酷应用

分享几段祖传的 Python 代码，拿来直接使用！

百家作者：AI100 2022-01-27 21:18:08

作者 | 周萝卜

来源 | 萝卜大杂烩

今天分享几段工作生活中常用的代码，都是最为基础的功能和操作，而且大多还都是出现频率比较高的，很多都是可以拿来直接使用或者简单修改就可以放到自己的项目当中

日期生成

很多时候我们需要批量生成日期，方法有很多，这里分享两段代码

获取过去 N 天的日期

import?datetime

def?get_nday_list(n):
????before_n_days?=?[]
????for?i?in?range(1,?n?+?1)[::-1]:
????????before_n_days.append(str(datetime.date.today()?-?datetime.timedelta(days=i)))
????return?before_n_days

a?=?get_nday_list(30)
print(a)

Output:

['2021-12-23', '2021-12-24', '2021-12-25', '2021-12-26', '2021-12-27', '2021-12-28', '2021-12-29', '2021-12-30', '2021-12-31', '2022-01-01', '2022-01-02', '2022-01-03', '2022-01-04', '2022-01-05', '2022-01-06', '2022-01-07', '2022-01-08', '2022-01-09', '2022-01-10', '2022-01-11', '2022-01-12', '2022-01-13', '2022-01-14', '2022-01-15', '2022-01-16', '2022-01-17', '2022-01-18', '2022-01-19', '2022-01-20', '2022-01-21']

生成一段时间区间内的日期

import?datetime

def?create_assist_date(datestart?=?None,dateend?=?None):
????#?创建日期辅助表

????if?datestart?is?None:
????????datestart?=?'2016-01-01'
????if?dateend?is?None:
????????dateend?=?datetime.datetime.now().strftime('%Y-%m-%d')

????#?转为日期格式
????datestart=datetime.datetime.strptime(datestart,'%Y-%m-%d')
????dateend=datetime.datetime.strptime(dateend,'%Y-%m-%d')
????date_list?=?[]
????date_list.append(datestart.strftime('%Y-%m-%d'))
????while?datestart<dateend:
????????#?日期叠加一天
????????datestart+=datetime.timedelta(days=+1)
????????#?日期转字符串存入列表
????????date_list.append(datestart.strftime('%Y-%m-%d'))
????return?date_list

d_list?=?create_assist_date(datestart='2021-12-27',?dateend='2021-12-30')
d_list

Output:

['2021-12-27', '2021-12-28', '2021-12-29', '2021-12-30']

保存数据到CSV

保存数据到 CSV 是太常见的操作了，分享一段我个人比较喜欢的写法

def?save_data(data,?date):
????if?not?os.path.exists(r'2021_data_%s.csv'?%?date):
????????with?open("2021_data_%s.csv"?%?date,?"a+",?encoding='utf-8')?as?f:
????????????f.write("标题,热度,时间,url\n")
????????????for?i?in?data:
????????????????title?=?i["title"]
????????????????extra?=?i["extra"]
????????????????time?=?i['time']
????????????????url?=?i["url"]
????????????????row?=?'{},{},{},{}'.format(title,extra,time,url)
????????????????f.write(row)
????????????????f.write('\n')
????else:
????????with?open("2021_data_%s.csv"?%?date,?"a+",?encoding='utf-8')?as?f:
????????????for?i?in?data:
????????????????title?=?i["title"]
????????????????extra?=?i["extra"]
????????????????time?=?i['time']
????????????????url?=?i["url"]
????????????????row?=?'{},{},{},{}'.format(title,extra,time,url)
????????????????f.write(row)
????????????????f.write('\n')

带背景颜色的 Pyecharts

Pyecharts 作为 Echarts 的优秀 Python 实现，受到众多开发者的青睐，用 Pyecharts 作图时，使用一个舒服的背景也会给我们的图表增色不少

以饼图为例，通过添加 JavaScript 代码来改变背景颜色

def?pie_rosetype(data)?->?Pie:
????background_color_js?=?(
????"new?echarts.graphic.LinearGradient(0,?0,?0,?1,?"
????"[{offset:?0,?color:?'#c86589'},?{offset:?1,?color:?'#06a7ff'}],?false)"
)
????c?=?(
????????Pie(init_opts=opts.InitOpts(bg_color=JsCode(background_color_js)))
????????.add(
????????????"",
????????????data,
????????????radius=["30%",?"75%"],
????????????center=["45%",?"50%"],
????????????rosetype="radius",
????????????label_opts=opts.LabelOpts(formatter="{b}:?{c}"),
????????)
????????.set_global_opts(title_opts=opts.TitleOpts(title=""),
????????????????????????)
????)
????return?c

requests 库调用

据统计，requests 库是 Python 家族里被引用的最多的第三方库，足见其江湖地位之高大！

发送 GET 请求

import?requests


headers?=?{
????'user-agent':?'Mozilla/5.0?(Windows?NT?10.0;?Win64;?x64)?AppleWebKit/537.36?(KHTML,?like?Gecko)?Chrome/96.0.4664.110?Safari/537.36',
??'cookie':?'some_cookie'
}
response?=?requests.request("GET",?url,?headers=headers)

发送 POST 请求

import?requests


payload={}
files=[]
headers?=?{
????'user-agent':?'Mozilla/5.0?(Windows?NT?10.0;?Win64;?x64)?AppleWebKit/537.36?(KHTML,?like?Gecko)?Chrome/96.0.4664.110?Safari/537.36',
??'cookie':?'some_cookie'
}
response?=?requests.request("POST",?url,?headers=headers,?data=payload,?files=files)

根据某些条件循环请求，比如根据生成的日期

def?get_data(mydate):
????date_list?=?create_assist_date(mydate)
????url?=?"https://test.test"
????files=[]
????headers?=?{
????????'user-agent':?'Mozilla/5.0?(Windows?NT?10.0;?Win64;?x64)?AppleWebKit/537.36?(KHTML,?like?Gecko)?Chrome/96.0.4664.110?Safari/537.36',
????????'cookie':?''
????????}
????for?d?in?date_list:
????????payload={'p':?'10',
????????'day':?d,
????????'nodeid':?'1',
????????'t':?'itemsbydate',
????????'c':?'node'}
????????for?i?in?range(1,?100):
????????????payload['p']?=?str(i)
????????????print("get?data?of?%s?in?page?%s"?%?(d,?str(i)))
????????????response?=?requests.request("POST",?url,?headers=headers,?data=payload,?files=files)
????????????items?=?response.json()['data']['items']
????????????if?items:
????????????????save_data(items,?d)
????????????else:
????????????????break

Python 操作各种数据库

操作 Redis

连接 Redis

import?redis


def?redis_conn_pool():
????pool?=?redis.ConnectionPool(host='localhost',?port=6379,?decode_responses=True)
????rd?=?redis.Redis(connection_pool=pool)
????return?rd

写入 Redis

from?redis_conn?import?redis_conn_pool


rd?=?redis_conn_pool()
rd.set('test_data',?'mytest')

操作 MongoDB

连接 MongoDB

from?pymongo?import?MongoClient


conn?=?MongoClient("mongodb://%s:%s@ipaddress:49974/mydb"?%?('username',?'password'))
db?=?conn.mydb
mongo_collection?=?db.mydata

批量插入数据

res?=?requests.get(url,?params=query).json()
commentList?=?res['data']['commentList']
mongo_collection.insert_many(commentList)

操作 MySQL

连接 MySQL

import?MySQLdb

#?打开数据库连接
db?=?MySQLdb.connect("localhost",?"testuser",?"test123",?"TESTDB",?charset='utf8'?)

#?使用cursor()方法获取操作游标?
cursor?=?db.cursor()

执行 SQL 语句

#?使用?execute?方法执行?SQL?语句
cursor.execute("SELECT?VERSION()")

#?使用?fetchone()?方法获取一条数据
data?=?cursor.fetchone()

print?"Database?version?:?%s?"?%?data

#?关闭数据库连接
db.close()

Output:

Database version : 5.0.45

本地文件整理

整理文件涉及需求的比较多，这里分享的是将本地多个 CSV 文件整合成一个文件

import?pandas?as?pd
import?os


df_list?=?[]
for?i?in?os.listdir():
????if?"csv"?in?i:
????????day?=?i.split('.')[0].split('_')[-1]
????????df?=?pd.read_csv(i)
????????df['day']?=?day
????????df_list.append(df)
df?=?pd.concat(df_list,?axis=0)
df.to_csv("total.txt",?index=0)

多线程代码

多线程也有很多实现方式，我们选择自己最为熟悉顺手的方式即可

import?threading
import?time

exitFlag?=?0

class?myThread?(threading.Thread):
????def?__init__(self,?threadID,?name,?delay):
????????threading.Thread.__init__(self)
????????self.threadID?=?threadID
????????self.name?=?name
????????self.delay?=?delay
????def?run(self):
????????print?("开始线程："?+?self.name)
????????print_time(self.name,?self.delay,?5)
????????print?("退出线程："?+?self.name)

def?print_time(threadName,?delay,?counter):
????while?counter:
????????if?exitFlag:
????????????threadName.exit()
????????time.sleep(delay)
????????print?("%s:?%s"?%?(threadName,?time.ctime(time.time())))
????????counter?-=?1

#?创建新线程
thread1?=?myThread(1,?"Thread-1",?1)
thread2?=?myThread(2,?"Thread-2",?2)

#?开启新线程
thread1.start()
thread2.start()
thread1.join()
thread2.join()
print?("退出主线程")

异步编程代码

异步爬取网站

import?asyncio
import?aiohttp
import?aiofiles

async?def?get_html(session,?url):
????try:
????????async?with?session.get(url=url,?timeout=8)?as?resp:
????????????if?not?resp.status?//?100?==?2:
????????????????print(resp.status)
????????????????print("爬取",?url,?"出现错误")
????????????else:
????????????????resp.encoding?=?'utf-8'
????????????????text?=?await?resp.text()
????????????????return?text
????except?Exception?as?e:
????????print("出现错误",?e)
????????await?get_html(session,?url)

使用异步请求之后，对应的文件保存也需要使用异步，即是一处异步，处处异步

async?def?download(title_list,?content_list):
????async?with?aiofiles.open('{}.txt'.format(title_list[0]),?'a',
?????????????????????????????encoding='utf-8')?as?f:
????????await?f.write('{}'.format(str(content_list)))