Boost Workplace Efficiency with Python Automation Scripts

Many professionals spend countless hours on repetitive tasks that add little value. This article shows how Python can automate such work, offering ready-to-use scripts for system entry, Excel processing, Word resume extraction, operational monitoring, and email sending.

System Entry Automation

When you repeatedly input data into a system, a simple script can mimic clicks and fill forms.

import time
from splinter import Browser

def splinter(url):
    browser = Browser()
    browser.visit(url)
    time.sleep(5)
    browser.find_by_id('idInput').fill('xxxxxx')
    browser.find_by_id('pwdInput').fill('xxxxx')
    browser.find_by_id('loginBtn').click()
    time.sleep(8)
    browser.quit()

if __name__ == '__main__':
    websize = 'https://mail.163.com/'
    splinter(websize)

Similarly, a basic game‑idle script can control the mouse.

import win32api, win32con, time, random

def move_click(x, y, t=0):
    win32api.SetCursorPos((x, y))
    win32api.mouse_event(win32con.MOUSEEVENTF_LEFTDOWN | win32con.MOUSEEVENTF_LEFTUP, x, y, 0, 0)
    if t == 0:
        time.sleep(random.random()*2+1)
    else:
        time.sleep(t)
    return 0

move_click(30, 30)

def resolution():
    return win32api.GetSystemMetrics(0), win32api.GetSystemMetrics(1)

Excel Automation

To merge multiple Excel files into one, use xlrd to read and xlsxwriter to write.

# -*- coding: utf-8 -*-
import xlrd
import xlsxwriter

def getsheet(fh):
    return fh.sheets()

def getnrows(fh, sheet):
    return fh.sheets()[sheet].nrows

def getFilect(file, shnum):
    fh = open_xls(file)
    table = fh.sheets()[shnum]
    num = table.nrows
    for row in range(num):
        rdata = table.row_values(row)
        datavalue.append(rdata)
    return datavalue

Or concatenate dataframes directly:

for i in var_list:
    df_0 = data[['var_1','var_2','var_3','var_4',i]][data[i]=='信息']
    df_0['month'] = date_replace(i)
    df_0 = df_0[['var_1','var_2','var_3','var_4','var_5']]
    li.append(df_0)
writer = pd.ExcelWriter(r'C:\Users\mapping.xlsx')
df = pd.concat(li)
df.to_excel(writer,'Sheet1',index=False,header=None)

Adding charts:

import xlsxwriter

data = [20,45,26,18,45]
workbook = xlsxwriter.Workbook("temp.xlsx")
worksheet = workbook.add_worksheet("data")
worksheet.write_column('A1', data)
chart = workbook.add_chart({'type':'line'})
chart.add_series({
    'values':'=data!$A1:$A6',
    'name':'Chart Name',
    'marker':{'type':'circle','size':8,'border':{'color':'black'},'fill':{'color':'red'}},
    'data_labels':{'values':True},
    'trendline':{'type':'polynomial','order':2,'name':'Trendline','forward':0.5,'backward':0.5,'display_equation':True,'line':{'color':'red','width':1,'dash_type':'long_dash'}}
})
worksheet.insert_chart('c1', chart)
workbook.close()

Word Key‑Info Extraction

For thousands of resumes, extract fields like name, gender, ethnicity using regex on the docx’s XML content.

import re

def get_field_value(text):
    value_list = []
    m = re.findall(r"姓 名(.*?)性 别", text)
    value_list.append(m)
    m = re.findall(r"性 别(.*?)学 历", text)
    value_list.append(m)
    m = re.findall(r"民 族(.*?)健康状况", text)
    value_list.append(m)
    return value_list

Automated Operation Monitoring

Collect daily KPI data and store results automatically, either from offline files or directly from databases.

from impala.dbapi import connect
from impala.util import as_pandas
import pandas as pd

conn = connect(host='host',port=21050,auth_mechanism='PLAIN',user='user',password='password')

df_data = pd.read_excel('temp.xlsx')
rows = []
for index, row in df_data.iterrows():
    rows.append('(' + '"' + str(row['case_id']).replace('nan','null') + '"' + ',' + '"' + str(row['birth_date']) + '"' + '),')

a = '''
INSERT into table
(case_id, birth_date)
values '''
for i in rows:
    a += i
a = a[:-1]
cursor1 = conn.cursor()
cursor1.execute(a)
cursor1.close()
conn.close()
print('成功导入数据至数据库...')

Running SQL scripts:

import sql
sql_end = sql.sql_end
cursor1 = conn.cursor()
for i in sql_end.split(';'):
    cursor1.execute(i)
cursor1.close()
conn.close()
print('程序运行结束，请执行下一步。')

Automated Email Sending

Use the email and smtplib modules to compose HTML bodies, embed images, attach files, and send them programmatically.

from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
from email.mime.image import MIMEImage
import smtplib

msg = MIMEMultipart()

df_text = '''<html><body><p>Hi all,</p><p>This is a test email, see attachment.</p><p>See the figure below:</p></body></html>'''
msgtext = MIMEText(df_text, 'html', 'utf-8')
msg.attach(msgtext)

image = open('temp.jpg','rb')
msgimage = MIMEImage(image.read())
msg.attach(msgimage)

msgfile = MIMEText(open('temp.xlsx','rb').read(),'base64','utf-8')
msgfile["Content-Disposition"] = 'attachment; filename="temp.xlsx"'
msg.attach(msgfile)

email_host = ''
sender = ''
password = ''
receiver = ''

try:
    smtp = smtplib.SMTP(host=email_host)
    smtp.connect(email_host)
    smtp.starttls()
    smtp.login(sender, password)
    smtp.sendmail(sender, receiver.split(','), msg.as_string())
    smtp.quit()
    print('发送成功')
except Exception:
    print('发送失败')

These examples demonstrate how Python can turn tedious manual work into automated workflows, freeing time for higher‑value activities.