isort; edit workflow

Author: 88d52bdba0366127fffca9dfa93895

.flake8

@@ -0,0 +1,3 @@
+[flake8]
+max-line-length = 88
+extend-ignore = E203

.github/workflows/main.yml

@@ -1,9 +1,13 @@
+# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
+# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python
+
 name: pytest
+
 on:
-    pull_request:
-    push:
-        branches:
-            - master
+  push:
+    branches: [ "master" ]
+  pull_request:
+    branches: [ "master" ]
 
 jobs:
     pytest:
@@ -28,7 +32,16 @@ jobs:
             - name: Install dependencies
               run: |
                   pip install -r requirements.txt
+                  pip install pytest isort black flake8
             - name: Test with pytest
               run: |
-                  pip install pytest
-                  pytest ./tests
+                  pytest ./tests
+            - name: Check with isort
+              run: |
+                  isort --check --diff .
+            - name: Check with black
+              run: |
+                  black --check --diff .
+            - name: Check with flake8
+              run: |
+                  flake8 --show-source --statistics .

.gitignore

@@ -1,3 +1,4 @@
+.git
 *.pyc
 .idea
 build

docs/conf.py

@@ -13,8 +13,8 @@
 # All configuration values have a default; values that are commented out
 # serve to show the default.
 
-import sys
 import os
+import sys
 
 # If extensions (or modules to document with autodoc) are in another directory,
 # add these directories to sys.path here. If the directory is relative to the

example/examples.py

@@ -1,17 +1,19 @@
-import pandas as pd
-import numpy as np
 import cvxpy as cp
-from pypfopt import risk_models
-from pypfopt import expected_returns
-from pypfopt import EfficientFrontier
-from pypfopt import objective_functions
-from pypfopt.discrete_allocation import DiscreteAllocation, get_latest_prices
-from pypfopt import HRPOpt
-from pypfopt import CLA
-from pypfopt import black_litterman
-from pypfopt import BlackLittermanModel
-from pypfopt import plotting
+import numpy as np
+import pandas as pd
 
+from pypfopt import (
+    CLA,
+    BlackLittermanModel,
+    EfficientFrontier,
+    HRPOpt,
+    black_litterman,
+    expected_returns,
+    objective_functions,
+    plotting,
+    risk_models,
+)
+from pypfopt.discrete_allocation import DiscreteAllocation, get_latest_prices
 
 # Reading in the data; preparing expected returns and a risk model
 df = pd.read_csv("tests/resources/stock_prices.csv", parse_dates=True, index_col="date")

pypfopt/__init__.py

@@ -1,20 +1,19 @@
 from .black_litterman import (
+    BlackLittermanModel,
     market_implied_prior_returns,
     market_implied_risk_aversion,
-    BlackLittermanModel,
 )
 from .cla import CLA
-from .discrete_allocation import get_latest_prices, DiscreteAllocation
+from .discrete_allocation import DiscreteAllocation, get_latest_prices
 from .efficient_frontier import (
+    EfficientCDaR,
+    EfficientCVaR,
     EfficientFrontier,
     EfficientSemivariance,
-    EfficientCVaR,
-    EfficientCDaR,
 )
 from .hierarchical_portfolio import HRPOpt
 from .risk_models import CovarianceShrinkage
 
-
 __version__ = "1.5.4"
 
 __all__ = [

pypfopt/base_optimizer.py

@@ -13,13 +13,12 @@
 from collections.abc import Iterable
 from typing import List
 
+import cvxpy as cp
 import numpy as np
 import pandas as pd
-import cvxpy as cp
 import scipy.optimize as sco
 
-from . import objective_functions
-from . import exceptions
+from . import exceptions, objective_functions
 
 
 class BaseOptimizer:

pypfopt/black_litterman.py

@@ -8,8 +8,10 @@
 """
 import sys
 import warnings
+
 import numpy as np
 import pandas as pd
+
 from . import base_optimizer
 
 

pypfopt/cla.py

@@ -6,6 +6,7 @@
 
 import numpy as np
 import pandas as pd
+
 from . import base_optimizer
 
 

pypfopt/efficient_frontier/__init__.py

@@ -3,11 +3,10 @@
 which generate optimal portfolios for various possible objective functions and parameters.
 """
 
-from .efficient_frontier import EfficientFrontier
+from .efficient_cdar import EfficientCDaR
 from .efficient_cvar import EfficientCVaR
+from .efficient_frontier import EfficientFrontier
 from .efficient_semivariance import EfficientSemivariance
-from .efficient_cdar import EfficientCDaR
-
 
 __all__ = [
     "EfficientFrontier",