Packaging Pypi

.github/workflows/build.yml

@@ -4,7 +4,14 @@ on: [push]
 
 jobs:
   build:
-    runs-on: ubuntu-latest
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        os: [ubuntu-latest, macos-latest]
+        python-version: [3.6, 3.7, 3.8]
+        exclude:
+          - os: macos-latest
+            python-version: 3.8
 
     steps:
     - uses: actions/checkout@v2

.github/workflows/tests.yml

@@ -4,7 +4,14 @@ on: [push]
 
 jobs:
   build:
-    runs-on: ubuntu-latest
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        os: [ubuntu-latest, macos-latest]
+        python-version: [3.6, 3.7, 3.8]
+        exclude:
+          - os: macos-latest
+            python-version: 3.8
 
     steps:
     - uses: actions/checkout@v2
@@ -34,7 +41,16 @@ jobs:
         flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
 
   test:
-    runs-on: ubuntu-latest
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        os: [ubuntu-latest, macos-latest, windows-latest]
+        python-version: [3.6, 3.7, 3.8, pypy-3.6]
+        exclude:
+          - os: macos-latest
+            python-version: 3.8
+          - os: windows-latest
+            python-version: 3.6
     steps:
       - uses: actions/checkout@v2
       - name: Set up Python 3.7

README.md

@@ -45,23 +45,15 @@ $ julia --color=yes -e 'using Pkg; Pkg.add(Pkg.PackageSpec(path="https://github.
 
 ```bash
 $ python3 -m pip install --upgrade pip
-$ git clone https://github.com/APLA-Toolbox/PythonPDDL
-$ cd PythonPDDL
-$ python3 -m pip install -r requirements.txt
+$ python3 -m pip install jupyddl
 ```
 
-# Usage
-
-Navigate to the root directory and you can run the tool by using : `python3 main.py "data/domain.pddl" "data/problem.pddl"`
-
 # REFL Mode
 
-- Clone the repository: `git clone https://github.com/APLA-Toolbox/PythonPDDL`
-- Move to the repository folder: `cd PythonPDDL`
 - Run `python3` in the terminal.
 - Use the AutomatedPlanner class to do what you want:
 ```python
-from src.automated_planner import AutomatedPlanner # takes some time because it has to instantiate the Julia interface
+from jupyddl import AutomatedPlanner # takes some time because it has to instantiate the Julia interface
 apl = AutomatedPlanner("data/domain.pddl", "data/problem.pddl)
 
 apl.initial_state
@@ -85,15 +77,11 @@ print(apl.get_actions_from_path(path))
 [<PyCall.jlwrap flip_row(r1)>, <PyCall.jlwrap flip_row(r3)>, <PyCall.jlwrap flip_column(c2)>]
 ```
 
-# Script mode
-
-UC
-
 # Contribute
 
 Open an issue to state clearly the contribution you want to make. Upon aproval send in a PR with the Issue referenced. (Implement Issue #No / Fix Issue #No).
 
-# Contributors
+# Maintainers
 
 - Erwin Lejeune
 - Sampreet Sarkar

jupyddl/__init__.py

@@ -0,0 +1,4 @@
+from .automated_planner import AutomatedPlanner
+
+if __name__ == "__main__":
+    _ = AutomatedPlanner("data/domain.pddl", "data/problem.pddl")

src/automated_planner.py → jupyddl/automated_planner.py

@@ -47,8 +47,7 @@ def satisfies(self, asserted_state, state):
     def state_has_term(self, state, term):
         if self.pddl.has_term_in_state(self.domain, state, term):
             return True
-        else:
-            return False
+        return False
 
     def __flatten_goal(self):
         return self.pddl.flatten_goal(self.problem)
@@ -74,8 +73,7 @@ def get_actions_from_path(self, path):
         cost = self.pddl.get_value(path[-1].state, "total-cost")
         if not cost:
             return actions
-        else:
-            return (actions, cost)
+        return (actions, cost)
 
     def get_state_def_from_path(self, path):
         if not path:
@@ -92,32 +90,28 @@ def breadth_first_search(self, time_it=False):
         path = self.__retrace_path(last_node)
         if time_it:
             return path, total_time
-        else:
-            return path, None
+        return path, None
 
     def depth_first_search(self, time_it=False):
         dfs = DepthFirstSearch(self)
         last_node, total_time = dfs.search()
         path = self.__retrace_path(last_node)
         if time_it:
             return path, total_time
-        else:
-            return path, None
+        return path, None
 
     def dijktra_best_first_search(self, time_it=False):
         dijkstra = DijkstraBestFirstSearch(self)
         last_node, total_time = dijkstra.search()
         path = self.__retrace_path(last_node)
         if time_it:
             return path, total_time
-        else:
-            return path, None
+        return path, None
 
     def astar_best_first_search(self, time_it=False, heuristic=goal_count_heuristic):
         astar = AStarBestFirstSearch(self, heuristic)
         last_node, total_time = astar.search()
         path = self.__retrace_path(last_node)
         if time_it:
             return path, total_time
-        else:
-            return path, None
+        return path, None

setup.py

@@ -0,0 +1,33 @@
+import setuptools
+
+with open("requirements.txt") as f:
+    required = f.read().splitlines()
+
+with open("README.md", "r", encoding="utf-8") as fh:
+    long_description = fh.read()
+
+
+setuptools.setup(
+    name="jupyddl",  # Replace with your own username
+    version="0.2.4",
+    author="Erwin Lejeune",
+    author_email="erwinlejeune.pro@gmail.com",
+    description="Jupyddl is a PDDL planner built on top of a Julia parser",
+    long_description=long_description,
+    long_description_content_type="text/markdown",
+    url="https://github.com/apla-toolbox/pythonpddl",
+    packages=setuptools.find_packages(),
+    install_requires=required,
+    classifiers=[
+        "Programming Language :: Python :: 3 :: Only",
+        "Programming Language :: Python :: 3.6",
+        "Programming Language :: Python :: 3.7",
+        "Programming Language :: Python :: 3.8",
+        "Programming Language :: Python :: 3",
+        "License :: OSI Approved :: Apache Software License",
+        "Operating System :: Unix",
+        "Operating System :: MacOS",
+        "Framework :: Pytest",
+    ],
+    python_requires=">=3.6",
+)

tests/test_automated_planner.py

@@ -28,9 +28,9 @@ def test_execute_action():
 def test_state_has_term():
     apla = AutomatedPlanner("data/domain.pddl", "data/problem.pddl")
     is_goal = apla.state_has_term(apla.initial_state, apla.goals[0])
-    assert is_goal == False
+    assert not is_goal
 
 
 def test_state_assertion():
     apla = AutomatedPlanner("data/domain.pddl", "data/problem.pddl")
-    assert apla.satisfies(apla.problem.goal, apla.initial_state) == False
+    assert not apla.satisfies(apla.problem.goal, apla.initial_state)