diff --git a/src/blp/blp.py b/src/blp/blp.py
index 0ac26f9..b7b2add 100644
--- a/src/blp/blp.py
+++ b/src/blp/blp.py
@@ -925,13 +925,7 @@ def bdib(
 
         """
         query = create_intraday_bar_query(
-            security,
-            event_type,
-            interval,
-            start_datetime,
-            end_datetime,
-            overrides,
-            options,
+            security, event_type, interval, start_datetime, end_datetime, overrides, options,
         )
         res = self.query(query, self.parser, self.collect_to_bdib)
         dfs = []
diff --git a/src/blp/test/test_blp.py b/src/blp/test/test_blp.py
index d6b31e6..9e39b86 100644
--- a/src/blp/test/test_blp.py
+++ b/src/blp/test/test_blp.py
@@ -60,13 +60,7 @@ class MockBlpQuery(blp.BlpQuery):
     }
 
     def __init__(
-        self,
-        host="localhost",
-        port=8194,
-        timeout=10000,
-        parser=None,
-        cache_data=None,
-        **kwargs,
+        self, host="localhost", port=8194, timeout=10000, parser=None, cache_data=None, **kwargs,
     ):
         self._cache = cache_data
         super().__init__(host=host, port=port, timeout=timeout, parser=parser, **kwargs)
@@ -198,8 +192,7 @@ def assert_info_equal(data, exp_data, ignore_overrides=True):
             d["message"]["element"]["fieldResponse"], key=lambda x: x["fieldData"]["id"]
         )
         ed["message"]["element"]["fieldResponse"] = sorted(
-            ed["message"]["element"]["fieldResponse"],
-            key=lambda x: x["fieldData"]["id"],
+            ed["message"]["element"]["fieldResponse"], key=lambda x: x["fieldData"]["id"],
         )
         if ignore_overrides:
             for di in [d, ed]:
@@ -2451,16 +2444,8 @@ def collector_params():
     return {
         "ids": ["collect_many_to_bds_single_bulk", "collect_many_to_bds_with_multi_bulk"],
         "argvalues": [
-            (
-                bulk_reference_parsed_data,
-                blp.BlpQuery().collect_many_to_bds,
-                bulk_reference_collected_exp,
-            ),
-            (
-                bulk_reference_parsed_data_multi,
-                blp.BlpQuery().collect_many_to_bds,
-                bulk_reference_collected_multi_exp,
-            ),
+            (bulk_reference_parsed_data, blp.BlpQuery().collect_many_to_bds, bulk_reference_collected_exp,),
+            (bulk_reference_parsed_data_multi, blp.BlpQuery().collect_many_to_bds, bulk_reference_collected_multi_exp,),
         ],
     }
 
@@ -2489,12 +2474,7 @@ def test_bdh_infer():
     host = HOST
     port = PORT
     bquery = blp.BlpQuery(host, port, timeout=QUERY_TIMEOUT, field_column_map={}).start()
-    df = bquery.bdh(
-        ["SPY US Equity"],
-        ["PX_LAST_ACTUAL"],
-        start_date="20180102",
-        end_date="20180103",
-    )
+    df = bquery.bdh(["SPY US Equity"], ["PX_LAST_ACTUAL"], start_date="20180102", end_date="20180103",)
     df_expect = pandas.DataFrame(
         [(TS(2018, 1, 2), "SPY US Equity", 268.77), (TS(2018, 1, 3), "SPY US Equity", 270.47)],
         columns=["date", "security", "PX_LAST_ACTUAL"],
@@ -2509,16 +2489,10 @@ def test_bdh_coerce_none():
     bquery = blp.BlpQuery(
         host, port, timeout=QUERY_TIMEOUT, field_column_map={"PX_VOLUME": lambda x: pandas.Series(x, dtype="float64")}
     ).start()
-    df = bquery.bdh(
-        ["DOESCRUD Index"],
-        ["PX_VOLUME", "PX_LAST"],
-        start_date="20180105",
-        end_date="20180105",
-    )
+    df = bquery.bdh(["DOESCRUD Index"], ["PX_VOLUME", "PX_LAST"], start_date="20180105", end_date="20180105",)
     dtypes = {"PX_VOLUME": numpy.dtype("float64")}
     df_expect = pandas.DataFrame(
-        [(TS(2018, 1, 5), "DOESCRUD Index", None, 419515.0)],
-        columns=["date", "security", "PX_VOLUME", "PX_LAST"],
+        [(TS(2018, 1, 5), "DOESCRUD Index", None, 419515.0)], columns=["date", "security", "PX_VOLUME", "PX_LAST"],
     ).astype(dtypes)
     assert_frame_equal(df, df_expect)
 
@@ -2550,8 +2524,7 @@ def test_bdp_not_applicable(bquery):
     df = bquery.bdp(["RSF82 Comdty", "PLG18 Comdty"], ["ID_EXCH_SYMBOL"])
     dtypes = {"security": numpy.dtype("O"), "ID_EXCH_SYMBOL": numpy.dtype("O")}
     df_expect = pandas.DataFrame(
-        [["RSF82 Comdty", None], ["PLG18 Comdty", "PL"]],
-        columns=["security", "ID_EXCH_SYMBOL"],
+        [["RSF82 Comdty", None], ["PLG18 Comdty", "PL"]], columns=["security", "ID_EXCH_SYMBOL"],
     ).astype(dtypes)
     assert_frame_equal(df, df_expect)
 
@@ -2607,12 +2580,7 @@ def bdit_params():
         "ids": ["bdit", "bdit_with_condition_codes"],
         "argvalues": [
             ("CL1 Comdty", ["TRADE"], None, dtype_expect),
-            (
-                "CL1 Comdty",
-                ["TRADE"],
-                [("includeConditionCodes", True)],
-                dtype_expect_cc,
-            ),
+            ("CL1 Comdty", ["TRADE"], [("includeConditionCodes", True)], dtype_expect_cc,),
         ],
     }
 
@@ -2645,11 +2613,7 @@ def test_create_historical_query():
         }
     }
     res = blp.create_historical_query(
-        ["SPY US Equity"],
-        ["PX_LAST"],
-        "20190101",
-        "20190110",
-        options=[("periodicitySelection", "DAILY")],
+        ["SPY US Equity"], ["PX_LAST"], "20190101", "20190110", options=[("periodicitySelection", "DAILY")],
     )
     assert res == exp_res