def generic_solver_multi(maze_num):
maze_map = mazes[maze_num]
selected_type = request.args.get('search_type')
# change string to enum
selected_type = search_type.A_Star if selected_type == "a_star" else selected_type
selected_type = search_type.DFS if selected_type == "dfs" else selected_type
selected_type = search_type.BFS if selected_type == "bfs" else selected_type
selected_type = search_type.GFS if selected_type == "gfs" else selected_type
s = search(selected_type, maze_map)
targets_dict = s.get_path()
distance = s.get_cost()
targets_ordered = list(targets_dict.keys())
path = multi_point_path(targets_dict)
# points = path_id_to_points(maze_map, path)
for k in targets_dict.keys():
path_ids = targets_dict[k]
path = [maze_map.graph.nodes[id_] for id_ in path_ids]
points = path_to_points(path)
targets_dict[k] = points
return json.dumps({"points": targets_dict, "order": targets_ordered, "cost": distance}, cls=EnhancedJSONEncoder)
def search_endpoint():
query = request.args.get("query")
medium = request.args.get("medium")
results = search(query, medium)
return jsonify(results)
def home():
if request.method == 'GET':
return render_template('index.html', ID = "")
else:
search_term = request.form['lyric']
outputfilename = search.setup(search_term)
client_id, client_secret, client_access_token = search.load_credentials()
return render_template('index.html', ID= search.search(request.form['lyric'],rake.do(search_term),outputfilename,client_access_token))#, hi=translator.prep(search.setup(search_term)))
def search_key():
if request.method == 'GET':
key = request.args.get('key_txt')
if key:
result = search(key)
if result:
return render_template('index_upload.html', result=result)
return render_template('index_upload.html')
def main():
mode = input(
'Welcome to Gresynonyms, pls type your commands:\n-s: search for words or explainations\n-i: input new words pair\n'
)
if mode == '-s':
search.search()
elif mode == '-q':
memorize.main()
# elif '--rw' in mode:
elif mode == '-i':
input_continue = "y"
while input_continue != "N":
save_words.input_pairs()
input_continue = input("continue input? y/N: ")
elif mode == '--help':
print('-s search /n -q quiz /n --rw random word /n -w write new pairs')
else:
print('invalid inpt, pls ')
async def play(self, ctx, *song):
await self.join(ctx)
server = ctx.message.server
voice_client = self.bot.voice_client_in(server)
player = await voice_client.create_ytdl_player(
search(song), after=lambda: self.check_queue(ctx))
if self.players.get(server.id) is None:
self.players[server.id] = player
player.start()
await self.bot.say("now playing " + player.title)
else:
await self.queue(server.id, player)
def _traverse(self, curr_node, LCCN): if not curr_node: return srh = search() if srh.contains(curr_node.getLCCN(), LCCN): children = curr_node.getChildren() if children: for child in children: ret_node = self._traverse(child, LCCN) if ret_node: return ret_node return curr_node
def epander_solver(maze_num):
maze_map = mazes[maze_num]
selected_type = request.args.get('search_type')
# change string to enum
selected_type = search_type.A_Star if selected_type == "a_star" else selected_type
selected_type = search_type.DFS if selected_type == "dfs" else selected_type
selected_type = search_type.BFS if selected_type == "bfs" else selected_type
selected_type = search_type.GFS if selected_type == "gfs" else selected_type
s = search(selected_type, maze_map)
expantion = s.get_expansion()
distance = s.get_cost()
# points = path_id_to_points(maze_map, path)
# print(path)
# distance = path_to_distance(path)
return json.dumps({"expantion": expantion, "cost": distance}, cls=EnhancedJSONEncoder)
def generic_solver_single(maze_num):
maze_map = mazes[maze_num]
selected_type = request.args.get('search_type')
# change string to enum
selected_type = search_type.A_Star if selected_type == "a_star" else selected_type
selected_type = search_type.DFS if selected_type == "dfs" else selected_type
selected_type = search_type.BFS if selected_type == "bfs" else selected_type
selected_type = search_type.GFS if selected_type == "gfs" else selected_type
s = search(selected_type, maze_map)
path = list(s.get_path().values())[0]
distance = s.get_cost()
points = path_id_to_points(maze_map, path)
# print(path)
# distance = path_to_distance(path)
return json.dumps({"points": points, "cost": distance}, cls=EnhancedJSONEncoder)
'mediumSearch.txt', 'smallSearch.txt', 'tinySearch.txt'
]
# NOTE testing common search logic
for i in search_type:
for j in range(7):
if j > 2 and i == search_type.DFS:
break
maze_name = mazes[j]
maze_map = Maze_map(f'Maze/{maze_name}')
search_type_name = i.name
# print("Testing...")
print('search type is: ', i)
s = search(i, maze_map)
path = s.get_path()
_path_copy = deepcopy(path)
path_nodes_ids = multi_point_path(_path_copy)
try:
points = path_id_to_points(maze_map, path_nodes_ids)
except:
points = [0]
# print(f"path saved in sol/{search_type_name}/{mazes[j]}")
cost = s.get_cost()
# cost = 0
print(cost)
print(len(points) - 1)
# print(cost == len(points))
