There is a popular question on Zhihu, will Python become a common programming tool for public office in the future?
In the programming world, Python is already a veritable Internet celebrity. A graduate student who studied Chinese language once asked me how to learn Python, because they need to use text analysis in their course papers and use Python to run data. I told him that after two days of reading grammar, you can get started, and if you don’t know how to do it, you can check the information again. 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 that of Java and C++, which provides the possibility for non-programmers to work 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 in all walks of life.
To give more than 10 common examples of office automation, Python can handle them efficiently.
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1. Python processing Excel data
You can use packages such as pandas, xlwings, and openpyxl to perform operations such as addition, deletion, modification, and format adjustment on Excel, and you can even use Python functions to analyze excel data.
read excel form
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 plots to excel sheets
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, and many people have various needs for processing PDF, such as making PDF, getting text, getting pictures, getting tables, etc. There are packages such as PyPDF, pdfplumber, ReportLab, and PyMuPDF in Python that can easily meet these requirements.
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 forms
# extract pdf form
import pdfplumber
with pdfplumber.open("example.pdf") as pdf:
page01 = pdf.pages[0] #Specify the 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 the automatic transmission of emails, which is very convenient.
import smtplib
import email
# Responsible for grouping multiple objects together
from email.mime.multipart import MIMEMultipart
from email.header import Header
# SMTP server, use 163 mailboxes here
mail_host = "smtp.163.com"
# sender email
mail_sender = "******@163.com"
# Email authorization code, note that this is not the email password, how to get the email authorization code, please see the last tutorial 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 a text object 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 the information interacted with the SMTP server
stp.set_debuglevel(1)
# Log in to the mailbox, pass parameter 1: email address, parameter 2: email authorization code
stp.login(mail_sender, mail_license)
# Send email, pass parameter 1: sender email address, parameter 2: recipient email address, parameter 3: change the format of email content to str
stp. sendmail(mail_sender, mail_receivers, mm. as_string())
print("Mail sent successfully")
# Close the SMTP object
stp. quit()
4, Python processing database
The database is our commonly used office application. There are various database driver interface packages in Python, which support the addition, deletion, modification and query of the database, as well as operation and maintenance management. 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 to MySQL
import pymysql
# Open the 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()
# Execute SQL query using execute() method
cursor. execute("SELECT VERSION()")
# Use the fetchone() method to get a single piece of data.
data = cursor. fetchone()
print ("Database version : %s " % data)
# Close the database connection
db. close()
5. Python processes batch files
For many office scenarios, batch processing files has always been a dirty job, and Python can help you out of the sea of suffering. There are many packages in Python that deal with system files, such as sys, os, shutil, glob, path.py, and so on.
Batch delete folders with the same name under different folders
import os, shutil
import sys
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 extensions 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 dot.):')
new_suffix = input('Please enter the suffix you want to change to (need to add 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 controls the mouse
This is the demand of many people, to realize the automatic control of the mouse, and to 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 function and test source code
# Get the 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()#Left double click
except KeyboardInterrupt:
print("\\
")
7. Python controls the keyboard
Similarly, Python can also control the keyboard through pyautogui.
keyboard write
import pyautogui
#typewrite() cannot input Chinese content, and only English can be input if Chinese and English are mixed
#interval set 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 for compression, which requires manual operation.
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 realize operations 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") #Write into the compressed file, the original content in the compressed file will be overwritten
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") ##Decompress 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
The python crawler should be the most popular function, and it is also the main reason for the majority of Python lovers to enter the pit.
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 analyze the content of the captured web pages, which are called analysis packages.
Crawl Baidu home page 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 pictures
from urllib.request import urlretrieve
# Request to get HTML
html = urlopen("http://www.baidu.com/")
# Parse html with BeautifulSoup
obj = bf(html.read(),'html.parser')
# Extract the title from the tags head and title
title = obj.head.title
# Only extract 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']
# Download images using urlretrieve
urlretrieve(logo_url, 'logo.png')
10. Python processing image chart
Image processing and chart visualization involve image processing, which is also the strength of Python. Now Python is also used in cutting-edge fields such as image recognition and computer vision.
The packages for processing images in Python include scikit Image, PIL, OpenCV, etc., and the packages for processing charts include matplotlib, plotly, seaborn, etc.
Black and white the image
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, helping more people in need
Python experience sharing
It is good to learn Python whether it is employment data analysis or doing side jobs to make money, but you still need a learning plan to learn Python. Finally, everyone will share a full set of Python learning materials to help those who want to learn Python!
Python learning route
Here we sort out the commonly used technical points of Python, and summarize the knowledge points in various fields. You can find the corresponding learning resources according to the above knowledge points.
Learning software
Python commonly used development software will save you a lot of time.
Learning video
To learn programming, you must watch a lot of videos. Only by combining books and videos can you get twice the result with half the effort.
100 practice questions
Actual case
Optical theory is useless. Learning programming should not be done on paper, but by hands-on practice, and apply the knowledge you have learned to practice.
Finally, I wish everyone progress every day! !
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