今天分享幾段工作生活中常用的代碼，都是最為基礎(chǔ)的功能和操作，而且大多還都是出現(xiàn)頻率比較高的，很多都是可以拿來直接使用或者簡單修改就可以放到自己的項目當(dāng)中
日期生成
獲取過去 N 天的日期
import datetimedef 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_daysa = 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’]
生成一段時間內(nèi)的日期
import datetimedef create_assist_date(datestart = None,dateend = None): # 創(chuàng)建日期輔助表 if datestart is None: datestart = ‘2016-01-01’ if dateend is None: dateend = datetime.datetime.now().strftime(‘%Y-%m-%d’) # 轉(zhuǎn)為日期格式 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: # 日期疊加一天 datestart+=datetime.timedelta(days=+1) # 日期轉(zhuǎn)字符串存入列表 date_list.append(datestart.strftime('%Y-%m-%d')) return date_listd_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’]
保存數(shù)據(jù)到CSV
保存數(shù)據(jù)到 CSV 是太常見的操作了，分享一段我個人比較喜歡的寫法
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(“標(biāo)題,熱度,時間,url”) 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(”) 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(”)
帶背景顏色的 Pyecharts
Pyecharts 作為 Echarts 的優(yōu)秀 Python 實現(xiàn)，受到眾多開發(fā)者的青睞，用 Pyecharts 作圖時，使用一個舒服的背景也會給我們的圖表增色不少
以餅圖為例，通過添加 JavaScript 代碼來改變背景顏色
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=”: {c}”), ) .set_global_opts(title_opts=opts.TitleOpts(title=””), ) ) return c
requests 庫調(diào)用
據(jù)統(tǒng)計，requests 庫是 Python 家族里被引用得最多的第三方庫，足見其江湖地位之高大！
發(fā)送 GET 請求
import requestsheaders = { ‘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)
發(fā)送 POST 請求
import requestspayload={}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)
根據(jù)某些條件循環(huán)請求，比如根據(jù)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 操作各種數(shù)據(jù)庫
操作 Redis
連接 Redis
import redisdef redis_conn_pool(): pool = redis.ConnectionPool(host=’localhost’, port=6379, decode_responses=True) rd = redis.Redis(connection_pool=pool) return rd
寫入 Redis
from redis_conn import redis_conn_poolrd = redis_conn_pool()rd.set(‘test_data’, ‘mytest’)
操作 MongoDB
連接 MongoDB
from pymongo import MongoClientconn = MongoClient(“mongodb://%s:%s@ipaddress:49974/mydb” % (‘username’, ‘password’))db = conn.mydbmongo_collection = db.mydata
批量插入數(shù)據(jù)
res = requests.get(url, params=query).json()commentList = res[‘data’][‘commentList’]mongo_collection.insert_many(commentList)
操作 MySQL
連接 MySQL
import MySQLdb# 打開數(shù)據(jù)庫連接db = MySQLdb.connect(“localhost”, “testuser”, “test123”, “TESTDB”, charset=’utf8′ )# 使用cursor()方法獲取操作游標(biāo) cursor = db.cursor()
執(zhí)行 SQL 語句
# 使用 execute 方法執(zhí)行 SQL 語句cursor.execute(“SELECT VERSION()”)# 使用 fetchone() 方法獲取一條數(shù)據(jù)data = cursor.fetchone()print “Database version : %s ” % data# 關(guān)閉數(shù)據(jù)庫連接db.close()
Output:
Database version : 5.0.45
本地文件整理
整理文件涉及需求的比較多，這里分享的是將本地多個 CSV 文件整合成一個文件
import pandas as pdimport osdf_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)
多線程代碼
多線程也有很多實現(xiàn)方式，我們選擇自己最為熟悉順手的方式即可
import threadingimport timeexitFlag = 0class 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 (“開始線程：” + self.name) print_time(self.name, self.delay, 5) print (“退出線程：” + 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# 創(chuàng)建新線程thread1 = myThread(1, “Thread-1”, 1)thread2 = myThread(2, “Thread-2”, 2)# 開啟新線程thread1.start()thread2.start()thread1.join()thread2.join()print (“退出主線程”)
異步編程代碼
異步爬取網(wǎng)站
import asyncioimport aiohttpimport aiofilesasync 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, “出現(xiàn)錯誤”) else: resp.encoding = ‘utf-8’ text = await resp.text() return text except Exception as e: print(“出現(xiàn)錯誤”, e) await get_html(session, url)
使用異步請求之后，對應(yīng)的文件保存也需要使用異步，即是一處異步，處處異步
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)))
好了，今天的分享到這啦，希望對你們有所收獲??！
