chore: reformat with black

Author: chilango74

examples/02 index funds perfomance.ipynb

@@ -155,7 +155,7 @@
     "    \"VOO.US\",\n",
     "    \"IVV.US\",\n",
     "]  # the benchmark symbol should be in the first place\n",
-    "sp = ok.AssetList(symbols, last_date='2022-04')\n",
+    "sp = ok.AssetList(symbols, last_date=\"2022-04\")\n",
     "sp"
    ]
   },
@@ -291,7 +291,7 @@
     }
    ],
    "source": [
-    "sp.tracking_difference_annualized(rolling_window=5*12).plot()  # rolling window is 5 years"
+    "sp.tracking_difference_annualized(rolling_window=5 * 12).plot()  # rolling window is 5 years"
    ]
   },
   {

main.py

@@ -1,4 +1,4 @@
 import okama as ok
 
-x = ok.AssetList(['SPY.US', 'BND.US', 'GLD.US'], inflation=False)
+x = ok.AssetList(["SPY.US", "BND.US", "GLD.US"], inflation=False)
 print(x.assets_last_dates)

tests/test_frontier.py

@@ -112,14 +112,14 @@ def test_ef_points(init_efficient_frontier):
 
 
 test_tangency_data = [
-    (False, [0.409596, 0.590404], 0.1627),   # cagr = False
-    (True, [0.424916, 0.575084], 0.15617)  # cagr = True
+    (False, [0.409596, 0.590404], 0.1627),  # cagr = False
+    (True, [0.424916, 0.575084], 0.15617),  # cagr = True
 ]
 
 
-@pytest.mark.parametrize("cagr, expected_weights, expected_return",
-                         test_tangency_data,
-                         ids=["MSR Arithmetic mean", "MSR geometric mean"])
+@pytest.mark.parametrize(
+    "cagr, expected_weights, expected_return", test_tangency_data, ids=["MSR Arithmetic mean", "MSR geometric mean"]
+)
 @mark.frontier
 def test_get_tangency_portfolio(init_efficient_frontier, cagr, expected_weights, expected_return):
     rf_rate = 0.05