diff --git a/docs/source/conf.py b/docs/source/conf.py
index 35daebf6..fd6692f0 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -125,7 +125,6 @@ def process_docstring(app, what, name, obj, options, lines):
     """Add parameter entries for decorated mods"""
 
     if what in ["function", "method"] and hasattr(obj, "_decorated_mod"):
-
         # Find where the last input parameter is listed
         in_paramlist = False
         lineno = None
diff --git a/src/gurobi_optimods/bipartite_matching.py b/src/gurobi_optimods/bipartite_matching.py
index 6dee1922..39ca267e 100644
--- a/src/gurobi_optimods/bipartite_matching.py
+++ b/src/gurobi_optimods/bipartite_matching.py
@@ -93,7 +93,6 @@ def _maximum_bipartite_matching_pandas(frame, n1_column, n2_column, create_env):
     already in a pandas dataframe."""
 
     with create_env() as env, gp.Model(env=env) as model:
-
         # Directed flow variables between bipartite sets
         df = frame.set_index([n1_column, n2_column]).gppd.add_vars(
             model, ub=1, name="flow"
diff --git a/src/gurobi_optimods/qubo.py b/src/gurobi_optimods/qubo.py
index 755c3692..b400aa70 100644
--- a/src/gurobi_optimods/qubo.py
+++ b/src/gurobi_optimods/qubo.py
@@ -33,7 +33,6 @@ class QuboResult:
 
 
 def callback(model, where):
-
     if where == GRB.Callback.MIP:
         runtime = model.cbGet(GRB.Callback.RUNTIME)
         if runtime >= model._next_output_time:
@@ -85,7 +84,6 @@ def solve_qubo(coeff_matrix, time_limit=GRB.INFINITY, *, create_env) -> QuboResu
     params = {"TimeLimit": time_limit, "LogToConsole": 0}
 
     with create_env(params=params) as env, gp.Model(env=env) as model:
-
         x = model.addMVar(n, vtype=GRB.BINARY)
         model.setObjective(x @ coeff_matrix @ x, GRB.MINIMIZE)
 
diff --git a/src/gurobi_optimods/regression.py b/src/gurobi_optimods/regression.py
index 70325fba..bf72f975 100644
--- a/src/gurobi_optimods/regression.py
+++ b/src/gurobi_optimods/regression.py
@@ -49,7 +49,6 @@ def fit(self, X_train, y_train, *, create_env):
 
         # Create model
         with create_env() as env, gp.Model(env=env) as model:
-
             # Create unbounded variables for each column coefficient, and bound
             # magnitudes using additional variables. Keep intercept separate.
             intercept = model.addVar(lb=-GRB.INFINITY, name="intercept")
diff --git a/src/gurobi_optimods/workforce.py b/src/gurobi_optimods/workforce.py
index ad1b6378..b9de582c 100644
--- a/src/gurobi_optimods/workforce.py
+++ b/src/gurobi_optimods/workforce.py
@@ -62,7 +62,6 @@ def solve_workforce_scheduling(
         input data
     """
     with create_env() as env, gp.Model(env=env) as m:
-
         # Create binary variables for all valid shift assignments and
         # create preference maximization objective
         m.ModelSense = GRB.MAXIMIZE
diff --git a/tests/test_workforce.py b/tests/test_workforce.py
index ca819125..600b072f 100644
--- a/tests/test_workforce.py
+++ b/tests/test_workforce.py
@@ -196,7 +196,6 @@ def test_constrained(self):
         )
 
         with self.subTest("upperlimits"):
-
             worker_limits = read_csv(
                 """
                 Worker,MinShifts,MaxShifts
@@ -228,7 +227,6 @@ def test_constrained(self):
             )
 
         with self.subTest("lowerlimits"):
-
             worker_limits = read_csv(
                 """
                 Worker,MinShifts,MaxShifts