###py2 dict是无序的 py3默认是有序的fromcollectionsimportdequefromcollectionsimportdefaultdict,Counter,OrderedDict,ChainMap users=["aa","bb","cc","aa","cc"] dd={}foruserinusers:##方法1#if user not in dd:#dd[user]=1#else:#dd[user]+=1##方法2dd.setdefault(user, 0) dd[user]+= 1...
###py2 dict是无序的 py3默认是有序的 from collections import deque from collections import defaultdict,Counter,OrderedDict,ChainMap users=["aa","bb","cc","aa","cc"] dd={} for user in users: ##方法1 #if user not in dd: #dd[user]=1 # else: # dd[user]+=1 ##方法2 dd.setdef...
from collections import defaultdict, Counter from queue import deque import sys line = sys.stdin.readline() lines = sys.stdin.readlines() l = [] for i in range(len(lines)-1): l.append(list(map(int, lines[i].strip().split())) init = list(map(int, lines[-1].strip().split())...
from collections import Counter # not loaded by default def not_the_same(user, other_user): """two users are not the same if they have different ids""" return user["id"] != other_user["id"] def not_friends(user, other_user): """other_user is not a friend if he's not in ...
from collections import defaultdict dico=defaultdict(list) x_len, y_len = df.shape for i in range(x_len) : if df.iloc[i,0] not in dico : print(str(df.iloc[i,0]) + '\t'+ str(df.iloc[i,1])+ '\t' + str(bool(df.iloc[i,0] not in dico))) dico[str(df.ilo...
from collections import abc, Counter, defaultdict, namedtuple, OrderedDict from collections.abc import Iterable make the above changes. This will import the Iterable class from the collections.abc module, which will allow you to use the inltk package without getting the error. Another wa...
from gensim.models import KeyedVectors from collections import defaultdict, Counter from scipy import optimize as opt import numpy as np# 读取Glove文件,这里使用维度为100的词向量。 def load_embedding(): glovefile = "glove.6B.100d.txt"
# -*- coding: utf-8 -*-importpulpimportnumpyasnpfromitertoolsimportproductfromcollectionsimportdefaultdictfromtypingimportDict,Listfromnltk.corpusimportstopwordsfromnltk.tokenizeimportRegexpTokenizerfromgensim.models.keyedvectorsimportWord2VecKeyedVectors# 加载 txt glove 模型并储存成字典,网上自行下载训练好的...
1.range 迭代器 list(range(1,10))是最快的方式,比列表解析还快。 找出列表出现元素的次数(collections.Counter()) collections.defaultdict()operator.itemgetter() collections.ChainMap() itertools.permutations() 列表解析: 还要字典解析, 集合解析 列表 ...
import itertools import math from typing import Callable, List, Set, Optional, Tuple, Union from collections import defaultdict, Counter import os import shutil import cv2 from PIL import Image import numpy as np import einops import networkx as nx from shapely.geometry import Polygon import torch ...