Python Development Services : Pros & Cons

Python is a popular programming language known for its simplicity, readability, and versatility. It is an interpreted language that is executed line by line rather than compiled. This makes writing and testing code more accessible, reducing turnaround time, and we get the app quickly.

Python can be used for various applications, including web development, data analysis, artificial intelligence, automation, and web scraping. Python has considerable community support which conducts good virtual events. Python is one of the popular events that happen around the world.

Django, Flask, FastAPI, Cherrypy, etc., are popular Python frameworks widely used for Python application development. Various libraries can be used in any framework to speed up development.

What type of applications can be developed in Python?

“Building a scalable application using Python is impossible” is a myth.

Many popular applications across different domains are built using Python. Let’s see how Python fares in building different kinds of applications.

Web Development:

The most popular application built using Python is Instagram. It supports around 500 million users daily, which scraps the fact that Python needs to be more scalable. Another example in the field of entertainment would be Spotify.

Reddit and Quora are the most sought community platforms, and they are built using Python. Quora was built using the Django framework.

Regarding cloud storage, Dropbox has weight and is built using Python. A few applications built using other tech were later moved to Python, of which Youtube is a good example.

Artificial Intelligence:

Artificial Intelligence is the ability of machines to perform tasks that require human-like intelligence. AI has been around for decades, but recent advances in computing power and neural networks have boosted the adoption of AI.

AI, as a whole, contains many things. Among those are Machine learning, Natural Language processing, deep learning, etc

These days, there are frequent updates in AI; the latest sensation is the emergence of ChatGPT. It took the AI application to a whole new level. One can look at the latest updates by following a website https://paperswithcode.com/. It contains newly published papers, and one can also get the implementation for rapid prototyping.

Data Analysis is a significant part of Data Science, and some libraries ease this analysis like NumPy, Pandas, and Matplotlib. Pandas can connect to databases and read Excel and CSV files. It performs data cleaning and visualizes the same data using matplotlib and Seaborn. Dask is the library that is gaining popularity in data analysis.

Automation:

Python can be helpful in various automation activities like copying content from a website which we call web scraping. It can be performed using frameworks like Scrapy or libraries like Selenium and Beautiful Soup. Selenium can be used as an automation testing tool. It opens a browser using Chrome or firefox, where we can log in to a website and perform tasks.

Say we must perform a task requiring copying files from one location to another. For that, we can set a cron job daily. We can use Python’s OS along with the shuttle library that can perform OS-level operations to copy and delete a file/folder from the system.

Top Python Web Frameworks?

Python frameworks simplify developers’ work as they contain basic things already set up. This pre-defined setup assists Python developers in focusing on core tasks or functionality, thereby improving productivity. Python has two types of frameworks.

1. Micro or Lightweight framework: Good for small and medium-sized applications
2. Complete Stack framework: Good for large-scale application

Below are the most widely used frameworks in Python:

Django:

It is a Fullstack framework and the preferred choice for most organizations and developers as it includes most things by default. Django follows the Model View Controller architecture pattern. Any non-technical person can add or delete data from the app with Django’s inbuilt admin module.

Django developers use the ORM layer to simplify database interactions rather than writing raw SQL queries.

Flask:

Flask is a microframework used for small applications. Unlike Django, Flask does not contain a database abstraction layer. It is a very minimal framework. Developers can use any external package conveniently rather than relying on inbuilt functionalities. For someone who wants to start learning Python to develop applications, Flask can be a perfect starting point.

It is also a popular framework in the data science community to deploy machine learning models in production.

FastAPI:

FastAPI has been gaining popularity recently due to its speed and performance, which is on par with nodejs and go language. FastAPI helped the Python language to overcome the myth that Python is slow in performance compared to other languages.

FastAPI uses the asynchronous nature of Python’s asyncio library to handle many concurrent connections efficiently. Due to its performance, this framework is also gaining popularity in the Data Science community. Many developers are shifting to use FastAPI to build APIs quickly and have other frontend languages of choice.

Python Pros

Ease of Learning:

Python is an easy language to learn. It has a simple syntax. Any non-technical person wanting to start coding. They can take up Python and build applications or perform data analysis quickly.

Large Community and Libraries:

Python is open source with a big community. If one is stuck developing any feature, one can get quick support from the community. Moreover, there might be a possibility that someone already has a solution to the problem. Developers have access to a vast pool of prebuilt libraries, so they must write all the code from scratch. Python has a package management system called Pip.

Rapid Development:

With the ease of writing code, Python helps organizations to create a prototype in a short time. Organizations can leverage to check the adoption of the concept and adapt to any changes very quickly.

Python Cons

Performance:

The simplicity of Python comes with the cost of speed. Since Python is an interpreted language, it executes each line of code step by step. Therefore the performance of Python could be better with other languages. Recent advancements overcome this in the FastAPI, where the performance is comparable with Nodejs and Go language.

Mobile Development:

Python is rarely used for mobile development. There are frameworks like Kivy and BeeWare, but they need to be better established than other languages.

Memory problems:

Python faces the problem of memory leaks; it consumes much memory compared to other languages.

Runtime Errors:

Python supports dynamic variables, meaning a variable that previously held an integer value may hold a string value in the future. This dynamic nature can lead to runtime errors, requiring developers to conduct multiple rounds of testing for any application developed.

Thinkitive – Python Development Services

Python Consulting and Architecture:

Thinkitive can help you with a range of services. We can help design a backend for your website to build a data-heavy project containing complicated computation. We have a team of business analysts who can collaborate with you to understand business needs. We can also provide support and maintenance in the entire software development lifecycle.

Python web Development:

Our skilled Python programmers can develop secure, dynamic, and dependable web applications. We use top Python frameworks, including Django, Flask, CheerPy and Pyramid, to create powerful online applications. The application is tailored to your business needs.

Django Development:

Thinkitive has extensive experience utilizing Django to create exciting web applications. We have a group of highly qualified and experienced Django developers on staff. They help you develop the most lucrative and engaging applications tailored to your company’s requirements.

Flask Web Development:

We offer top-notch Flask web development services. We have the necessary infrastructure, development teams, and novel application-building technologies. We take on all aspects of Flask web development, from basic alterations to sophisticated revamping. We have developed into a leading provider of flask development services thanks to our years of experience in software technology. Our team has provided clients with the best Flask web development services worldwide for over two decades.

Python Mobile Development:

From the backend design of your website to a data-intensive project requiring complex computation, we can assist you with everything. Our business analyst works with you to understand the requirements of your project. We offer upkeep and support through the software development lifecycle.

Automated Testing:

We have expertise in various software testing methods that use automated tools, frameworks, and scripts for testing the product. Test automation shortens the testing life cycle’s regression time and improves quality releases. Developing automated test scripts in languages like Python, C#, Ruby, Java, etc., is a speciality of our software testers.

Python AI/ML Services:

We at Thinkitive offer the best AI & ML development services. We have good expertise in dealing with all kinds of data formats. Our engineers are well-versed in libraries and frameworks such as sci-kit-Learn, TensorFlow, NLTK, and Keras.

Python Migration and Integration:

We have a squad of developers who can assist you with the Python migration of your web application. During migration, developers maintain the application’s compatibility, security, and version updating. Our developers will ensure no data loss during the complete process.