Estimated reading time: 15 minutes
Introduction
With digitization, every organization and individual seeks tools and technologies that make manual tasks redundant. Performing repetitive tasks manually can be monotonous, time-consuming, and boring out even the most dedicated individuals over time. Besides, manually performed tasks are always prone to human error and bias. This is where the Python automation scripts comes in and makes life easier.
The concept of automation is not relatively nascent; instead, it dates back to the 1780s, when the first automatic flour mill was developed. Since then, humans have been trying to automate every other task or procedure. Fast forwarding to the 21st century, automation was witnessed in almost every industry and even homes. Especially for those born in the digital age, automation offers an escape from repeatedly performing redundant tasks. While it sounds intriguing, a lot goes behind automation. This article discusses what automation is all about and how Python can make it easier. We have added a few samples of automated Python scripts that can be run on numerous platforms (Mac, Windows, and Linux).
Table of contents
- Introduction
- Introduction to Python and Automation
- What can you Automate with Python?
- How to Automate Tasks Using Python?
- Top 10 Common Workflows that can be Automated with Python Scripts
- 1. Web Scraping
- 2. Interacting with an API
- 3. Converting a PDF Text File to an Audio File (Text to Speech)
- 4. Downloading Multiple Images in a JPG/PNG Format
- 5. Read a CSV File
- 6. Copying Contents of a Text File to Clipboards
- 7. Send Personalized Emails to Several Recipients
- 8. Cleaning up your Computer
- 9. Check Whether a File is in JSON Format or Not
- 10. Creating a GitHub Repository
- How Much a Python Automation Test Engineer can Earn?
- Conclusion
- Frequently Asked Questions
Introduction to Python and Automation
Python is a popular high-level, interpreted programming language for beginners (as well as experienced programmers). It is used for various applications, including automation, data analysis, and web development. It is well renowned for being readable and having a straightforward syntax, making it simple to learn and use. Given that it is an open-source language with a sizable and engaged community, several algorithms, python libraries, modules, frameworks, and tools are available to those who wish to delve deeper into working with Python.
Regarding automation, Python offers many pre-built features that simplify and facilitate automation processes, like data handling, data manipulation, and even working on regular expressions. In addition, many third-party libraries can automate specific tasks, such as web scraping, email handling, or system administration.
What can you Automate with Python?
Python is a versatile and widely used programming language that almost all programmers are expected to know in the software development domain. Due to its versatility and straightforward syntax, this language is utilized for several automation tasks, including:
- Data Processing: Data processing is automatic data processing and analysis, including data transformation, cleaning, and visualization.
- Web Scraping: Web scraping is the automated collection of information from websites, such as news articles, product prices, or job listings.
- Machine Learning: Python may be used to automate operations related to machine learning, including developing and deploying machine learning models and automating the data preparation process.
- Software Testing: Python is capable of automating software testing, including the execution of automated tests, the creation of test reports, and the analysis of test findings.
- System Administration: Python can automate processes like initiating and terminating services, checking the health of servers, or scheduling backups.
How to Automate Tasks Using Python?
Here are some general steps to follow when automating tasks for Python Projects:
- Identify the Task
Identify the task that you want to automate. It can be anything from downloading files, web scraping, or sending emails to complex tasks like data analysis or machine learning.
- Break Down the Task
Break down the task into smaller subtasks that can be automated using Python. This will help you to identify the required libraries, functions, and workflows.
- Research
Research the libraries and functions you can use to automate the subtasks. Python documentation and community forums are great resources for solving everyday problems.
- Write the Code
Write the Python code to automate the subtasks. This will involve using libraries such as requests for making HTTP requests, BeautifulSoup for parsing HTML, pandas for data manipulation, and many others.
- Test the Code
Test the Python code to ensure it works as expected. This will involve running the code with different inputs and verifying the outputs.
- Run the Code
Once you have tested it, you can run it to automate the task. Depending on the task, you can schedule the code to run at specific intervals using tools like cron on Linux or Task Scheduler on Windows.
- Monitor and Update
Monitor the task to ensure it runs smoothly. If there are any issues or errors, update the code to fix the problem.
Top 10 Common Workflows that can be Automated with Python Scripts
1. Web Scraping
Web scraping is the process of using bots to collect data and content from a website. Web scraping, as opposed to screen scraping, which scrapes pixels from the screen, collects the underlying HTML code and data from databases. The scraper can then replicate the entire website’s content elsewhere.
Python is a preferred programming language for web scraping. A Python library called BeautifulSoup is used for parsing XML and HTML documents to extract data. Other Python libraries that scrape data include Scrapy, Pandas, Requests, and Selenium. They are used alongside BeautifulSoup to make the process more structured.
2. Interacting with an API
API is a shorthand for Application Programming Interface, and API interactions enable communication between data, devices, and applications. These interactions deliver and facilitate data movement in programs and backend systems. Examples of a few API-based interactions are a cloud application engaging with a server, servers pinging one another, or apps interacting with an operating system.
Amongst programming languages like Flask, Node, and Express, Python is among the most loved programming languages for automating API interactions. It offers PyCharm (an integrated development environment), PyTest (Python’s built-in testing framework), and libraries like Requests to automate API interactions.
3. Converting a PDF Text File to an Audio File (Text to Speech)
Python has packages and modules that make text-to-speech simple for folks who are blind or for those of us who would prefer to listen to an audiobook than pick up a paper copy. For this script, you can use PyPDF, a library that can read text from PDF files, and Pyttsx3, a program that turns text into speech.
You can also convert a website into an audio file using these libraries. Specifically, Pyttsx3 in Python 3 takes a PDF input, removes the spaces, and converts the remaining text to audio.
After converting into an audio file, you can also convert the speech back to a text file in a similar manner.
4. Downloading Multiple Images in a JPG/PNG Format
If you wish to download hundreds of images simultaneously, doing so manually will consume much time. This task can be automated with the help of Python and a couple of lines of code. Python uses the concept of Multithreading (executing numerous threads by switching CPU controls between different threads).
You will utilize the following libraries: uuid, requests, and concurrent.futures. Uuid is a built-in library that generates random uuid values (here, image names). Concurrent.futures library leverages the thread pooling functionality. Using them together makes this script one of the most widely used Python automation scripts.
5. Read a CSV File
You can automate reading a CSV file with a Python automation script. This programming language benefits this automation task because it contains a CSV module that implements classes to read and write data (tabular) in a CSV format. Without being aware of the specifics of the CSV format that Excel uses, it enables programmers to say things like, “put this data in the format favored by Excel” or “read data from this file which Excel generated.”
Below are two sample Python automation scripts that can be used to read and retrieve data from a CSV file in real-time.
This code opens the CSV file named “file.csv” in read mode and creates a csv.reader object. The csv.reader object is then used to iterate through each row in the file, and the print() function is used to output each row to the console.
You can also use the csv.DictReader class to read a CSV file as a dictionary. Here’s an example:
6. Copying Contents of a Text File to Clipboards
It happens all too often that you need to copy the contents of a text file to the clipboard for better visualization, whether it’s a log file that someone wants to see, a configuration file that you need to distribute, or even an SSH key. On the command line, accessing the file is simple enough, but opening it in an editor so you may copy and paste takes time you don’t need to squander.
The following copy2clip script is one of the most straightforward Python automation scripts that load the files onto the clipboard using native functionality wrapped in a small amount of Python code. This script utilizes the following libraries: os, sys, platform, and subprocess. It is compatible with both Windows and Mac.
After you import os, system, subprocess, and platform, you define a function called copy_text_file_to_clipboard that takes a file path as input. The function uses the platform.system() method to determine the current operating system and then uses the appropriate command to copy the file’s contents to the clipboard.
7. Send Personalized Emails to Several Recipients
Nobody enjoys sending tens or more individually similar emails. Python programming greatly simplifies this if you work in an area that necessitates it, such as marketing, education, or management, to mention a few. Python provides several modules that can be used to send multiple emails. Some of the most commonly used modules are smtplib, csv, and ssl.
Using only smtplib, you can use one of the Python automation scripts mentioned below.
In this script, you will first import the necessary modules – smtplib, email.mime.text, and email.mime.multipart. You will then set up email credentials (i.e., email address and password), create a message object with the email content (including the subject and body), and specify the recipients’ email addresses.
You can also create a CSV file of your email recipients. After importing csv and datetime, run the following python script.
8. Cleaning up your Computer
If your desktop has become a pile of unorganized files and apps, Python can also help you automate the cleaning task in a matter of a few seconds! To do this, you will need the following modules: os and shutil. These modules enable Python to alter your device’s operating system. You can rename files, create new folders, organize existing folders, and do much more. However, It’s important to be cautious when automating computer cleanup tasks as they can cause unintended consequences. That being said, here’s a basic Python script that uses the os module to automate some common cleanup tasks:
It is one of the simplest Python automation scripts that clean up your computer. You can add additional directories or exclude certain files and folders from deletion. Additionally, you should test this script thoroughly before running it on your computer to avoid unintended consequences.
9. Check Whether a File is in JSON Format or Not
This may be the simplest task that you can automate using Python programming. This Pythin script will read a file, declare it a legitimate JSON file, or perish in agony. Yet, it informs you if the issue is in the file or the program you are attempting to load it into for all intents and purposes. You can check whether a file is in JSON format or not using Python’s json module. Here’s an example code:
Here, we define the JSON file function, which accepts a file path as input and returns the value ‘True’ if the file is in JSON format and False otherwise. If the file is not in proper JSON format, the function throws a ValueError and attempts to load it using the json.load() method. The function returns False when an error is raised. The function returns True if it successfully loaded the file.
10. Creating a GitHub Repository
GitHub is a platform for code collaboration and version control. It enables remote collaboration on projects between you and other people. It is employed for archiving, monitoring, and teamwork on software projects. It makes it simple for developers to cooperate on open-source projects and share code files using repositories.
Using Python, you can automate the process of creating new repositories. You will use the Requests library and module for JSON. Here is a sample code that automates creating a GitHub repository with Python:
After defining all the parameters for your GitHub repository, send the request to create a new repository:
How Much a Python Automation Test Engineer can Earn?
Python Automation Test Engineers may earn more or less money depending on their experience, qualifications, location, and employer. Yet, according to Glassdoor, a Python Automation Test Engineer typically makes roughly $94,000 a year. It’s also important to note that as more businesses use automated testing techniques, demand for Python Automation Test Engineers is anticipated to increase in the upcoming years. This might boost the earning potential of individuals with the requisite training and expertise.
Conclusion
Python is a well-known programming language for automation because of its ease of use, adaptability, and extensive library system. It offers many benefits:
- A beginner-friendly syntax,
- Easy integration capabilities,
- And custom scripts.
Consequently, many operations can be automated, from direct file downloads to sophisticated data analysis, testing, decision-making, creating chatbots, and machine learning.
A well-known online community for fans of data science and machine learning is Analytics Vidhya. They provide a vast array of tools and training courses to assist people in learning Python programming and automating their jobs. Analytics Vidhya can assist with easy and speedy Python automation in several ways, including
- Learning Python Programming: Analytics Vidhya offers various courses, tutorials, and articles to help individuals learn Python programming from scratch. These courses teach basic syntax, data structures, and functions essential for automation.
- Learning Python Libraries: Python has a vast collection specifically designed for automation. Analytics Vidhya offers courses and tutorials on popular libraries like requests, BeautifulSoup, pandas, and others.
- Learning Automation Workflows: Automation requires a clear understanding of workflows and pipelines. Analytics Vidhya provides training and tutorials on automation workflows that can help individuals automate their tasks more efficiently.
Frequently Asked Questions
A. Python is a beginner-friendly programming language widely used in the automation of simple as well as complex tasks. You can use Python to automate:
1. Web scraping tasks,
2. File and folder management,
3. Task scheduling,
4. Social media management,
5. Emailing,
6. Machine learning.
A. As Python is a frequently used language, you can find many useful Python readily available scripts. Some of these are
1. Data visualization scripts,
2. Web scraping scripts,
3. Text filtering Python scripts,
4. Converting a CSV file to an excel script,
5. Audio manipulation scripts, etc.
A. You can automate daily tasks using Python scripts and following the below points.
1. Identify what you want to automate.
2. Break down the task into smaller sub-tasks.
3. Select the Python libraries and modules that you would like to use.
4. Write the script.
5. Schedule the automated task.
A. Although Python is a beginner-friendly language, the degree of automation might vary based on several variables such as task difficulty, experience, proficiency with Python, etc. Writing automation scripts will be more straightforward if you are comfortable with Python programming. Automation is simple for tasks like organizing files on your desktop or sending emails. On the other hand, more strenuous activities, including web scraping and machine learning, can be involved.
