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tkinter实现，直接贴上代码

t = {    "password": account.password}but_js = session.get('http://s.xnimg.cn/a85738/wap/mobile/wechatLive/js/Barrett.js').content.decode()big_js = session.get(&#

class Queue(object):    #初始化队列    def __init__(self):        self.items = []        &

%% 导入数据load tran_data.matclass=avilatr(:,end);   %这个方法读取出来是tableclass1=avilatr{:,end};  %这个读取出来是字符串，可以用find操作%% A类索引class_A=find(class1=="A")';A=avilatr{class_A,1:10};%% 每

import numpy as npimport matplotlib.pyplot as pltdef py_cpu_nms(nms_show, dets, thresh):# nms操作    "Pure Python NMS baseline"    # x1、y1、x2、y2以及score赋

''' 八方向连接算法'''import numpy as npimport matplotlib.image as mpimgfrom PIL import Imagedef compute_conv(fm, kernel, judge=None, kernel_num=3):    [h, w]

# -*- encoding='utf-8' -*-import requestsimport randomimport timeimport refrom bs4 import BeautifulSoupimport os# 首页域名Host = "https://www.qqxsw.co/"user_agent = [   &n

步骤1：初始化参数import numpy as npimport matplotlib.pyplot as pltimport matplotlib as mplmpl.rcParams['font.sans-serif'] = ['SimHei']  # 指定默认字体mpl.rcParams['axes.unicode_minus']

测试脚本：测试脚本，和我前几期讲的差不多，就是发请求，断言，不过这里有个新东西和大家说下，就是sessionID问题，因为实际工作中有好多请求就是依赖这些东西，我这里是更新用户信息，需要用户登录返回来的sessionID，直接上代码：import osfrom HTMLTestRunner import HTMLTestRunnerimport requestsimport unittestimp

# 可以自己import我们平台支持的第三方python模块，比如pandas、numpy等。import numpy as npimport pandas as pdfrom sklearn.linear_model import LinearRegression# 在这个方法中编写任何的初始化逻辑。context对象将会在你的算法策略的任何方法之间做传递。def init(context):&

import plotly as pypy.offline.init_notebook_mode()pyplot = py.offline.iplotimport plotly.graph_objs as gofrom plotly.graph_objs import Scatterfrom scipy import statsimport pandas as pdimport numpy as

import osimport easygui as gimport globimport pandas as pdimport xml.etree.ElementTree as ETfrom tqdm import tqdmimport pandas_profilingimage_path = g.diropenbox( title= "请选择图像文件夹路径",default

from selenium import webdriverimport csvfrom time import sleepimport time##  Author : ATFWUS#  Date : 2021-03-21 20:00#  Version : 1.0#  爬取周杰伦最热门五首歌曲的基本信息，歌词，前五百条热门评论#  此代码仅供交

python解法：# 100分def dfs(x, y, sum1, num):    global count    #不定义全局变量，函数里面的变量不影响外边，而且函数不能调用外边的变量，相当于两个变量了。    global flag     

#-----建立模型、创建数据集-----#-----建立模型、创建数据集-----import osimport cv2import numpy as npfrom PIL import Image#导入pillow库，用于处理图像#设置之前收集好的数据文件路径path = 'data'#初始化识别的方法recog = cv2.face.LBPHFaceRecognizer_cr

import requestsfrom my_test import settingsimport sysimport timeimport pymysqlimport threading# 继承父类threading.Threadclass DownLoadPictures(threading.Thread):    def __init__(self,

def reduce_mem_usage(df):    start_mem = df.memory_usage().sum() / 1024**2     print('Memory usage of dataframe is {:.2f} MB'.format(start_mem)) &n

import osimport torchimport torchimport torch.nn as nnfrom tqdm import tqdmdef autopad(k, p=None):      # Pad to 'same'    if p is None: &nbsp

import timeimport pygameimport ChinaChess.constantsfrom ChinaChess import constants, pieces, computerimport ChinaChess.computerimport ChinaChess.my_game as mg'''此文件为可视化中国象棋运行入口''&#

# coding:utf-8from ctypes import POINTER, c_bool, c_int, pointer, sizeof, WinDLL, byreffrom ctypes.wintypes import DWORD, HWND, LONG, LPCVOIDfrom win32 import win32api, win32guifrom win32.lib import w