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refactor: Replace list()
and dict()
calls with literals (#7198)
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@ -160,7 +160,7 @@ def postorder(curr_node):
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"""
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"""
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postOrder (left, right, self)
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postOrder (left, right, self)
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"""
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"""
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node_list = list()
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node_list = []
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if curr_node is not None:
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if curr_node is not None:
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node_list = postorder(curr_node.left) + postorder(curr_node.right) + [curr_node]
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node_list = postorder(curr_node.left) + postorder(curr_node.right) + [curr_node]
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return node_list
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return node_list
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@ -9,7 +9,7 @@ class Heap:
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def __init__(self, key: Callable | None = None) -> None:
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def __init__(self, key: Callable | None = None) -> None:
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# Stores actual heap items.
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# Stores actual heap items.
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self.arr: list = list()
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self.arr: list = []
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# Stores indexes of each item for supporting updates and deletion.
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# Stores indexes of each item for supporting updates and deletion.
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self.pos_map: dict = {}
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self.pos_map: dict = {}
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# Stores current size of heap.
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# Stores current size of heap.
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@ -8,7 +8,7 @@ longest word)) lookup time making it an optimal approach when space is not an is
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class TrieNode:
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class TrieNode:
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def __init__(self) -> None:
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def __init__(self) -> None:
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self.nodes: dict[str, TrieNode] = dict() # Mapping from char to TrieNode
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self.nodes: dict[str, TrieNode] = {} # Mapping from char to TrieNode
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self.is_leaf = False
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self.is_leaf = False
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def insert_many(self, words: list[str]) -> None:
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def insert_many(self, words: list[str]) -> None:
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@ -54,7 +54,7 @@ def get_frequency_table(edge_array):
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Returns Frequency Table
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Returns Frequency Table
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"""
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"""
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distinct_edge = get_distinct_edge(edge_array)
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distinct_edge = get_distinct_edge(edge_array)
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frequency_table = dict()
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frequency_table = {}
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for item in distinct_edge:
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for item in distinct_edge:
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bit = get_bitcode(edge_array, item)
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bit = get_bitcode(edge_array, item)
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@ -74,7 +74,7 @@ def find_minimum_change(denominations: list[int], value: str) -> list[int]:
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# Driver Code
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# Driver Code
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if __name__ == "__main__":
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if __name__ == "__main__":
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denominations = list()
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denominations = []
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value = "0"
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value = "0"
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if (
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if (
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@ -199,7 +199,7 @@ def find_pure_symbols(
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{'A1': True, 'A2': False, 'A3': True, 'A5': False}
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{'A1': True, 'A2': False, 'A3': True, 'A5': False}
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"""
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"""
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pure_symbols = []
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pure_symbols = []
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assignment: dict[str, bool | None] = dict()
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assignment: dict[str, bool | None] = {}
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literals = []
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literals = []
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for clause in clauses:
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for clause in clauses:
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@ -264,7 +264,7 @@ def find_unit_clauses(
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n_count += 1
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n_count += 1
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if f_count == len(clause) - 1 and n_count == 1:
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if f_count == len(clause) - 1 and n_count == 1:
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unit_symbols.append(sym)
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unit_symbols.append(sym)
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assignment: dict[str, bool | None] = dict()
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assignment: dict[str, bool | None] = {}
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for i in unit_symbols:
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for i in unit_symbols:
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symbol = i[:2]
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symbol = i[:2]
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assignment[symbol] = len(i) == 2
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assignment[symbol] = len(i) == 2
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@ -100,7 +100,7 @@ def solution(filename: str = "p107_network.txt") -> int:
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script_dir: str = os.path.abspath(os.path.dirname(__file__))
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script_dir: str = os.path.abspath(os.path.dirname(__file__))
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network_file: str = os.path.join(script_dir, filename)
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network_file: str = os.path.join(script_dir, filename)
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adjacency_matrix: list[list[str]]
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adjacency_matrix: list[list[str]]
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edges: dict[EdgeT, int] = dict()
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edges: dict[EdgeT, int] = {}
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data: list[str]
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data: list[str]
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edge1: int
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edge1: int
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edge2: int
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edge2: int
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@ -51,7 +51,7 @@ def generate_neighbours(path):
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with open(path) as f:
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with open(path) as f:
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for line in f:
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for line in f:
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if line.split()[0] not in dict_of_neighbours:
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if line.split()[0] not in dict_of_neighbours:
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_list = list()
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_list = []
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_list.append([line.split()[1], line.split()[2]])
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_list.append([line.split()[1], line.split()[2]])
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dict_of_neighbours[line.split()[0]] = _list
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dict_of_neighbours[line.split()[0]] = _list
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else:
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else:
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@ -59,7 +59,7 @@ def generate_neighbours(path):
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[line.split()[1], line.split()[2]]
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[line.split()[1], line.split()[2]]
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)
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)
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if line.split()[1] not in dict_of_neighbours:
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if line.split()[1] not in dict_of_neighbours:
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_list = list()
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_list = []
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_list.append([line.split()[0], line.split()[2]])
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_list.append([line.split()[0], line.split()[2]])
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dict_of_neighbours[line.split()[1]] = _list
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dict_of_neighbours[line.split()[1]] = _list
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else:
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else:
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@ -206,7 +206,7 @@ def tabu_search(
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"""
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"""
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count = 1
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count = 1
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solution = first_solution
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solution = first_solution
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tabu_list = list()
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tabu_list = []
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best_cost = distance_of_first_solution
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best_cost = distance_of_first_solution
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best_solution_ever = solution
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best_solution_ever = solution
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@ -52,8 +52,8 @@ def _msd_radix_sort(list_of_ints: list[int], bit_position: int) -> list[int]:
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if bit_position == 0 or len(list_of_ints) in [0, 1]:
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if bit_position == 0 or len(list_of_ints) in [0, 1]:
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return list_of_ints
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return list_of_ints
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zeros = list()
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zeros = []
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ones = list()
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ones = []
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# Split numbers based on bit at bit_position from the right
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# Split numbers based on bit at bit_position from the right
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for number in list_of_ints:
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for number in list_of_ints:
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if (number >> (bit_position - 1)) & 1:
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if (number >> (bit_position - 1)) & 1:
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@ -5,7 +5,7 @@ from collections import deque
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class Automaton:
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class Automaton:
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def __init__(self, keywords: list[str]):
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def __init__(self, keywords: list[str]):
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self.adlist: list[dict] = list()
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self.adlist: list[dict] = []
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self.adlist.append(
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self.adlist.append(
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{"value": "", "next_states": [], "fail_state": 0, "output": []}
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{"value": "", "next_states": [], "fail_state": 0, "output": []}
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)
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)
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