14個(gè) Python 自動(dòng)化實(shí)戰(zhàn)腳本
作者：PythonAI編程
批量文件重命名神器在工作中，我們常常需要對(duì)大量文件進(jìn)行批量重命名，Python幫你輕松搞定！
1.批量文件重命名神器在工作中，我們常常需要對(duì)大量文件進(jìn)行批量重命名，Python幫你輕松搞定！
import os
def batch_rename(path, prefix='', suffix=''):
for i, filename in enumerate(os.listdir(path)):
new_name = f"{prefix}{i:03d}{suffix}{os.path.splitext(filename)[1]}"
old_file = os.path.join(path, filename)
new_file = os.path.join(path, new_name)
os.rename(old_file, new_file)
# 使用示例：
batch_rename('/path/to/your/directory', 'file_', '.txt')2.自動(dòng)發(fā)送郵件通知告別手動(dòng)發(fā)送，用Python編寫定時(shí)發(fā)送郵件的自動(dòng)化腳本。
import smtplib
from email.mime.text import MIMEText
def send_email(to_addr, subject, content):
smtp_server = 'smtp.example.com'
username = 'your-email@example.com'
password = 'your-password'
msg = MIMEText(content)
msg['Subject'] = subject
msg['From'] = username
msg['To'] = to_addr
server = smtplib.SMTP(smtp_server, 587)
server.starttls()
server.login(username, password)
server.sendmail(username, to_addr, msg.as_string())
server.quit()
# 使用示例：
send_email('receiver@example.com', '每日?qǐng)?bào)告提醒', '今日?qǐng)?bào)告已生成，請(qǐng)查收。')3.定時(shí)任務(wù)自動(dòng)化執(zhí)行使用Python調(diào)度庫(kù)，實(shí)現(xiàn)定時(shí)執(zhí)行任務(wù)的自動(dòng)化腳本。
import schedule
import time
def job_to_schedule():
print("當(dāng)前時(shí)間：", time.ctime(), "任務(wù)正在執(zhí)行...")
# 定義每天9點(diǎn)執(zhí)行任務(wù)
schedule.every().day.at("09:00").do(job_to_schedule)
while True:
schedule.run_pending()
time.sleep(1)
# 使用示例：
# 運(yùn)行此腳本后，每天上午9點(diǎn)會(huì)自動(dòng)打印當(dāng)前時(shí)間及提示信息4.數(shù)據(jù)庫(kù)操作自動(dòng)化簡(jiǎn)化數(shù)據(jù)庫(kù)管理，Python幫你自動(dòng)化執(zhí)行CRUD操作。
import sqlite3
def create_connection(db_file):
conn = None
try:
conn = sqlite3.connect(db_file)
print(f"成功連接到SQLite數(shù)據(jù)庫(kù)：{db_file}")
except Error as e:
print(e)
return conn
def insert_data(conn, table_name, data_dict):
keys = ', '.join(data_dict.keys())
values = ', '.join(f"'{v}'" for v in data_dict.values())
sql = f"INSERT INTO {table_name} ({keys}) VALUES ({values});"
try:
cursor = conn.cursor()
cursor.execute(sql)
conn.commit()
print("數(shù)據(jù)插入成功！")
except sqlite3.Error as e:
print(e)
# 使用示例：
conn = create_connection('my_database.db')
data = {'name': 'John Doe', 'age': 30}
insert_data(conn, 'users', data)
# 在適當(dāng)時(shí)候關(guān)閉數(shù)據(jù)庫(kù)連接
conn.close()5.網(wǎng)頁(yè)內(nèi)容自動(dòng)化抓取利用BeautifulSoup和requests庫(kù)，編寫Python爬蟲獲取所需網(wǎng)頁(yè)信息。
import requests
from bs4 import BeautifulSoup
def fetch_web_content(url):
response = requests.get(url)
if response.status_code == 200:
soup = BeautifulSoup(response.text, 'html.parser')
# 示例提取頁(yè)面標(biāo)題
title = soup.find('title').text
return title
else:
return "無法獲取網(wǎng)頁(yè)內(nèi)容"
# 使用示例：
url = 'https://example.com'
web_title = fetch_web_content(url)
print("網(wǎng)頁(yè)標(biāo)題：", web_title)6.數(shù)據(jù)清洗自動(dòng)化使用Pandas庫(kù)，實(shí)現(xiàn)復(fù)雜數(shù)據(jù)處理和清洗的自動(dòng)化。
import pandas as pd
def clean_data(file_path):
df = pd.read_csv(file_path)
# 示例：處理缺失值
df.fillna('N/A', inplace=True)
# 示例：去除重復(fù)行
df.drop_duplicates(inplace=True)
# 示例：轉(zhuǎn)換列類型
df['date_column'] = pd.to_datetime(df['date_column'])
return df
# 使用示例：
cleaned_df = clean_data('data.csv')
print("數(shù)據(jù)清洗完成，已準(zhǔn)備就緒！")7.圖片批量壓縮用Python快速壓縮大量圖片以節(jié)省存儲(chǔ)空間。
from PIL import Image
import os
def compress_images(dir_path, quality=90):
for filename in os.listdir(dir_path):
if filename.endswith(".jpg") or filename.endswith(".png"):
img = Image.open(os.path.join(dir_path, filename))
img.save(os.path.join(dir_path, f'compressed_{filename}'), optimize=True, quality=quality)
# 使用示例：
compress_images('/path/to/images', quality=80)8.文件內(nèi)容查找替換Python腳本幫助你一鍵在多個(gè)文件中搜索并替換指定內(nèi)容。
import fileinput
def search_replace_in_files(dir_path, search_text, replace_text):
for line in fileinput.input([f"{dir_path}/*"], inplace=True):
print(line.replace(search_text, replace_text), end='')
# 使用示例：
search_replace_in_files('/path/to/files', 'old_text', 'new_text')9.日志文件分析自動(dòng)化通過Python解析日志文件，提取關(guān)鍵信息進(jìn)行統(tǒng)計(jì)分析。
def analyze_log(log_file):
with open(log_file, 'r') as f:
lines = f.readlines()
error_count = 0
for line in lines:
if "ERROR" in line:
error_count += 1
print(f"日志文件中包含 {error_count} 條錯(cuò)誤記錄。")
# 使用示例：
analyze_log('application.log')10.數(shù)據(jù)可視化自動(dòng)化利用Matplotlib庫(kù)，實(shí)現(xiàn)數(shù)據(jù)的自動(dòng)圖表生成。
import matplotlib.pyplot as plt
import pandas as pd
def visualize_data(data_file):
df = pd.read_csv(data_file)
# 示例：繪制柱狀圖
df.plot(kind='bar', x='category', y='value')
plt.title('數(shù)據(jù)分布')
plt.xlabel('類別')
plt.ylabel('值')
plt.show()
# 使用示例：
visualize_data('data.csv')11.郵件附件批量下載通過Python解析郵件，自動(dòng)化下載所有附件。
import imaplib
import email
from email.header import decode_header
import os
def download_attachments(email_addr, password, imap_server, folder='INBOX'):
mail = imaplib.IMAP4_SSL(imap_server)
mail.login(email_addr, password)
mail.select(folder)
result, data = mail.uid('search', None, "ALL")
uids = data[0].split()
for uid in uids:
_, msg_data = mail.uid('fetch', uid, '(RFC822)')
raw_email = msg_data[0][1].decode("utf-8")
email_message = email.message_from_string(raw_email)
for part in email_message.walk():
if part.get_content_maintype() == 'multipart':
continue
if part.get('Content-Disposition') is None:
continue
filename = part.get_filename()
if bool(filename):
file_data = part.get_payload(decode=True)
with open(os.path.join('/path/to/download', filename), 'wb') as f:
f.write(file_data)
mail.close()
mail.logout()
# 使用示例：
download_attachments('your-email@example.com', 'your-password', 'imap.example.com')12.定時(shí)發(fā)送報(bào)告自動(dòng)化根據(jù)數(shù)據(jù)庫(kù)或文件內(nèi)容，自動(dòng)生成并定時(shí)發(fā)送日?qǐng)?bào)/周報(bào)。
import pandas as pd
import smtplib
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
def generate_report(source, to_addr, subject):
# 假設(shè)這里是從數(shù)據(jù)庫(kù)或文件中獲取數(shù)據(jù)并生成報(bào)告內(nèi)容
report_content = pd.DataFrame({"Data": [1, 2, 3], "Info": ["A", "B", "C"]}).to_html()
msg = MIMEMultipart()
msg['From'] = 'your-email@example.com'
msg['To'] = to_addr
msg['Subject'] = subject
msg.attach(MIMEText(report_content, 'html'))
server = smtplib.SMTP('smtp.example.com', 587)
server.starttls()
server.login('your-email@example.com', 'your-password')
text = msg.as_string()
server.sendmail('your-email@example.com', to_addr, text)
server.quit()
# 使用示例：
generate_report('data.csv', 'receiver@example.com', '每日數(shù)據(jù)報(bào)告')
# 結(jié)合前面的定時(shí)任務(wù)腳本，可實(shí)現(xiàn)定時(shí)發(fā)送功能13.自動(dòng)化性能測(cè)試使用Python的locust庫(kù)進(jìn)行API接口的壓力測(cè)試。
from locust import HttpUser, task, between
class WebsiteUser(HttpUser):
wait_time = between(5, 15) # 定義用戶操作之間的等待時(shí)間
@task
def load_test_api(self):
response = self.client.get("/api/data")
assert response.status_code == 200 # 驗(yàn)證返回狀態(tài)碼為200
@task(3) # 指定該任務(wù)在總?cè)蝿?wù)中的執(zhí)行頻率是其他任務(wù)的3倍
def post_data(self):
data = {"key": "value"}
response = self.client.post("/api/submit", json=data)
assert response.status_code == 201 # 驗(yàn)證數(shù)據(jù)成功提交后的響應(yīng)狀態(tài)碼
# 運(yùn)行Locust命令啟動(dòng)性能測(cè)試：
# locust -f your_test_script.py --host=http://your-api-url.com14、自動(dòng)化部署與回滾腳本使用Fabric庫(kù)編寫SSH遠(yuǎn)程部署工具，這里以部署Django項(xiàng)目為例：
from fabric import Connection
def deploy(host_string, user, password, project_path, remote_dir):
c = Connection(host=host_string, user=user, connect_kwargs={"password": password})
with c.cd(remote_dir):
c.run('git pull origin master') # 更新代碼
c.run('pip install -r requirements.txt') # 安裝依賴
c.run('python manage.py migrate') # 執(zhí)行數(shù)據(jù)庫(kù)遷移
c.run('python manage.py collectstatic --noinput') # 靜態(tài)文件收集
c.run('supervisorctl restart your_project_name') # 重啟服務(wù)
# 使用示例：
deploy(
host_string='your-server-ip',
user='deploy_user',
password='deploy_password',
project_path='/path/to/local/project',
remote_dir='/path/to/remote/project'
)
# 對(duì)于回滾操作，可以基于版本控制系統(tǒng)實(shí)現(xiàn)或創(chuàng)建備份，在出現(xiàn)問題時(shí)恢復(fù)上一版本的部署。責(zé)任編輯：趙寧寧
來源：
手把手PythonAI編程
