【BOOK】数据存储—文件存储(TXT、JSON、CSV)

数据存储

文本文件—TXT、JSON、CSV

关系型数据库—MySQL、SQLite、Oracle、SQL Server、DB2

非关系型数据库—MongoDB、Redis

文件打开 open()，第二个参数设置文件打开方式

※ r：只读，文件指针在文件开头

※ rb：二进制只读，文件指针在文件开头

※ r+：读写方式，文件指针在文件开头

※ w：写入，如果文件已存在，则覆盖；若文件不存在，则新建

※ wb：二进制写入，如果文件已存在，则覆盖；若文件不存在，则新建

※ w+：读写，如果文件已存在，则覆盖；若文件不存在，则新建

※ a：追加方式，如果文件已存在，将内容新增再最后；若文件不存在，则新建写入

※ ab：二进制追加方式，如果文件已存在，将内容新增再最后；若文件不存在，则新建写入

※ a+：读写追加，如果文件已存在，将内容新增再最后；若文件不存在，则新建写入

一、TXT文本存储

实例：爬取知乎--热门专题页面

## 爬取知乎热门专题

import requests

from pyquery import PyQuery as pq

url = 'https://www.zhihu.com/special/all'

try:

    headers = {

        'cookie': 'miid=421313831459957575; _samesite_flag_=true; cookie2=1cd225d128b8f915414ca1d56e99dd42; t=5b4306b92a563cc96ffb9e39037350b4; _tb_token_=587ae39b3e1b8; cna=DmpEFqOo1zMCAdpqkRZ0xo79; unb=643110845; uc3=nk2=30mP%2BxQ%3D&id2=VWsrWqauorhP&lg2=U%2BGCWk%2F75gdr5Q%3D%3D&vt3=F8dBxdz4jRii0h%2Bs3pw%3D; csg=f54462ca; lgc=%5Cu5939zhi; cookie17=VWsrWqauorhP; dnk=%5Cu5939zhi; skt=906cb7efa634723b; existShop=MTU4MjI5Mjk4NQ%3D%3D; uc4=id4=0%40V8o%2FAfalcPHRLJCDGtb%2Fdp1gVzM%3D&nk4=0%403b07vSmMRqc2uEhDugyrBg%3D%3D; publishItemObj=Ng%3D%3D; tracknick=%5Cu5939zhi; _cc_=UIHiLt3xSw%3D%3D; tg=0; _l_g_=Ug%3D%3D; sg=i54; _nk_=%5Cu5939zhi; cookie1=AnPBkeBRJ7RXH1lHWy9jEkFiHPof0dsM6sKE2hraCKY%3D; enc=gTfBHQmDAXUW0nTwDZWT%2BXlVfPmDqVQdFSKTby%2BoWsATGTG4yqih%2FJwqG7BvGfl1N%2Bc1FeptT%2BWNjgCnd3%2FX9Q%3D%3D; __guid=154677242.2334981537288746500.1582292984682.7253; mt=ci=25_1; v=0; thw=cn; hng=CN%7Czh-CN%7CCNY%7C156; JSESSIONID=6A1CD727C830F88997EE7A11C795F670; uc1=cookie14=UoTUOLFGTPNtWQ%3D%3D&lng=zh_CN&cookie16=URm48syIJ1yk0MX2J7mAAEhTuw%3D%3D&existShop=false&cookie21=URm48syIYn73&tag=8&cookie15=URm48syIIVrSKA%3D%3D&pas=0; monitor_count=4; isg=BGRk121i5pgW-RJU8ZZzF7W5NWJW_Yhn96AFLn6F6C_yKQXzpgzI9-XL6IExt8C_; l=cBjv7QE7QsWpTNssBOCiNQhfh1_t7IRf6uSJcRmMi_5p21T_QV7OoWj0Ve96DjWhTFLB4IFj7TyTxeW_JsuKHdGJ4AadZ',

        'user-agent': "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.132 Safari/537.36"

    }

    html = requests.get(url, headers=headers, timeout=30).text

except:

    print('爬取失败！')

doc = pq(html)

## pyquery进行页面解析，class属性用 . 匹配

## 调用items()得到一个生成器，for in 进行遍历

items = doc('.SpecialListCard.SpecialListPage-specialCard').items()

for item in items:

    title = item.find('.SpecialListCard-title').text()

    intro = item.find('.SpecialListCard-intro').text()

    with open('special.txt', 'a', encoding='utf-8') as file:

        file.write('\n'.join([title,intro]) + '\n')

        sections = item.find('.SpecialListCard-sections').items()

        for section in sections:

            special = section.find('a').text()

            file.write('\n'.join([special]))

        file.write('\n' + '='*50 + '\n')

    file.close()

运行结果：

二、JSON文件存储

JavaScript Object Notation—JavaScript对象标记

1、用对象和数组表示数据，结构化程度高

※对象—键值对 {key : value}

※数组—[‘a’, ‘b’, ’c’]

—> [{key 1: value1}, {key2 : value2}]

2、JSON库实现JSON文件的读写操作

※读取JSON

       loads() 将字符串类型转换成JSON对象

import json

## JSON对象中的数据需要双引号 "" 包围

str = '''

[{"name":"呱呱", "gender":"男", "age":"5"},

{"name":"嘎嘎", "gender":"女", "age":"22"}

]

'''

## loads() 将字符串类型转换成JSON对象

data = json.loads(str)

print(type(data))  ## <class 'list'>，字符串类型转换成列表类型

print(data[0]['name'])

print(data[0].get('name'))

## 读取JSON文件

import json

with open('data.json', 'r') as file:

    str = file.read()

    data = json.loads(str)

    print(data)

※输出JSON

       dumps() 将JSON对象换成字符串

import json

## JSON对象中的数据需要双引号 "" 包围

data = [{"name":"呱呱", "gender":"男", "age":"5"},

{"name":"嘎嘎", "gender":"女", "age":"22"}

]

## dumps() 将JSON对象换成字符串

with open('data.json', 'w', encoding='utf-8') as file:

    ## indent=2 保存的JSON对象自带缩进

    ## ensure_ascii=False,JSON文件中包含中文

    file.write(json.dumps(data, indent=2, ensure_ascii=False))

三、CSV文件存储【！！可以用excel打开！！】

Comma-Separated Values—逗号分隔值/字符分隔值

纯文本形式存储表格数据

1、写入

import csv

## newline='' ,保证每行之间没有空格

with open('data.csv', 'w', newline='') as csvfile:

    writer = csv.writer(csvfile)

    ## writerow() 每行写入

    writer.writerow(['id', 'name', 'age'])

    writer.writerow(['1001', '呱呱', '20'])

    writer.writerow(['1002', '啦啦', '36'])

    writer.writerow(['1003', '哈哈', '14'])

    ## writerows() 写入多行，效果同上

    writer.writerows([['1004', '卡卡', '6'],['1005', '哇哇', '65']])

import csv

## 字典写入

with open('data1.csv', 'w', newline='') as csvfile:

    fieldnames = ['id', 'name', 'age'] ## 给csv表的表头赋值

    ## DictWriter初始化一个字典写入对象

    writer = csv.DictWriter(csvfile, fieldnames=fieldnames)

    writer.writeheader()

    writer.writerow({'id':'1001', 'name':'呱呱', 'age':20})

    writer.writerow({'id': '1002', 'name': '啦啦', 'age': 36})

    writer.writerow({'id': '1003', 'name': '哈哈', 'age': 14})

## 追加数据

with open('data1.csv', 'a', newline='') as csvfile:

    fieldnames = ['id', 'name', 'age']

    writer = csv.DictWriter(csvfile, fieldnames=fieldnames)

    writer.writerow({'id':'1004', 'name':'八八', 'age':20})

2、读取

import csv

with open('data.csv', 'r') as csvfile:

    reader = csv.reader(csvfile)

    for row in reader:

        print(row)

【实例】知乎--热门专题--存储到excel

## 爬取知乎热门专题

import requests

from pyquery import PyQuery as pq

import csv

url = 'https://www.zhihu.com/special/all'

try:

    headers = {

        'cookie': 'miid=421313831459957575; _samesite_flag_=true; cookie2=1cd225d128b8f915414ca1d56e99dd42; t=5b4306b92a563cc96ffb9e39037350b4; _tb_token_=587ae39b3e1b8; cna=DmpEFqOo1zMCAdpqkRZ0xo79; unb=643110845; uc3=nk2=30mP%2BxQ%3D&id2=VWsrWqauorhP&lg2=U%2BGCWk%2F75gdr5Q%3D%3D&vt3=F8dBxdz4jRii0h%2Bs3pw%3D; csg=f54462ca; lgc=%5Cu5939zhi; cookie17=VWsrWqauorhP; dnk=%5Cu5939zhi; skt=906cb7efa634723b; existShop=MTU4MjI5Mjk4NQ%3D%3D; uc4=id4=0%40V8o%2FAfalcPHRLJCDGtb%2Fdp1gVzM%3D&nk4=0%403b07vSmMRqc2uEhDugyrBg%3D%3D; publishItemObj=Ng%3D%3D; tracknick=%5Cu5939zhi; _cc_=UIHiLt3xSw%3D%3D; tg=0; _l_g_=Ug%3D%3D; sg=i54; _nk_=%5Cu5939zhi; cookie1=AnPBkeBRJ7RXH1lHWy9jEkFiHPof0dsM6sKE2hraCKY%3D; enc=gTfBHQmDAXUW0nTwDZWT%2BXlVfPmDqVQdFSKTby%2BoWsATGTG4yqih%2FJwqG7BvGfl1N%2Bc1FeptT%2BWNjgCnd3%2FX9Q%3D%3D; __guid=154677242.2334981537288746500.1582292984682.7253; mt=ci=25_1; v=0; thw=cn; hng=CN%7Czh-CN%7CCNY%7C156; JSESSIONID=6A1CD727C830F88997EE7A11C795F670; uc1=cookie14=UoTUOLFGTPNtWQ%3D%3D&lng=zh_CN&cookie16=URm48syIJ1yk0MX2J7mAAEhTuw%3D%3D&existShop=false&cookie21=URm48syIYn73&tag=8&cookie15=URm48syIIVrSKA%3D%3D&pas=0; monitor_count=4; isg=BGRk121i5pgW-RJU8ZZzF7W5NWJW_Yhn96AFLn6F6C_yKQXzpgzI9-XL6IExt8C_; l=cBjv7QE7QsWpTNssBOCiNQhfh1_t7IRf6uSJcRmMi_5p21T_QV7OoWj0Ve96DjWhTFLB4IFj7TyTxeW_JsuKHdGJ4AadZ',

        'user-agent': "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.132 Safari/537.36"

    }

    html = requests.get(url, headers=headers, timeout=30).text

except:

    print('爬取失败！')

doc = pq(html)

## pyquery进行页面解析，class属性用 . 匹配

## 调用items()得到一个生成器，for in 进行遍历

with open('data1.csv', 'a', newline='') as csvfile:

    header = ['专题标题', '说明', '子专题']

    writer = csv.DictWriter(csvfile, fieldnames=header)

    writer.writeheader()

    items = doc('.SpecialListCard.SpecialListPage-specialCard').items()

    for item in items:

        title = item.find('.SpecialListCard-title').text()

        intro = item.find('.SpecialListCard-intro').text()

        sections = item.find('.SpecialListCard-sections').items()

        for section in sections:

            special = section.find('a').text()

            writer.writerow({'专题标题': title, '说明': intro, '子专题': special})

csvfile.close()

运行结果：

巴特西

【BOOK】数据存储—文件存储(TXT、JSON、CSV)

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