Programming languages are the basis of the web development process. Selecting the perfect language is crucial for the efficient development of revenue-generating websites and web applications.
Table of Content
- A Brief Glance At Python
- Pros and Cons of Using Python Language
A Brief Glance At Python
Python is an interpreted, high-level programming language that focuses on ease of use and accessibility. It is a general-purpose programming language that is used for developing small to large-scale applications. It features dynamic semantics, and a flexible language construct (syntax rules of a programming language), making it extremely easy to read and modify. Python is thus perfect for creating web applications.
Python is one of the most used object-oriented programming languages. It gives developers virtual objects that can be used as building blocks. Each object has its own sets of properties, such as shape, size, and type of behavior, that can be inherited and derived from each other.
Python can also be used for writing scripts for web browsers. Its smooth learning curve and performance make it apt for quick prototyping and quick updates. It is also a top choice for data analysts and ML scientists for the robust libraries it offers.
Some common features of both the languages are –
- Multi-paradigm – Both are multi-paradigm languages, supporting Object-oriented, procedural, functional (or declarative), and imperative programming paradigms.
- High-level languages
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|Type||Object-oriented programming language||Considered both programming and scripting languages|
|General Usage||It provides good support for Machine Learning, Data Analytics, math-intensive websites and applications||Used for native mobile, desktop and web applications. Hybrid and cross-platform application development is also supported|
|Usage in web development||Mainly used for backend development of websites and web apps||Used for designing the frontend of web pages|
|Numeric Data Types||Python has various numerical data types such as – Integer, Complex, and Floating-point||It has only floating-point for numerical data types.|
|Defining properties||Python uses getter and setter functions for defining an attribute||Attributes are used for defining properties of an object|
|Inheritance Model||Python has a class-based inheritance model||It uses prototypes for inheritance|
|Encoding Format||ASCII code encryption is used for Python files unless explicitly specified||The UTF-16 encoding format is used as it provides no support for byte manipulation|
|Data-conversion||Strongly typed – Allows no implicit data conversion||Weakly typed- Allows data conversion automatically|
|Modules||Batteries-included- has numerous modules and in-built libraries||Does not include too many modules|
3. Uses Prototypes
4. Implements Async Processing
Pros and Cons of Using Python Language
Why should you use Python? What are some advantages of Python programming language for web app development?
1. Fast and Highly Productive
Python is extremely fast and employs productivity-enhancing practices. You can do a lot more with fewer lines of code lines making it a great choice for quick prototyping. Python not only saves a lot of time but also reduces your company’s costs. That is why we prefer Python in our projects. Get Python web development services with us to save time and costs.
2. Easy To Use
Python is an extremely easy programming language to use. Using high-level keywords and simple, uncluttered syntax, Python offers readability and understandability.
If you are switching to Python, you will be able to grasp it quickly and start coding in a matter of days. With a huge online community, you can easily get solutions to any error or hindrance you might face.
3. Machine Learning and Data Sciences
Python has emerged as the best programming language for implementing Artificial Intelligence and Machine Learning paradigms. It offers a concise and simple coding environment for implementing complex ML algorithms.
Python also offers an extensive collection of libraries such as Pandas or Keras for Information Retrieval systems, Data Visualization, and Natural Language Processing. This can help you reduce coding time and develop reliable intelligent systems quickly.
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Some drawbacks of using Python are-
1. Python web apps are slow
Python is an interpreted language, so you may find that it is comparatively slower than other popular languages. But Python can handle most websites and the speed is only an issue for time-intensive apps that require a huge memory.
2. Multi Threading not supported
One of the main issues for Python developers is it’s inability to support multi-threading. Python has this limitation because of the Global Interpreter Lock (GIL), a mutex that restricts the availability of resources for threads, allowing only one thread to execute at a time.
Since single-threaded programs are much slower in comparison, Python apps take a serious performance hit. Instead of multi-threading, you can implement multi-processes in Python. Multiprocessing will allow you to allocate separate resources to each process, but this can slow down your website.
3. Not suitable for Mobile App Development
Python is not native to the mobile environment. Although many tools can extend the functionalities of the language, many developers would prefer a better-suited coding language for developing native mobile apps. Moreover, Android and iOS technology don’t support Python as an official programming language.
- Dynamic websites
- Cross-platform applications
- Mobile development
- Game app development
- Web servers
Python programming language on the other hand should be preferred when working with –
- Database driven apps
- Scalable applications
- Artificial Intelligence and Machine Learning
- Deep learning or Data Analysis
- Rapid prototyping
- Ad hoc programming
- GUI applications
- Neural Networks
Frequently Asked Questions
Is Python good for machine learning?
Machine Learning is a relatively new technology with a vast scope of implementation in numerous fields. With its simplicity, flexibility, and scalability, Python is a preferred programming language for ML. With access to extensive libraries, data scientists and programmers are able to perform math-intensive statistics and data analytics easily with Python code.