Performance Evaluation of Python
Python is known for its classic properties and versatile usage. Let's evaluate its performance in areas like development, automation, data extraction, and more.
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Join For FreeIn a class, some students are multi-talented and score well in all the spheres — sports, academics, and debates. There are some students, who are only good in sports and not in academics. And we have a lot of students who are good at none. So where does this smart, handsome boy named Python belong to?
We need to evaluate the performance while looking at the different capabilities and accomplishments before making a performance card. So let's check the calculations.
Introduction
Python is a smart and intellectual language and is one of the most favored ones. It is really easy to write scripts and develop some good, captivating web development. Python is one of the most loved programming languages and lays down a healthy competition in almost all spheres:
- Creating bots
- Scraping the web
- Machine learning (ML), data visualization, and analysis
- Web development
- Mobile apps development
Let’s get started!
Web Development
Python gels very well with its other frameworks like Django, Flask, and others. Also, it plays a fairly important role in building server-side web apps and can be integrated with any front end. On the other hand, Python does not participate directly in web browsers. Python and Django help make some beautiful web apps and present the best of functionalities together. They provide a defined structure, support database interactions, and all this with a minimal setup.
Apart from these, there are some well-known libraries that help with Python for web development. Some popular ones include Requests, Pillow, PyMongo, etc.
Automation and Scripting
Python holds its position when it comes to automation and scripting with its simplified approach. You can write some amazing Python scripts to develop the best of automation with minimal coding. Python enables its developers to download, automate, and extract the data on the web easily and strategically. Python developers can compose some innovative Python scripts to swiftly and securely automate the web.
For instance, there was a project where we built an application that would increase the play count of tracks on the Apple music store. This involved logging into the store, fetching OTP, entering into the sign-in page, and then waiting for the track to finish to move on to the next ones. There are a lot of things to note here:
- There's heavy interaction with the web pages, like identifying the sign-in button, switching to the login iFrame, waiting for the OTP, and then logging in. After that, move to the track page, click on the play button, wait for the song to complete, and then switch to another one.
- The OTP retrieval mechanism involved the integration of the third-party API storing OTP into the database so that our bot can read it and mark it as read.
Web Scraping
Web scraping is a technique of strategically importing the data from the web by implying different technical tactics. Python provides easy access to data through its web libraries and support. It is ideal for the following use cases:
- Scraping websites with bare-bones structures and sites that are complex to parse
- Regular expression (regex) to extract data
- Selenium scripts to automate activities on the web
- Bot development
- ETL
Python has a great set of libraries that work wonders for extracting data from the web, including Beautiful Soup and Scrapy.
Data Science and ML
The world is changing with the many new normals. Everything is now getting automated and two things that got the maximum benefit out of this are data science and ML.
Python is indistinguishably used for data extraction, data manipulation, analysis, and implementing complex algorithms. Also, it is used for data parsing and visualization by making use of its beautiful libraries like NumPy, SciPy, scikit-learn, etc.
Python grabs its position among the winners for data-intensive and machine learning applications by making use of libraries such as NumPy, Pandas, Matplotlib, and Seaborn.
Conclusion
Now that we have evaluated various domains where Python has established its importance and prominence, it's time to declare the results. As we can deduce, Python is super talented and is used in almost all domains of web development, automation, and scripting.
Additionally, Python is very cooperative and gels well with its peer libraries. As such, we give Python the title “jack of all trades” and the star of the programming languages.
Opinions expressed by DZone contributors are their own.
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