Five convenient and easy-to-use Python automation scripts

Compared to everyone who has heard words such as automated production lines and automated offices, machines can complete various tasks on their own without human intervention, which greatly improves work efficiency.

There are various automation scripts in the programming world to complete different tasks.

In particular, Python is very suitable for writing automated scripts because its syntax is simple and easy to understand, and it has a rich third-party tool library.

This time we use Python to implement several automation scenarios, which may be used in your work.

1. Automatically read web news

This script can capture text from web pages and then automatically read it by voice. This is a good choice when you want to listen to news.

The code is divided into two parts. The first is to crawl the web page text through a crawler, and the second is to read the text aloud through a reading tool.

Required third-party libraries:

Beautiful Soup - classic HTML/XML text parser, used to extract crawled web page information

requests - easy to use in reverse Tian's HTTP tool, used to send requests to web pages to obtain data

Pyttsx3 - Convert text to speech, and control the rate, frequency and speech

import pyttsx3
import requests
from bs4 import BeautifulSoup
engine = pyttsx3.init('sapi5')
voices = engine.getProperty('voices')
newVoiceRate = 130 ## Reduce The Speech Rate
engine.setProperty('rate',newVoiceRate)
engine.setProperty('voice', voices[1].id)
def speak(audio):
engine.say(audio)
engine.runAndWait()
text = str(input("Paste articlen"))
res = requests.get(text)
soup = BeautifulSoup(res.text,'html.parser')
articles = []
for i in range(len(soup.select('.p'))):
article = soup.select('.p')[i].getText().strip()
articles.append(article)
text = " ".join(articles)
speak(text)
# engine.save_to_file(text, 'test.mp3') ## If you want to save the speech as a audio file
engine.runAndWait()

2. Automatically generate sketches

This script can convert color pictures into pencil sketches, which has good effects on portraits and scenery.

And it only takes a few lines of code to generate it with one click, which is suitable for batch operations and is very fast.

Required third-party libraries:

Opencv - computer vision tool that can achieve diversified image and video processing, with Python interface

""" Photo Sketching Using Python """
import cv2
img = cv2.imread("elon.jpg")
## Image to Gray Image
gray_image = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
## Gray Image to Inverted Gray Image
inverted_gray_image = 255-gray_image
## Blurring The Inverted Gray Image
blurred_inverted_gray_image = cv2.GaussianBlur(inverted_gray_image, (19,19),0)
## Inverting the blurred image
inverted_blurred_image = 255-blurred_inverted_gray_image
### Preparing Photo sketching
sketck = cv2.divide(gray_image, inverted_blurred_image,scale= 256.0)
cv2.imshow("Original Image",img)
cv2.imshow("Pencil Sketch", sketck)
cv2.waitKey(0)

3. Automatically send multiple emails

This script can help us send emails in batches at regular intervals. The email content and attachments can also be customized and adjusted, which is very practical.

Compared with email clients, the advantage of Python scripts is that they can deploy email services intelligently, in batches, and with high customization.

Required third-party libraries:

Email - used to manage email messages

Smtlib - sends emails to the SMTP server, which defines an SMTP client session object , this object can send emails to any computer with an SMTP or ESMTP listening program on the Internet

Pandas - a tool for data analysis and cleaning

import smtplib
from email.message import EmailMessage
import pandas as pd
def send_email(remail, rsubject, rcontent):
email = EmailMessage()## Creating a object for EmailMessage
email['from'] = 'The Pythoneer Here'## Person who is sending
email['to'] = remail## Whom we are sending
email['subject'] = rsubject ## Subject of email
email.set_content(rcontent) ## content of email
with smtplib.SMTP(host='smtp.gmail.com',port=587)as smtp:
smtp.ehlo() ## server object
smtp.starttls() ## used to send data between server and client
smtp.login("deltadelta371@gmail.com","delta@371") ## login id and password of gmail
smtp.send_message(email)## Sending email
print("email send to ",remail)## Printing success message
if __name__ == '__main__':
df = pd.read_excel('list.xlsx')
length = len(df)+1
for index, item in df.iterrows():
email = item[0]
subject = item[1]
content = item[2]
send_email(email,subject,content)

4. Automated data exploration

Data exploration is the first step in a data science project. You need to understand the basic information of the data to further analyze the deeper value.

Generally, we will use tools such as pandas and matplotlib to explore data, but we need to write a lot of code ourselves. If we want to improve efficiency, Dtale is a good choice.

Dtale is characterized by generating automated analysis reports with one line of code. It combines the Flask backend and React frontend to provide us with an easy way to view and analyze Pandas data structures.

We can use Dtale on Jupyter.

Required third-party libraries:

Dtale - Automatically generate analysis reports

### Importing Seaborn Library For Some Datasets
import seaborn as sns
### Printing Inbuilt Datasets of Seaborn Library
print(sns.get_dataset_names())
### Loading Titanic Dataset
df=sns.load_dataset('titanic')
### Importing The Library
import dtale
#### Generating Quick Summary
dtale.show(df)

##5 , Automatic desktop prompts

This script will automatically trigger windows desktop notifications to prompt important matters, such as: You have been working for two hours and it’s time to take a break

We can set fixed time prompts, such as Every 10 minutes, 1 hour, etc

The third-party library used:

win10toast - a tool for sending desktop notifications

from win10toast import ToastNotifier
import time
toaster = ToastNotifier()
header = input("What You Want Me To Remembern")
text = input("Releated Messagen")
time_min=float(input("In how many minutes?n"))
time_min = time_min * 60
print("Setting up reminder..")
time.sleep(2)
print("all set!")
time.sleep(time_min)
toaster.show_toast(f"{header}", f"{text}", duration=10, threaded=True)
while toaster.notification_active(): time.sleep(0.005)

Summary

The automation functions that Python can achieve are very rich. If you can be "lazy" in demand scenarios, you may want to try it.

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