前言：

由于最近接触了 tensorflow.js，出于试一下的心态，想通过线性回归预测一下博客的粉丝走向和数量，结果翻车了。虽然场景用错地方，但是整个实战方法用在身高体重等方面的预测还是有可行性，所以就记录下来了。

来源：百问网_嵌入式Linux wiki_jz2440 新1期视频维基教程 (视频文字版)

作者：韦东山

本文字数：2403，阅读时长：2.5分钟

CPU中还有许多协处理器来协助主处理功能 比如2440有CP0 ~ CP15一共16个协处理器

CP15管理cache mmu 我们启动cache需要操作CP15 协处理器指令 先看硬件结构

@Author：BY Runsen

前言

在前几天，接到一个大学生的作业的爬虫单子，要求采用scrapy爬取链家官方网站新房的数据（3-5页即可，太多可能被封禁ip），网址：https://bj.fang.lianjia.com/loupan/，将楼盘名称、价格、平米数等（可以拓展）数据保存到一个json文件中。

为了50块钱，废话不说就是开干。虽说我不是计算机的，还是一个屌丝大三化工学生。

代码如下：

import requests
import re
import time

imgs_list = []     #设置空列表imgs_list，用来存储所有的页面爬取的图片路径
def download1(page):
    url="https://www.qiushibaike.com/imgrank/page/"+str(page)+"/"    #设置请求网址
    headers={"User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.198 Safari/537.36"}    #设置请求头
    html=requests.get(url,headers=headers).text   #伪装浏览器对url进行请求,并将请求的文本内容赋值给html
    regex1='<div class="thumb">.*?<img src="(.*?)" alt.*?</div>'   #设置正则匹配规则，匹配图片的路径
    img_list=re.findall(regex1,html,re.S)    #re.S为单行匹配，必须放
    imgs_list.extend(img_list)    #imgs_list扩展img_list
    return imgs_list    #返回图片列表

if __name__=="__main__":
    for i in range(1,14):   #共计有13页图片，故遍历13次
        download1(i)     #执行下载图片的函数download1
    print(imgs_list)
    j=1     #
    for img in imgs_list:
        headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.198 Safari/537.36"}  # 设置请求头
        html1=requests.get(url="https:"+str(img),headers=headers).content
        with open(r"F:\PPT图片\糗事百科\{}.jpg".format(j),"wb") as f:   #以写入方式打开F盘PPT图片下面路径为糗事百科的文件夹，并设置为f
            f.write(html1)    #将图片存入f
            j=j+1
            print("{}下载成功".format(img))

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新一代报表工具FastReport VCL 6.6更新发布，添加了FastReport VCL和FastRepot For Lazarus的许多重要新功能。

FastReport VCL v6.6最新版：https://www.fastreportcn.com/download.html

在此版本中，我们在“Data Tree”数据树中添加了“变量和函数”选项卡的过滤。

现在可以将所有面板隐藏在“Data Tree”数据树中。

前一段时间，一直在忙框架方面的工作，偶尔也会帮业务同学去优化优化使用TensorFlow的代码，也加上之前看了dmlc/relay，nnvm的代码，觉得蛮有意思，也想分别看下TensorFlow的Graph IR、PaddlePaddle的Graph IR，上周五，看代码看的正津津有味的时候，看到某个数据竞赛群里面讨论东西，不记得具体内容，大概说的是框架的代码实现， 有几位算法大佬说看底层源码比较麻烦，因为比较早从框架，这块代码通常都还能看，问题都不大，和群里小伙伴吹水了半天之后，感觉是可以写篇如何看TensorFlow或者其他框架底层源码的劝退文了。

当地时间8月31日，美国防部在推特上发布了最后一位离开阿富汗的美军士兵照片，并配文称：“最后一名离开阿富汗的美国士兵：克里斯·多纳休少将，空降指挥官，于2021年8月30日登上一架C-17运输机，结束了美国在喀布尔的任务。”（The last American soldier to leave Afghanistan: Maj. Gen. Chris Donahue, commanding general of the @82ndABNDiv, @18airbornecorps boards an @usairforce C-17 on August 30th, 2021, ending the U.S. mission in Kabul.）