feat: flake8 Job (#13)

* feat: Pylint Job

* only test for python 3.10

* Move direct scirpts out of src

* use flake8

* set max line length to 120

* fixe format

.github/workflows/flake8.yml

@@ -0,0 +1,23 @@
+name: Pylint
+
+on: [push]
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ["3.10"]
+    steps:
+    - uses: actions/checkout@v3
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v3
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install flake8
+    - name: Analysing the code with flake8
+      run: |
+        flake8 $(git ls-files 'src/**.py')

src/irlwpython/scripts/direct_train_deep_max_entropy_irl.py → scripts/direct_train_deep_max_entropy_irl.py

@@ -124,7 +124,7 @@ def get_demonstrations(self, env):
         env_high = env.observation_space.high
         env_distance = (env_high - env_low) / self.one_feature
 
-        raw_demo = np.load(file="../expert_demo/expert_demo.npy")
+        raw_demo = np.load(file="../src/irlwpython/expert_demo/expert_demo.npy")
         demonstrations = np.zeros((len(raw_demo), len(raw_demo[0]), 3))
         for x in range(len(raw_demo)):
             for y in range(len(raw_demo[0])):

setup.cfg

@@ -112,7 +112,7 @@ formats = bdist_wheel
 
 [flake8]
 # Some sane defaults for the code style checker flake8
-max_line_length = 88
+max_line_length = 120
 extend_ignore = E203, W503
 # ^  Black-compatible
 #    E203 and W503 have edge cases handled by black

src/irlwpython/MaxEntropyIRL.py

@@ -5,7 +5,6 @@
 #
 
 import numpy as np
-import matplotlib.pyplot as plt
 
 from irlwpython.FigurePrinter import FigurePrinter
 
@@ -135,7 +134,8 @@ def train(self, theta_learning_rate, episode_count=30000):
                 score_avg = np.mean(scores)
                 print('{} episode score is {:.2f}'.format(episode, score_avg))
                 self.printer.save_plot_as_png(episodes, scores,
-                                              f"src/irlwpython/learning_curves/maxent_{episode_count}_{episode}_qtable.png")
+                                              f"src/irlwpython/learning_curves/"
+                                              f"maxent_{episode_count}_{episode}_qtable.png")
                 self.printer.save_heatmap_as_png(learner.reshape((20, 20)),
                                                  f"src/irlwpython/heatmap/learner_{episode}_flat.png")
                 self.printer.save_heatmap_as_png(self.theta.reshape((20, 20)),

src/irlwpython/main.py

@@ -32,7 +32,8 @@ def parse_args(args):
         version=f"IRLwPython {__version__}",
     )
     parser.add_argument('algorithm', metavar='ALGORITHM', type=str,
-                        help='Currently supported training algorithm: [max-entropy, max-entropy-deep, max-entropy-deep-rl]')
+                        help='Currently supported training algorithm: '
+                             '[max-entropy, max-entropy-deep, max-entropy-deep-rl]')
     parser.add_argument('--training', action='store_true', help="Enables training of model.")
     parser.add_argument('--testing', action='store_true',
                         help="Enables testing of previously created model.")