update

.idea/.gitignore

@@ -0,0 +1,3 @@
+# Default ignored files
+/shelf/
+/workspace.xml

.idea/inspectionProfiles/profiles_settings.xml

@@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

@@ -0,0 +1,4 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.5" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/path-planning-algorithms.iml" filepath="$PROJECT_DIR$/.idea/path-planning-algorithms.iml" />
+    </modules>
+  </component>
+</project>

.idea/path-planning-algorithms.iml

@@ -0,0 +1,12 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+  <component name="PyDocumentationSettings">
+    <option name="format" value="PLAIN" />
+    <option name="myDocStringFormat" value="Plain" />
+  </component>
+</module>

.idea/vcs.xml

@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+  </component>
+</project>

Search-based Planning/.idea/Search-based Planning.iml

@@ -2,10 +2,7 @@
 <module type="PYTHON_MODULE" version="4">
   <component name="NewModuleRootManager">
     <content url="file://$MODULE_DIR$" />
-    <orderEntry type="jdk" jdkName="Python 3.7" jdkType="Python SDK" />
+    <orderEntry type="jdk" jdkName="Python 3.5" jdkType="Python SDK" />
     <orderEntry type="sourceFolder" forTests="false" />
   </component>
-  <component name="TestRunnerService">
-    <option name="PROJECT_TEST_RUNNER" value="Unittests" />
-  </component>
 </module>

Search-based Planning/.idea/misc.xml

@@ -1,4 +1,4 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <project version="4">
-  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.7" project-jdk-type="Python SDK" />
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.5" project-jdk-type="Python SDK" />
 </project>

Search-based Planning/.idea/workspace.xml

@@ -1,8 +1,18 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <project version="4">
   <component name="ChangeListManager">
-    <list default="true" id="025aff36-a6aa-4945-ab7e-b2c625055f47" name="Default Changelist" comment="" />
-    <option name="EXCLUDED_CONVERTED_TO_IGNORED" value="true" />
+    <list default="true" id="025aff36-a6aa-4945-ab7e-b2c625055f47" name="Default Changelist" comment="">
+      <change beforePath="$PROJECT_DIR$/.idea/Search-based Planning.iml" beforeDir="false" afterPath="$PROJECT_DIR$/.idea/Search-based Planning.iml" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/.idea/misc.xml" beforeDir="false" afterPath="$PROJECT_DIR$/.idea/misc.xml" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/.idea/workspace.xml" beforeDir="false" afterPath="$PROJECT_DIR$/.idea/workspace.xml" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/a_star.py" beforeDir="false" afterPath="$PROJECT_DIR$/a_star.py" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/bfs.py" beforeDir="false" afterPath="$PROJECT_DIR$/bfs.py" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/dfs.py" beforeDir="false" afterPath="$PROJECT_DIR$/dfs.py" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/dijkstra.py" beforeDir="false" afterPath="$PROJECT_DIR$/dijkstra.py" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/env.py" beforeDir="false" afterPath="$PROJECT_DIR$/env.py" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/plotting.py" beforeDir="false" afterPath="$PROJECT_DIR$/plotting.py" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/queue.py" beforeDir="false" afterPath="$PROJECT_DIR$/queue.py" afterDir="false" />
+    </list>
     <option name="SHOW_DIALOG" value="false" />
     <option name="HIGHLIGHT_CONFLICTS" value="true" />
     <option name="HIGHLIGHT_NON_ACTIVE_CHANGELIST" value="false" />
@@ -22,25 +32,19 @@
   <component name="ProjectLevelVcsManager" settingsEditedManually="true">
     <ConfirmationsSetting value="2" id="Add" />
   </component>
+  <component name="ProjectViewState">
+    <option name="hideEmptyMiddlePackages" value="true" />
+    <option name="showLibraryContents" value="true" />
+  </component>
   <component name="PropertiesComponent">
     <property name="ASKED_ADD_EXTERNAL_FILES" value="true" />
+    <property name="RunOnceActivity.OpenProjectViewOnStart" value="true" />
+    <property name="RunOnceActivity.ShowReadmeOnStart" value="true" />
     <property name="last_opened_file_path" value="$PROJECT_DIR$" />
     <property name="restartRequiresConfirmation" value="false" />
     <property name="settings.editor.selected.configurable" value="com.jetbrains.python.configuration.PyActiveSdkModuleConfigurable" />
   </component>
-  <component name="RunDashboard">
-    <option name="ruleStates">
-      <list>
-        <RuleState>
-          <option name="name" value="ConfigurationTypeDashboardGroupingRule" />
-        </RuleState>
-        <RuleState>
-          <option name="name" value="StatusDashboardGroupingRule" />
-        </RuleState>
-      </list>
-    </option>
-  </component>
-  <component name="RunManager" selected="Python.dfs">
+  <component name="RunManager" selected="Python.bfs">
     <configuration name="a_star" type="PythonConfigurationType" factoryName="Python" temporary="true">
       <module name="Search-based Planning" />
       <option name="INTERPRETER_OPTIONS" value="" />
@@ -148,10 +152,10 @@
     </configuration>
     <recent_temporary>
       <list>
-        <item itemvalue="Python.dfs" />
         <item itemvalue="Python.bfs" />
-        <item itemvalue="Python.dijkstra" />
         <item itemvalue="Python.a_star" />
+        <item itemvalue="Python.dfs" />
+        <item itemvalue="Python.dijkstra" />
         <item itemvalue="Python.searching" />
       </list>
     </recent_temporary>
@@ -174,12 +178,33 @@
       <map>
         <entry key="MAIN">
           <value>
-            <State>
-              <option name="COLUMN_ORDER" />
-            </State>
+            <State />
           </value>
         </entry>
       </map>
     </option>
+    <option name="oldMeFiltersMigrated" value="true" />
+  </component>
+  <component name="WindowStateProjectService">
+    <state width="1832" height="296" key="GridCell.Tab.0.bottom" timestamp="1592800940514">
+      <screen x="1920" y="0" width="1920" height="1080" />
+    </state>
+    <state width="1832" height="296" key="GridCell.Tab.0.bottom/65.24.1855.1056/1920.0.1920.1080@1920.0.1920.1080" timestamp="1592800940514" />
+    <state width="1832" height="296" key="GridCell.Tab.0.center" timestamp="1592800940514">
+      <screen x="1920" y="0" width="1920" height="1080" />
+    </state>
+    <state width="1832" height="296" key="GridCell.Tab.0.center/65.24.1855.1056/1920.0.1920.1080@1920.0.1920.1080" timestamp="1592800940514" />
+    <state width="1832" height="296" key="GridCell.Tab.0.left" timestamp="1592800940514">
+      <screen x="1920" y="0" width="1920" height="1080" />
+    </state>
+    <state width="1832" height="296" key="GridCell.Tab.0.left/65.24.1855.1056/1920.0.1920.1080@1920.0.1920.1080" timestamp="1592800940514" />
+    <state width="1832" height="296" key="GridCell.Tab.0.right" timestamp="1592800940514">
+      <screen x="1920" y="0" width="1920" height="1080" />
+    </state>
+    <state width="1832" height="296" key="GridCell.Tab.0.right/65.24.1855.1056/1920.0.1920.1080@1920.0.1920.1080" timestamp="1592800940514" />
+    <state x="2406" y="174" key="SettingsEditor" timestamp="1592800563456">
+      <screen x="1920" y="0" width="1920" height="1080" />
+    </state>
+    <state x="2406" y="174" key="SettingsEditor/65.24.1855.1056/1920.0.1920.1080@1920.0.1920.1080" timestamp="1592800563456" />
   </component>
 </project>

Search-based Planning/a_star.py

@@ -1,28 +1,22 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-@author: huiming zhou
-"""
-
 import queue
 import plotting
 import env
 
+
 class Astar:
     def __init__(self, x_start, x_goal, heuristic_type):
         self.xI, self.xG = x_start, x_goal
 
-        self.Env = env.Env()                                                        # class Env
-        self.plotting = plotting.Plotting(self.xI, self.xG)                         # class Plotting
+        self.Env = env.Env()  # class Env
+        self.plotting = plotting.Plotting(self.xI, self.xG)  # class Plotting
 
-        self.u_set = self.Env.motions                                               # feasible input set
-        self.obs = self.Env.obs                                                     # position of obstacles
+        self.u_set = self.Env.motions  # feasible input set
+        self.obs = self.Env.obs  # position of obstacles
 
         [self.path, self.policy, self.visited] = self.searching(self.xI, self.xG, heuristic_type)
 
         self.fig_name = "A* Algorithm"
-        self.plotting.animation(self.path, self.visited, self.fig_name)             # animation generate
-
+        self.plotting.animation(self.path, self.visited, self.fig_name)  # animation generate
 
     def searching(self, xI, xG, heuristic_type):
         """
@@ -31,33 +25,32 @@ class Astar:
         :return: planning path, action in each node, visited nodes in the planning process
         """
 
-        q_astar = queue.QueuePrior()                                                # priority queue
+        q_astar = queue.QueuePrior()  # priority queue
         q_astar.put(xI, 0)
-        parent = {xI: xI}                                                           # record parents of nodes
-        action = {xI: (0, 0)}                                                       # record actions of nodes
+        parent = {xI: xI}  # record parents of nodes
+        action = {xI: (0, 0)}  # record actions of nodes
         visited = []
         cost = {xI: 0}
 
         while not q_astar.empty():
             x_current = q_astar.get()
-            if x_current == xG:                                                     # stop condition
+            if x_current == xG:  # stop condition
                 break
             visited.append(x_current)
-            for u_next in self.u_set:                                   # explore neighborhoods of current node
+            for u_next in self.u_set:  # explore neighborhoods of current node
                 x_next = tuple([x_current[i] + u_next[i] for i in range(len(x_current))])
                 if x_next not in self.obs:
                     new_cost = cost[x_current] + self.get_cost(x_current, u_next)
-                    if x_next not in cost or new_cost < cost[x_next]:   # conditions for updating cost
+                    if x_next not in cost or new_cost < cost[x_next]:  # conditions for updating cost
                         cost[x_next] = new_cost
                         priority = new_cost + self.Heuristic(x_next, xG, heuristic_type)
-                        q_astar.put(x_next, priority)                   # put node into queue using priority "f+h"
+                        q_astar.put(x_next, priority)  # put node into queue using priority "f+h"
                         parent[x_next], action[x_next] = x_current, u_next
 
         [path, policy] = self.extract_path(xI, xG, parent, action)
 
         return path, policy, visited
 
-
     def extract_path(self, xI, xG, parent, policy):
         """
         Extract the path based on the relationship of nodes.
@@ -80,7 +73,6 @@ class Astar:
 
         return list(path_back), list(acts_back)
 
-
     def get_cost(self, x, u):
         """
         Calculate cost for this motion
@@ -93,7 +85,6 @@ class Astar:
 
         return 1
 
-
     def Heuristic(self, state, goal, heuristic_type):
         """
         Calculate heuristic.
@@ -116,4 +107,4 @@ if __name__ == '__main__':
     x_Start = (5, 5)  # Starting node
     x_Goal = (49, 5)  # Goal node
 
-    astar = Astar(x_Start, x_Goal, "manhattan")
+    astar = Astar(x_Start, x_Goal, "manhattan")

Search-based Planning/bfs.py

@@ -1,13 +1,8 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-@author: huiming zhou
-"""
-
 import queue
 import plotting
 import env
 
+
 class BFS:
     def __init__(self, x_start, x_goal):
         self.xI, self.xG = x_start, x_goal
@@ -15,14 +10,13 @@ class BFS:
         self.Env = env.Env()
         self.plotting = plotting.Plotting(self.xI, self.xG)
 
-        self.u_set = self.Env.motions                                       # feasible input set
-        self.obs = self.Env.obs                                             # position of obstacles
+        self.u_set = self.Env.motions  # feasible input set
+        self.obs = self.Env.obs  # position of obstacles
 
         [self.path, self.policy, self.visited] = self.searching(self.xI, self.xG)
 
         self.fig_name = "Breadth-first Searching"
-        self.plotting.animation(self.path, self.visited, self.fig_name)     # animation generate
-
+        self.plotting.animation(self.path, self.visited, self.fig_name)  # animation generate
 
     def searching(self, xI, xG):
         """
@@ -31,10 +25,10 @@ class BFS:
         :return: planning path, action in each node, visited nodes in the planning process
         """
 
-        q_bfs = queue.QueueFIFO()                                           # first-in-first-out queue
+        q_bfs = queue.QueueFIFO()  # first-in-first-out queue
         q_bfs.put(xI)
-        parent = {xI: xI}                                                   # record parents of nodes
-        action = {xI: (0, 0)}                                               # record actions of nodes
+        parent = {xI: xI}  # record parents of nodes
+        action = {xI: (0, 0)}  # record actions of nodes
         visited = []
 
         while not q_bfs.empty():
@@ -42,17 +36,16 @@ class BFS:
             if x_current == xG:
                 break
             visited.append(x_current)
-            for u_next in self.u_set:                                       # explore neighborhoods of current node
+            for u_next in self.u_set:  # explore neighborhoods of current node
                 x_next = tuple([x_current[i] + u_next[i] for i in range(len(x_current))])
-                if x_next not in parent and x_next not in self.obs:         # node not visited and not in obstacles
+                if x_next not in parent and x_next not in self.obs:  # node not visited and not in obstacles
                     q_bfs.put(x_next)
                     parent[x_next], action[x_next] = x_current, u_next
 
-        [path, policy] = self.extract_path(xI, xG, parent, action)          # extract path
+        [path, policy] = self.extract_path(xI, xG, parent, action)  # extract path
 
         return path, policy, visited
 
-
     def extract_path(self, xI, xG, parent, policy):
         """
         Extract the path based on the relationship of nodes.
@@ -77,6 +70,6 @@ class BFS:
 
 
 if __name__ == '__main__':
-    x_Start = (5, 5)                    # Starting node
-    x_Goal = (49, 5)                    # Goal node
+    x_Start = (5, 5)  # Starting node
+    x_Goal = (49, 5)  # Goal node
     bfs = BFS(x_Start, x_Goal)

Search-based Planning/dfs.py

@@ -1,13 +1,8 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-@author: huiming zhou
-"""
-
 import queue
 import plotting
 import env
 
+
 class DFS:
     def __init__(self, x_start, x_goal):
         self.xI, self.xG = x_start, x_goal
@@ -15,14 +10,13 @@ class DFS:
         self.Env = env.Env()
         self.plotting = plotting.Plotting(self.xI, self.xG)
 
-        self.u_set = self.Env.motions                                           # feasible input set
-        self.obs = self.Env.obs                                                 # position of obstacles
+        self.u_set = self.Env.motions  # feasible input set
+        self.obs = self.Env.obs  # position of obstacles
 
         [self.path, self.policy, self.visited] = self.searching(self.xI, self.xG)
 
         self.fig_name = "Depth-first Searching"
-        self.plotting.animation(self.path, self.visited, self.fig_name)         # animation generate
-
+        self.plotting.animation(self.path, self.visited, self.fig_name)  # animation generate
 
     def searching(self, xI, xG):
         """
@@ -31,10 +25,10 @@ class DFS:
         :return: planning path, action in each node, visited nodes in the planning process
         """
 
-        q_dfs = queue.QueueLIFO()                               # last-in-first-out queue
+        q_dfs = queue.QueueLIFO()  # last-in-first-out queue
         q_dfs.put(xI)
-        parent = {xI: xI}                                       # record parents of nodes
-        action = {xI: (0, 0)}                                   # record actions of nodes
+        parent = {xI: xI}  # record parents of nodes
+        action = {xI: (0, 0)}  # record actions of nodes
         visited = []
 
         while not q_dfs.empty():
@@ -42,9 +36,9 @@ class DFS:
             if x_current == xG:
                 break
             visited.append(x_current)
-            for u_next in self.u_set:                                   # explore neighborhoods of current node
+            for u_next in self.u_set:  # explore neighborhoods of current node
                 x_next = tuple([x_current[i] + u_next[i] for i in range(len(x_current))])
-                if x_next not in parent and x_next not in self.obs:     # node not visited and not in obstacles
+                if x_next not in parent and x_next not in self.obs:  # node not visited and not in obstacles
                     q_dfs.put(x_next)
                     parent[x_next], action[x_next] = x_current, u_next
 
@@ -52,7 +46,6 @@ class DFS:
 
         return path, policy, visited
 
-
     def extract_path(self, xI, xG, parent, policy):
         """
         Extract the path based on the relationship of nodes.
@@ -77,6 +70,6 @@ class DFS:
 
 
 if __name__ == '__main__':
-    x_Start = (5, 5)                # Starting node
-    x_Goal = (49, 5)                # Goal node
+    x_Start = (5, 5)  # Starting node
+    x_Goal = (49, 5)  # Goal node
     dfs = DFS(x_Start, x_Goal)

Search-based Planning/dijkstra.py

@@ -1,13 +1,8 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-@author: huiming zhou
-"""
-
 import queue
 import env
 import plotting
 
+
 class Dijkstra:
     def __init__(self, x_start, x_goal):
         self.xI, self.xG = x_start, x_goal
@@ -15,14 +10,13 @@ class Dijkstra:
         self.Env = env.Env()
         self.plotting = plotting.Plotting(self.xI, self.xG)
 
-        self.u_set = self.Env.motions                                           # feasible input set
-        self.obs = self.Env.obs                                                 # position of obstacles
+        self.u_set = self.Env.motions  # feasible input set
+        self.obs = self.Env.obs  # position of obstacles
 
         [self.path, self.policy, self.visited] = self.searching(self.xI, self.xG)
 
         self.fig_name = "Dijkstra's Algorithm"
-        self.plotting.animation(self.path, self.visited, self.fig_name)         # animation generate
-
+        self.plotting.animation(self.path, self.visited, self.fig_name)  # animation generate
 
     def searching(self, xI, xG):
         """
@@ -31,33 +25,32 @@ class Dijkstra:
         :return: planning path, action in each node, visited nodes in the planning process
         """
 
-        q_dijk = queue.QueuePrior()                             # priority queue
+        q_dijk = queue.QueuePrior()  # priority queue
         q_dijk.put(xI, 0)
-        parent = {xI: xI}                                       # record parents of nodes
-        action = {xI: (0, 0)}                                   # record actions of nodes
-        visited = []                                            # record visited nodes
+        parent = {xI: xI}  # record parents of nodes
+        action = {xI: (0, 0)}  # record actions of nodes
+        visited = []  # record visited nodes
         cost = {xI: 0}
 
         while not q_dijk.empty():
             x_current = q_dijk.get()
-            if x_current == xG:                                 # stop condition
+            if x_current == xG:  # stop condition
                 break
             visited.append(x_current)
-            for u_next in self.u_set:                           # explore neighborhoods of current node
+            for u_next in self.u_set:  # explore neighborhoods of current node
                 x_next = tuple([x_current[i] + u_next[i] for i in range(len(x_current))])
-                if x_next not in self.obs:                      # node not visited and not in obstacles
+                if x_next not in self.obs:  # node not visited and not in obstacles
                     new_cost = cost[x_current] + self.get_cost(x_current, u_next)
                     if x_next not in cost or new_cost < cost[x_next]:
                         cost[x_next] = new_cost
                         priority = new_cost
-                        q_dijk.put(x_next, priority)            # put node into queue using cost to come as priority
+                        q_dijk.put(x_next, priority)  # put node into queue using cost to come as priority
                         parent[x_next], action[x_next] = x_current, u_next
 
         [path, policy] = self.extract_path(xI, xG, parent, action)
 
         return path, policy, visited
 
-
     def get_cost(self, x, u):
         """
         Calculate cost for this motion
@@ -70,7 +63,6 @@ class Dijkstra:
 
         return 1
 
-
     def extract_path(self, xI, xG, parent, policy):
         """
         Extract the path based on the relationship of nodes.
@@ -95,6 +87,6 @@ class Dijkstra:
 
 
 if __name__ == '__main__':
-    x_Start = (5, 5)                # Starting node
-    x_Goal = (49, 5)                # Goal node
+    x_Start = (5, 5)  # Starting node
+    x_Goal = (49, 5)  # Goal node
     dijkstra = Dijkstra(x_Start, x_Goal)

Search-based Planning/env.py

@@ -1,11 +1,10 @@
-class Env():
+class Env:
     def __init__(self):
-        self.x_range = 51           # size of background
+        self.x_range = 51  # size of background
         self.y_range = 31
         self.motions = [(1, 0), (-1, 0), (0, 1), (0, -1)]
         self.obs = self.obs_map()
 
-
     def obs_map(self):
         """
         Initialize obstacles' positions
@@ -38,4 +37,3 @@ class Env():
             obs.append((40, i))
 
         return obs
-

Search-based Planning/plotting.py

@@ -1,25 +1,18 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-@author: huiming zhou
-"""
-
 import matplotlib.pyplot as plt
 import env
 
+
 class Plotting():
     def __init__(self, xI, xG):
         self.xI, self.xG = xI, xG
         self.env = env.Env()
         self.obs = self.env.obs_map()
 
-
     def animation(self, path, visited, name):
         self.plot_grid(name)
         self.plot_visited(visited)
         self.plot_path(path)
 
-
     def plot_grid(self, name):
         obs_x = [self.obs[i][0] for i in range(len(self.obs))]
         obs_y = [self.obs[i][1] for i in range(len(self.obs))]
@@ -30,7 +23,6 @@ class Plotting():
         plt.title(name)
         plt.axis("equal")
 
-
     def plot_visited(self, visited):
         visited.remove(self.xI)
         count = 0
@@ -50,7 +42,6 @@ class Plotting():
 
             if count % length == 0: plt.pause(0.001)
 
-
     def plot_path(self, path):
         path.remove(self.xI)
         path.remove(self.xG)

Search-based Planning/queue.py

@@ -1,13 +1,7 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-
-"""
-@author: Huiming Zhou
-"""
-
 import collections
 import heapq
 
+
 class QueueFIFO:
     """
     Class: QueueFIFO
@@ -21,10 +15,11 @@ class QueueFIFO:
         return len(self.queue) == 0
 
     def put(self, node):
-        self.queue.append(node)            # enter from back
+        self.queue.append(node)  # enter from back
 
     def get(self):
-        return self.queue.popleft()        # leave from front
+        return self.queue.popleft()  # leave from front
+
 
 class QueueLIFO:
     """
@@ -39,10 +34,11 @@ class QueueLIFO:
         return len(self.queue) == 0
 
     def put(self, node):
-        self.queue.append(node)            # enter from back
+        self.queue.append(node)  # enter from back
 
     def get(self):
-        return self.queue.pop()            # leave from back
+        return self.queue.pop()  # leave from back
+
 
 class QueuePrior:
     """
@@ -57,7 +53,7 @@ class QueuePrior:
         return len(self.queue) == 0
 
     def put(self, item, priority):
-        heapq.heappush(self.queue, (priority, item))    # reorder x using priority
+        heapq.heappush(self.queue, (priority, item))  # reorder x using priority
 
     def get(self):
-        return heapq.heappop(self.queue)[1]             # pop out the smallest item
+        return heapq.heappop(self.queue)[1]  # pop out the smallest item