TST: Use fixture's data with tmp_trading_env

instead of env needing to download it

tests/test_algorithm.py

@@ -92,7 +92,6 @@ from zipline.testing import (
     create_data_portal,
     create_data_portal_from_trade_history,
     create_minute_df_for_asset,
-    empty_trading_env,
     make_test_handler,
     make_trade_data_for_asset_info,
     parameter_space,
@@ -108,7 +107,6 @@ from zipline.testing.fixtures import (
     WithSimParams,
     WithTradingEnvironment,
     WithTmpDir,
-    WithTradingCalendars,
     ZiplineTestCase,
 )
 from zipline.test_algorithms import (
@@ -786,7 +784,8 @@ def log_nyse_close(context, data):
                 for i, date in enumerate(dates)
             ]
         )
-        with tmp_trading_env(equities=metadata) as env:
+        with tmp_trading_env(equities=metadata,
+                             load=self.make_load_function()) as env:
             algo = TradingAlgorithm(env=env)
 
             # Set the period end to a date after the period end
@@ -853,7 +852,8 @@ class TestTransformAlgorithm(WithLogger,
     def init_class_fixtures(cls):
         super(TestTransformAlgorithm, cls).init_class_fixtures()
         cls.futures_env = cls.enter_class_context(
-            tmp_trading_env(futures=cls.make_futures_info()),
+            tmp_trading_env(futures=cls.make_futures_info(),
+                            load=cls.make_load_function()),
         )
 
     def test_invalid_order_parameters(self):
@@ -1065,7 +1065,8 @@ def before_trading_start(context, data):
         }] * 2)
         equities['symbol'] = ['A', 'B']
         with TempDirectory() as tempdir, \
-                tmp_trading_env(equities=equities) as env:
+                tmp_trading_env(equities=equities,
+                                load=self.make_load_function()) as env:
             sim_params = SimulationParameters(
                 start_session=start_session,
                 end_session=period_end,
@@ -3175,7 +3176,8 @@ class TestTradingControls(WithSimParams, WithDataPortal, ZiplineTestCase):
             orient='index',
         )
         with TempDirectory() as tempdir, \
-                tmp_trading_env(equities=metadata) as env:
+                tmp_trading_env(equities=metadata,
+                                load=self.make_load_function()) as env:
             sim_params = factory.create_simulation_parameters(
                 start=start,
                 num_days=4,
@@ -3302,7 +3304,8 @@ class TestTradingControls(WithSimParams, WithDataPortal, ZiplineTestCase):
             'sid': 999,
         }])
         with TempDirectory() as tempdir, \
-                tmp_trading_env(equities=metadata) as env:
+                tmp_trading_env(equities=metadata,
+                                load=self.make_load_function()) as env:
             algo = SetAssetDateBoundsAlgorithm(
                 sim_params=self.sim_params,
                 env=env,
@@ -3324,7 +3327,8 @@ class TestTradingControls(WithSimParams, WithDataPortal, ZiplineTestCase):
             'sid': 999,
         }])
         with TempDirectory() as tempdir, \
-                tmp_trading_env(equities=metadata) as env:
+                tmp_trading_env(equities=metadata,
+                                load=self.make_load_function()) as env:
             data_portal = create_data_portal(
                 env.asset_finder,
                 tempdir,
@@ -3347,7 +3351,8 @@ class TestTradingControls(WithSimParams, WithDataPortal, ZiplineTestCase):
             'sid': 999,
         }])
         with TempDirectory() as tempdir, \
-                tmp_trading_env(equities=metadata) as env:
+                tmp_trading_env(equities=metadata,
+                                load=self.make_load_function()) as env:
             data_portal = create_data_portal(
                 env.asset_finder,
                 tempdir,
@@ -3774,7 +3779,7 @@ class TestFuturesAlgo(WithDataPortal, WithSimParams, ZiplineTestCase):
             self.assertEqual(txn['price'], expected_price)
 
 
-class TestTradingAlgorithm(ZiplineTestCase):
+class TestTradingAlgorithm(WithTradingEnvironment, ZiplineTestCase):
     def test_analyze_called(self):
         self.perf_ref = None
 
@@ -3794,9 +3799,8 @@ class TestTradingAlgorithm(ZiplineTestCase):
             env=self.env,
         )
 
-        with empty_trading_env() as env:
-            data_portal = FakeDataPortal(env)
-            results = algo.run(data_portal)
+        data_portal = FakeDataPortal(self.env)
+        results = algo.run(data_portal)
 
         self.assertIs(results, self.perf_ref)
 
@@ -3996,7 +4000,7 @@ class TestOrderCancelation(WithDataPortal,
             self.assertFalse(log_catcher.has_warnings)
 
 
-class TestEquityAutoClose(WithTmpDir, WithTradingCalendars, ZiplineTestCase):
+class TestEquityAutoClose(WithTradingEnvironment, WithTmpDir, ZiplineTestCase):
     """
     Tests if delisted equities are properly removed from a portfolio holding
     positions in said equities.
@@ -4027,7 +4031,10 @@ class TestEquityAutoClose(WithTmpDir, WithTradingCalendars, ZiplineTestCase):
 
         sids = asset_info.index
 
-        env = self.enter_instance_context(tmp_trading_env(equities=asset_info))
+        env = self.enter_instance_context(
+            tmp_trading_env(equities=asset_info,
+                            load=self.make_load_function())
+        )
 
         if frequency == 'daily':
             dates = self.test_days
@@ -4680,7 +4687,7 @@ class AlgoInputValidationTestCase(WithTradingEnvironment, ZiplineTestCase):
                 )
 
 
-class TestPanelData(ZiplineTestCase):
+class TestPanelData(WithTradingEnvironment, ZiplineTestCase):
 
     @parameterized.expand([
         ('daily',
@@ -4702,6 +4709,9 @@ class TestPanelData(ZiplineTestCase):
 
             def dt_transform(dt):
                 return dt
+        else:
+            raise AssertionError('Unexpected data_frequency: %s' %
+                                 data_frequency)
 
         sids = range(1, 3)
         dfs = {}
@@ -4742,11 +4752,13 @@ class TestPanelData(ZiplineTestCase):
                                  'prev_close']].values.astype('float64')
             )
 
-        trading_algo = TradingAlgorithm(initialize=initialize,
-                                        handle_data=handle_data)
-        trading_algo.run(data=panel)
-        check_panels()
-        price_record.loc[:] = np.nan
+        with tmp_trading_env(load=self.make_load_function()) as env:
+            trading_algo = TradingAlgorithm(initialize=initialize,
+                                            handle_data=handle_data,
+                                            env=env)
+            trading_algo.run(data=panel)
+            check_panels()
+            price_record.loc[:] = np.nan
 
         run_algorithm(
             start=start_dt,