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
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)))
以上就是萝卜哥平时用的最多的代码片段，希望对你有所帮助
好了，这就是今天分享的全部内容，
