first implementation of dfs, bfs, id, a*, ida*

.gitignore

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+.DS_Store
+.idea
+
+# Created by https://www.gitignore.io/api/python
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+
+### Python ###
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+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
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+MANIFEST
+
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+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
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+*.cover
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+# Translations
+*.mo
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+# Django stuff:
+*.log
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+# Sphinx documentation
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+
+# PyBuilder
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+# Jupyter Notebook
+.ipynb_checkpoints
+
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+profile_default/
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+
+# pyenv
+.python-version
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+celerybeat-schedule
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+*.sage.py
+
+# Environments
+.env
+.venv
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+ENV/
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+
+### Python Patch ###
+.venv/
+
+# End of https://www.gitignore.io/api/python

README.md

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+# Example Package
+
+pip install -e ~/Documents/PythonWorkspaces/AI/SEARCH/general_solution
+
+
+This is a simple example package. You can use
+[Github-flavored Markdown](https://guides.github.com/features/mastering-markdown/)
+to write your content.

setup.py

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+import setuptools
+
+with open("README.md", "r") as fh:
+    long_description = fh.read()
+
+setuptools.setup(
+    name="search-jbin", # Replace with your own username
+    version="0.0.1",
+    author="jbin",
+    author_email="[email protected]",
+    description="A library of searh algorithms"
+    long_description=long_description,
+    long_description_content_type="text/markdown",
+    url="",
+    packages=setuptools.find_packages(),
+    classifiers=[
+        "Programming Language :: Python :: 3",
+        "License :: OSI Approved :: MIT License",
+        "Operating System :: OS Independent",
+    ],
+    python_requires='>=3.6',
+)

src/blind_search.py

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+from data_structs import Node, StackFrontier, QueueFrontier
+
+
+def depth_first_search(**kwargs):
+    state_space = kwargs.get('state_space', None)
+    actions = kwargs.get('actions', None)
+    start = kwargs.get('start', None)
+    goal = kwargs.get('goal', None)
+    show_explored = kwargs.get('show_explored', False)
+    depth = kwargs.get('depth', None)   #this is used only when dfs is called in iterative deepening to a certain depth
+
+    #print("Depth: {}".format(depth))
+
+    num_explored = 0
+
+    if depth == None:
+        start = Node(state=start, parent=None, action=None)
+    else: #this is used only when dfs is called in iterative deepening to a certain depth
+        start = Node(state=start, parent=None, action=None, enable_depth=True) 
+
+    frontier = StackFrontier()
+    frontier.add(start)
+    explored = set()
+    print("dfs in pip")
+    while True:
+
+        if frontier.empty():
+            return None
+
+        node = frontier.remove()
+        print('In frontier')
+        num_explored += 1
+
+        if node.state == goal:
+            actions_to_goal = []
+            states_to_goal = []
+            while node.parent is not None:
+                actions_to_goal.append(node.action)
+                states_to_goal.append(node.state)
+                node = node.parent
+            actions_to_goal.reverse()
+            states_to_goal.reverse()
+            solution = (actions_to_goal, states_to_goal)
+            print(solution)
+            if show_explored:
+                return solution, explored
+            else:
+                return solution
+            #return solution
+
+
+        explored.add(node.state)
+        if depth == None:
+            for action, state in actions(node.state):
+                if not frontier.contains_state(state) and state not in explored:
+                    child = Node(state=state, parent=node, action=action)
+                    frontier.add(child)
+        else:    #this is used only when dfs is called in iterative deepening to a certain depth
+            if node.depth <= depth:
+                for action, state in actions(node.state):
+                    if not frontier.contains_state(state) and state not in explored:
+                        child = Node(state=state, parent=node, action=action, enable_depth=True)
+                        print("Child depth: {}".format(depth))
+                        frontier.add(child)              
+
+
+
+
+def breadth_first_search(**kwargs):
+    state_space = kwargs.get('state_space', None)
+    actions = kwargs.get('actions', None)
+    start = kwargs.get('start', None)
+    goal = kwargs.get('goal', None)
+
+    num_explored = 0
+    start = Node(state=start, parent=None, action=None)
+    frontier = QueueFrontier()
+    frontier.add(start)
+    explored = set()
+
+    while True:
+
+        if frontier.empty():
+            return None
+
+        node = frontier.remove()
+        #print('In frontier')
+        num_explored += 1
+
+        if node.state == goal:
+            actions_to_goal = []
+            states_to_goal = []
+            while node.parent is not None:
+                actions_to_goal.append(node.action)
+                states_to_goal.append(node.state)
+                node = node.parent
+            actions_to_goal.reverse()
+            states_to_goal.reverse()
+            solution = (actions_to_goal, states_to_goal)
+            return solution
+
+        explored.add(node.state)
+
+        for action, state in actions(node.state):
+            if not frontier.contains_state(state) and state not in explored:
+                child = Node(state=state, parent=node, action=action)
+                frontier.add(child)
+
+
+
+def iterative_deepening(**kwargs):
+    state_space = kwargs.get('state_space', None)
+    actions = kwargs.get('actions', None)
+    start = kwargs.get('start', None)
+    goal = kwargs.get('goal', None)
+    show_explored = kwargs.get('show_explored', False)
+
+    depth = 1
+    solution = None
+    while solution == None:
+        solution = depth_first_search(actions=actions, start=start, goal=goal, depth=depth, show_explored=show_explored)
+        depth += 1
+    print(solution)
+    return solution