendar_domain(self):
             expected_cutoff_date_offset=-7,
         )
 
-    @parameter_space(domain=BUILT_IN_DOMAINS)
+    @pytest.mark.parametrize("domain", BUILT_IN_DOMAINS)
     def test_equity_calendar_not_aligned(self, domain):
         valid_sessions = domain.all_sessions()[:50]
         sessions = pd.date_range(valid_sessions[0], valid_sessions[-1])
@@ -457,8 +457,9 @@ def test_equity_calendar_not_aligned(self, domain):
 
     Case = namedtuple("Case", "time date_offset expected_timedelta")
 
-    @parameter_space(
-        parameters=(
+    @pytest.mark.parametrize(
+        "parameters",
+        (
             Case(
                 time=datetime.time(8, 45, tzinfo=pytz.utc),
                 date_offset=0,
@@ -496,7 +497,7 @@ def test_equity_calendar_not_aligned(self, domain):
                     ["4 hours 30 minutes"] * 93 + ["3 hours 30 minutes"] * 60,
                 ),
             ),
-        )
+        ),
     )
     def test_equity_session_domain(self, parameters):
         time, date_offset, expected_timedelta = parameters
@@ -519,7 +520,7 @@ def test_equity_session_domain(self, parameters):
         assert_equal(expected, actual)
 
 
-class RollForwardTestCase(zf.ZiplineTestCase):
+class TestRollForward:
     def test_roll_forward(self):
         #     January 2017
         # Su Mo Tu We Th Fr Sa
@@ -557,8 +558,8 @@ def test_roll_forward(self):
 
         expected_msg = (
             f"Date {after_last_session.date()} was past the last session "
-            "for domain EquityCalendarDomain('JP', 'XTKS'). "
-            f"The last session for this domain is {JP_EQUITIES.calendar.last_session.date()}."
+            "for domain EquityCalendarDomain('JP', 'XTKS'). The last session for "
+            f"this domain is {JP_EQUITIES.calendar.last_session.date()}."
         )
         with pytest.raises(ValueError, match=re.escape(expected_msg)):
             JP_EQUITIES.roll_forward(after_last_session)
@@ -580,6 +581,6 @@ def test_roll_forward(self):
         )
 
 
-class ReprTestCase(zf.ZiplineTestCase):
+class TestRepr:
     def test_generic_domain_repr(self):
         assert repr(GENERIC) == "GENERIC"

tests/pipeline/test_engine.py

@@ -1588,7 +1588,7 @@ def test_no_groupby_maximum(self):
         assert_equal(groupby_max.to_numpy(), pipeline_max.to_numpy())
 
 
-class ResolveDomainTestCase(zf.ZiplineTestCase):
+class TestResolveDomain:
     def test_resolve_domain(self):
         # we need to pass a get_loader and an asset_finder to construct
         # SimplePipelineEngine, but do not expect to use them