There is a popular question on Zhihu: Will Python become a common programming tool for public offices in the future?
In the programming world, Python is already a veritable internet celebrity. Once, a graduate student studying Chinese language asked me how to learn Python, because their course paper needed to use text analysis and use Python to run data. I told him that if you read the grammar in two days, you can start working. If you don’t know how, you can look up the information. Later, this classmate used Python to complete the paper data in half a month.
Therefore, the biggest advantage of Python is that it is easy to learn, and the threshold is much lower than Java and C++, providing non-programmers with the possibility of working with code. Of course, Python can become a popular programming tool, not only because it is easy to learn, but also because Python has thousands of toolkits spread across all walks of life.
Let’s take a dozen common examples of office automation, and Python can handle them efficiently.
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1. Python processing Excel data
You can use pandas, xlwings, openpyxl and other packages to perform operations such as additions, deletions, modifications, and format adjustments on Excel. You can even use Python functions to analyze excel data.
Read excel table
import xlwings as xw
wb = xw.Book() # this will create a new workbook
wb = xw.Book('FileName.xlsx') # connect to a file that is open or in the current working directory
wb = xw.Book(r'C:\path\to\file.xlsx') # on Windows: use raw strings to escape backslashes
Write matplotlib plot to excel table
import matplotlib.pyplot as plt import xlwings as xw fig = plt.figure() plt.plot([1, 2, 3]) sheet = xw.Book().sheets[0] sheet.pictures.add(fig, name='MyPlot', update=True)
2. Python processing PDF text
PDF is almost the most common text format. Many people have various needs for processing PDF, such as making PDF, getting text, getting pictures, getting tables, etc. There are packages in Python such as PyPDF, pdfplumber, ReportLab, and PyMuPDF that can easily meet these needs.
Extract PDF text
import PyPDF2
pdfFile = open('example.pdf','rb')
pdfReader = PyPDF2.PdfFileReader(pdfFile)
print(pdfReader.numPages)
page = pdfReader.getPage(0)
print(page.extractText())
pdfFile.close()
Extract PDF table
# Extract pdf table
import pdfplumber
with pdfplumber.open("example.pdf") as pdf:
page01 = pdf.pages[0] #Specify page number
table1 = page01.extract_table()#Extract a single table
# table2 = page01.extract_tables()#Extract multiple tables
print(table1)
3. Python processing Email
In Python, you can use smtplib with the email library to realize automated transmission of emails, which is very convenient.
import smtplib
import email
# Responsible for gathering multiple objects
from email.mime.multipart import MIMEMultipart
from email.header import Header
# SMTP server, 163 mailbox is used here
mail_host = "smtp.163.com"
# Sender's email address
mail_sender = "******@163.com"
# Email authorization code. Note that this is not the email password. How to obtain the email authorization code? Please see the tutorial at the end of this article.
mail_license = "********"
# Recipient email address, can be multiple recipients
mail_receivers = ["******@qq.com","******@outlook.com"]
mm = MIMEMultipart('related')
# Email body content
body_content = """Hello, this is a test email!"""
# Construct text, parameter 1: text content, parameter 2: text format, parameter 3: encoding method
message_text = MIMEText(body_content,"plain","utf-8")
# Add text objects to the MIMEMultipart object
mm.attach(message_text)
#Create SMTP object
stp = smtplib.SMTP()
#Set the domain name and port of the sender's mailbox, the port address is 25
stp.connect(mail_host, 25)
# set_debuglevel(1) can print out all information interacting with the SMTP server
stp.set_debuglevel(1)
# Log in to the email, pass parameter 1: email address, parameter 2: email authorization code
stp.login(mail_sender,mail_license)
#Send an email, passing parameter 1: sender’s email address, parameter 2: recipient’s email address, parameter 3: change the email content format to str
stp.sendmail(mail_sender, mail_receivers, mm.as_string())
print("Email sent successfully")
#Close SMTP object
stp.quit()
4. Python processing database
Database is our commonly used office application. There are various database driver interface packages in Python to support addition, deletion, modification, query, and operation and maintenance management of the database. For example, the pymysql package corresponds to MySQL, the psycopg2 package corresponds to PostgreSQL, the pymssql package corresponds to sqlserver, the cxoracle package corresponds to Oracle, the PyMongo package corresponds to MongoDB, and so on.
Connection query for MySQL
import pymysql
#Open database connection
db = pymysql.connect(host='localhost',
user='testuser',
password='test123',
database='TESTDB')
# Use the cursor() method to create a cursor object cursor
cursor = db.cursor()
# Use the execute() method to execute SQL queries
cursor.execute("SELECT VERSION()")
# Use the fetchone() method to obtain a single piece of data.
data = cursor.fetchone()
print ("Database version : %s " % data)
#Close database connection
db.close()
5. Python processes batch files
For many office scenarios, batch processing of files has always been a dirty job, and Python can help you get out of the misery. There are many packages in Python that handle system files, such as sys, os, shutil, glob, path.py, etc.
Batch delete folders with the same name in different folders
import os,shutil
importsys
import numpy as np
def arrange_file(dir_path0):
for dirpath,dirnames,filenames in os.walk(dir_path0):
if 'my_result' in dirpath:
# print(dirpath)
shutil.rmtree(dirpath)
Modify file suffixes in batches
import os
def file_rename():
path = input("Please enter the directory you need to modify (format such as 'F:\test'):")
old_suffix = input('Please enter the suffix you need to modify (need to add a dot.):')
new_suffix = input('Please enter the suffix you want to change (need to add a dot.):')
file_list = os.listdir(path)
for file in file_list:
old_dir = os.path.join(path, file)
print('Current file:', file)
if os.path.isdir(old_dir):
continue
if old_suffix != os.path.splitext(file)[1]:
continue
filename = os.path.splitext(file)[0]
new_dir = os.path.join(path, filename + new_suffix)
os.rename(old_dir, new_dir)
if __name__ == '__main__':
file_rename()
6. Python control mouse
This is the need of many people to realize automatic control of the mouse and do some assembly line work, such as software testing.
Python has a pyautogui library that can control your mouse arbitrarily.
Control mouse left-click/right-click/double-click functions and test source code
# Get mouse position
import pyautogui as pg
try:
while True:
x, y = pg.position()
print(str(x) + " " + str(y)) #Output mouse position
if 1746 < x < 1800 and 2 < y < 33:
pg.click()#Left click
if 1200 < x < 1270 and 600 < y < 620:
pg.click(button='right')#right click
if 1646 < x < 1700 and 2 < y < 33:
pg.doubleClick()#Double left click
except KeyboardInterrupt:
print("\
")
7. Python control keyboard
Similarly, Python can also control the keyboard through pyautogui.
Keyboard writing
import pyautogui
#typewrite() cannot input Chinese content. If a mixture of Chinese and English is used, only English content can be input.
#interval sets the text input speed, the default value is 0
pyautogui.typewrite('Hello, world!',interval=0.5)
8. Python compressed file
Compressing files is a common operation in the office. Generally, compression software is used and manual operation is required.
There are many packages in Python that support file compression, allowing you to automatically compress or decompress local files, or package analysis results in memory. For example, zipfile, zlib, tarfile, etc. can operate on compressed file formats such as .zip, .rar, and .7z.
Compressed file
import zipfile
try:
with zipfile.ZipFile("c://test.zip",mode="w") as f:
f.write("c://test.txt") #Writing a compressed file will overwrite the original content in the compressed file.
except Exception as e:
print("The type of the exception object is: %s"%type(e))
print("The content of the exception object is: %s"%e)
finally:
f.close()
unzip files
import zipfile
try:
with zipfile.ZipFile("c://test.zip",mode="a") as f:
f.extractall("c://",pwd=b"root") ##Extract the file to the specified directory, the decompression password is root
except Exception as e:
print("The type of the exception object is: %s"%type(e))
print("The content of the exception object is: %s"%e)
finally:
f.close()
9. Python crawls network data
Python crawler should be the most popular feature and the main reason why Python enthusiasts get involved.
There are many packages in Python that support crawlers, and crawler packages are divided into two types: crawling and parsing.
For example, requests and urllib are network data request tools, that is, capture packages; xpath, re, and bs4 will parse the captured web page content, which is called parsing package.
Crawl Baidu homepage pictures and save them locally
# Import urlopen
from urllib.request import urlopen
# Import BeautifulSoup
from bs4 import BeautifulSoup as bf
#Import the urlretrieve function for downloading images
from urllib.request import urlretrieve
#Request to get HTML
html = urlopen("http://www.baidu.com/")
# Use BeautifulSoup to parse html
obj = bf(html.read(),'html.parser')
# Extract the title from the tags head and title
title = obj.head.title
# Extract only the information of the logo image
logo_pic_info = obj.find_all('img',class_="index-logo-src")
# Extract the link of the logo image
logo_url = "https:" + logo_pic_info[0]['src']
# Use urlretrieve to download images
urlretrieve(logo_url, 'logo.png')
10. Python processing of image charts
Image processing and chart visualization involve image processing, which is also the strength of Python. Nowadays, Python is also used in cutting-edge fields such as image recognition and computer vision.
Packages for processing images in Python include scikit Image, PIL, OpenCV, etc. Packages for processing charts include matplotlib, plotly, seaborn, etc.
Make images black and white
from PIL import Image
from PIL import ImageEnhance
img_main = Image.open(u'E:/login1.png')
img_main = img_main.convert('L')
threshold1 = 138
table1 = []
for i in range(256):
if i <threshold1:
table1.append(0)
else:
table1.append(1)
img_main = img_main.point(table1, "1")
img_main.save(u'E:/login3.png')
Generate statistical charts
import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = (20, 35, 30, 35, 27)
womenMeans = (25, 32, 34, 20, 25)
MenStd = (2, 3, 4, 1, 2)
womenStd = (3, 5, 2, 3, 3)
ind = np.arange(N) # the x locations for the groups
width = 0.35 # the width of the bars: can also be len(x) sequence
p1 = plt.bar(ind, menMeans, width, yerr=menStd)
p2 = plt.bar(ind, womenMeans, width,
bottom=menMeans, yerr=womenStd)
plt.ylabel('Scores')
plt.title('Scores by group and gender')
plt.xticks(ind, ('G1', 'G2', 'G3', 'G4', 'G5'))
plt.yticks(np.arange(0, 81, 10))
plt.legend((p1[0], p2[0]), ('Men', 'Women'))
plt.show()
Summary
In short, Python will become a popular programming language and help more people in need.
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