The Pros and Cons of Python Programming

Python is currently one of the world’s most popular programming languages. It achieved this position due to its powerful features, flexibility, and ease of use. This guide explains the pros and cons of Python and compares it to other languages. It also discusses the situations where Python is one of the best alternatives.

Python is an open source, general purpose programming language. Guido van Rossum developed Python based on the defunct ABC programming language and named it after the Monty Python comedy troupe. Python was designed to be simple, readable, and highly extensible through the use of modules. The first version of Python was released in 1991, and the more fully featured Python 2.0 followed in 2000. Both releases have since been discontinued.

Python 3.0 was introduced in 2008, but is not compatible with earlier releases. Even though Python included the 2to3 upgrade utility, this decision was highly controversial and created significant issues for the user base. Because the transition was so difficult, there is unlikely to be a release 4 of Python. Instead, new minor releases are planned for each year. The Python Software Foundation currently administers Python, and they continue to work on new features and ongoing performance improvements.

Python continues to increase in popularity and is now ranked as one of the top five languages. It is widely used in data science, machine learning, artificial intelligence, and server & web applications. Many web developers use Python alongside external frameworks, including Django and Flask, or third-party libraries. These frameworks include ready-to-use components and are especially useful for web development.

Python uses many of the same concepts, commands, and control structures as other traditional programming languages. But it is different in many respects, and can almost be considered a new programming paradigm. Python promotes flexibility and clear coding design, and code adhering to its principles is said to be “Pythonic”. Here are some of Python’s main characteristics.

• Python is a High-Level Language: High-level languages are more readable. They use meaningful variable names, and have meaningful syntax. No understanding of the underlying operating system is required. In this respect, Python is similar to other programming languages, including JavaScript, Rust, and C++, but is even more clear and legible. At the opposite end of the spectrum is assembly language. Assembly code refers to memory addresses and uses machine language instructions.
• Python Supports Object-Oriented Programming (OOP): Python is an OOP language with support for classes, methods, inheritance, and encapsulation. Unlike Java, Python does not enforce an OOP model and object-oriented design principles are strictly optional. So it is possible to use Python strictly in imperative/procedural mode for short programs and simple utilities. Python now incorporates some features from the functional programming paradigm, but it is not considered a true functional programming language.
• Python is a General-Purpose Language: Domain-specific languages are intended for one specific purpose. For example, SQL is only used to communicate with relational database systems. However, Python is a general-purpose language, and has a wide range of applications.
• Python is an Interpreted Language: Unlike many languages, developers do not have to compile Python into assembly or machine code. When a developer completes a program, they can immediately run it with no intermediate steps. The Python interpreter deciphers each line at run time and executes it. This is different from languages like C/C++, which must be pre-compiled first. Python does have a compilation stage, but it takes place at run time and is hidden from the user. Python compiles a program down to low-level bytecode for the Python Virtual Machine (PVM) to interpret and execute.
• Python is Dynamically-Typed: Variables do not have to be assigned a type, such as “integer”, when they are first used. Python determines the type of variable at run time. Python uses a technique known as “duck typing”. It assigns a type to a variable depending on its value and how it is used. Python allows a variable to change type dynamically over the duration of the program.
• Python Programs are Platform-Independent: Because Python programs are interpreted, they can be ported to any platform. Only the Python Virtual Machine is platform-specific. It translates the Python code into valid machine code for the platform it is running on.

Python is a very distinctive language that has both pros and cons. It is great for certain situations and not as good for others. This section highlights both the advantages and disadvantages of Python.

Python has become widely used and well liked due to a cluster of positive attributes. Here are some of the benefits of Python.

• Ease of Use: Python has a simple, concise, and straightforward syntax. A Python program looks a lot like plain English and is highly readable. This makes Python programs easy to read and debug. Python’s control structures are intuitive and easy to use. In addition, Python is dynamically typed, so there is no requirement to declare the type of each variable. For these reasons, Python is one of the most efficient and productive languages.
• Gentle Learning Curve: Python is one of the simpler languages to learn and is a good option for people learning to program. Programmers switching to Python from languages like C or Java can quickly reach peak efficiency. The Python package contains a useful Integrated Development and Learning Environment (IDLE).
• Versatility: Python is a flexible, general purpose language that fully supports both procedural and object-oriented programming. Due to its built-in and third-party packages, it is suitable for a wide range of tasks. It is dominant in the areas of data science and machine learning. It is also widely used for back-end web development and the Internet of Things (IoT). Even when it is not the best choice for a particular task, it is usually still a viable option. In addition, Python code can be embedded into projects written in other languages, such as C++, and code from other languages can be embedded in Python.
• Efficient for Rapid Development: Because Python is easy to use and does not have to be compiled, programs take less time to develop. Python programs are typically much shorter than equivalent programs in other languages. It is a great choice for quickly constructing prototypes in a rapid software development environment.
• True Portability: A huge Python advantage is that it can be written once and run anywhere. Python does not have to be compiled in advance, so users run a true Python program and not a Python executable. The program is not compiled until it is run, using the platform-specific PVM. This means any Python program can potentially run on any system that supports Python.
• No Compile Process: Python is an interpreted language and programs are automatically compiled at run time. A program can be run as soon as it is written. There is no separate compiler, no time-consuming compilation step, and no opaque compiler errors. Python programs are easy to write, debug, and change incrementally.
• Automatic Memory Allocation: Python does not have pointers and developers do not have to assign free space in memory. Python allocates memory automatically and a garbage collector recycles memory from discarded objects. This means developers do not have to worry about scribblers, memory leaks, invalid pointer references, or the size of each object.
• Extensive Built-In Objects and Libraries: Python has a large number of built-in compound objects including lists, sets, and record-like dictionaries. Each of these objects provides a collection of methods allowing for easy processing. In addition, Python has an extensive library containing tens of thousands of functions. These packages can be used for network communications, web integration, data processing, and hardware interactions. This makes it much faster to write programs because so many of the necessary routines have already been written.
• Third-Party Library Availability: In addition to Python’s extensive built-in library, developers can access many free external libraries. These third-party libraries are easy to import and install using Python’s pip package manager. Packages can be downloaded from the Python Package Index (PyPI) repository. PyPI also allows developers to publish their own packages.
• Open Source and Free to Use: All Python releases are available for free under an open source license. Python can even be modified and re-distributed at no cost. This greatly reduces development costs. For more information about Python licensing, see the Python documentation site.
• Large User Base: Python has a large, active, and passionate community of users. It is easy to find learning materials and other resources, ask questions, search for jobs, hire additional developers, and meet other Python programmers.

Despite its many advantages, Python also has a few notable disadvantages. Here are some of the drawbacks of Python.

• Not Very Fast: Python is much slower than more efficient languages like C and Java. Python is interpreted and dynamically-typed, so the run-time compiler has a lot of work to do. It must constantly validate the type of each variable. This means Python is not the best choice for scenarios where speed is critical.
• Memory Intensive: Python is not optimized to reduce memory. It can use ten times the RAM as a program written in a more frugal language. However, this is partly a tradeoff in return for flexibility and ease of use. In addition, the Python garbage collector cannot gather all discarded resources immediately, which reduces the amount of available memory. Python is not a good choice for memory-constrained environments.
• Harder to Avoid Runtime Errors: Python is not compiled until runtime and is dynamically typed. Therefore, many problems that would otherwise be caught by the compiler do not appear until the program runs. This might include something as simple as a syntax error, but it can include problems like trying to add an integer and a string together.
• Not Much Traction in Mobile or Desktop Applications: Because it is somewhat slow and uses a lot of memory, Python has not made gains in the mobile space. There are some Python development tools for mobile apps, but they are more limited than frameworks for other languages. The situation is a bit better in client desktops, but Python is still not too popular for front-end applications.
• Not Optimized for Database Access: It is more difficult to work with databases in Python than in some other applications. Python lacks a powerful, high quality, easy-to-use interface like the Java Database Connectivity (JDBC). It can still be used if the database reads and writes are relatively straightforward. But it is not the best choice for applications that have complex interactions with a large corporate database.
• No Multithreading Support: Due to its architecture, Python does not support multi-threading. Instead, it uses multiprocessing, where each “thread” runs in a separate Python process. This relies on the oversight of the operating system to schedule and balance the processes, and might not deliver equally good results.
• Prone to Overuse or Misuse: Python’s simplicity is one of its strengths, but this can be a surprising weakness in some situations. Because it is so easy to use, it is often misused for tasks where it is not one of the best alternatives. Python is great for rapid development and prototypes, but this might tempt organizations to overlook proper software development principles.

After reading about the pros and cons of Python, you might still be uncertain whether it is worth learning. On one hand, there are always benefits to learning a new language. But there are at least a dozen other popular languages, so there are also opportunity costs.

Nonetheless, there are some situations where Python is the right choice. There are benefits to learning Python if any of the following statements apply.

• You are Using Agile Development: Python is simple and concise, and it can be used to quickly work out a proof of concept or a trial prototype. Python’s extensive library reduces the number of helper functions to write. It is easy to be fast and productive in Python.
• You Work in Data Science or AI: Python is especially strong in the areas of data science and machine learning. There are many external libraries available for these areas and a strong user base. For machine learning or natural language processing, TensorFlow and PyTorch can be used. NumPy and SciPy are frequently used for data science or scientific computing.
• You Require Portable Tools: Python is a sensible choice for multi-platform utilities. Python is available for Linux, Windows, MacOS, and other popular platforms. It is compiled at run time, so the program can run anywhere on an interpreter optimized for the underlying operating system.
• You Require Test Automation or DevOps Scripts: Python is great for scripting because it is so quick and easy to write, modify, and debug. Speed and memory use are typically not of much concern in a QA environment, so there are no real downsides. Python has a built-in test library named PyUnit. PyUnit integrates smoothly with most test frameworks including pytest. On the DevOps side, Python forms the backbone of many configuration management programs.
• You Require a Back-End for Web Applications: Along with the popular Flask or Django frameworks, Python can provide the server-side engine for web applications. The frameworks provide libraries and templates for most web design tasks.
• You Want a Free and Open Source Language: Python is free to download, use, and modify under a versatile open source license. Python reduces development costs and makes it easy to upgrade to new releases.
• You Want a Fun and Easy to Learn Language: Python has an easy and straightforward syntax. It is a great choice for beginners who are learning how to program. It is also advantageous for professionals who want to dive into development without worrying about fussy programming details. Python’s extensive libraries allow developers to solve problems at a high-level without writing complex low-level routines.
• You Want a Large Developer Community: Python is one of the most popular general-purpose languages. It is versatile and used in a wide number of specialties, so companies are always looking for developers. Google, Facebook, Microsoft, Spotify, Instagram, and Uber all use Python for at least some applications. Python is also a popular development language in start-ups.

It is easy to start using Python. A good place to begin is the Python Beginner’s Guide. The Python Wiki also has a list of tutorials and resources for New or Experienced Programmers.

To run Python on Ubuntu or another Linux distribution, use the command python3. Python is usually already installed on most Linux systems. To download Python for other platforms, see the Python downloads page. For more information about how to use Python on a Linode system, see the Linode guide to Python.

For situations where Python is not the best choice, consider the following options.

• C/C++: These two languages are strong choices when speed, performance, and low memory use are important. They are statically typed and require pre-compilation, so they generate fewer runtime errors. They are often used in game development and embedded systems. Unfortunately, they are considered difficult languages to master.
• JavaScript: Like Python, JavaScript is an interpreted and dynamically-typed language. However, it is the most common language for interactive web pages. JavaScript runs on the client side, and interacts seamlessly with HTML and CSS components. It can be used alongside Node.js for full stack web development. Python is not typically used on the front end, so it is not a good full stack alternative.
• R: R is an alternative to Python for data science. However, it is more geared toward statistical analysis. R is particularly good for data visualization, but it is more complicated and difficult to learn. Python is a simpler and faster option for general purpose data and numerical analysis and has better machine learning capabilities.

This guide discusses the pros and cons of Python, which is more effective in some situations than others. Python is an interpreted, statically-typed programming language that allows both object-oriented and procedural programming. Some of the main benefits of Python include its ease of use, concise and straightforward syntax, and vast libraries. Other Python advantages are its portability, versatility, large user base, and free & open source license.

Some of the disadvantages of Python include its slow speed and heavy memory usage. It also lacks support for mobile environments, database access, and multi-threading. However, it is a good choice for rapid prototyping, and is widely used in data science, machine learning, and server-side web development. For more information about Python, see the official Python site.

More Information

You may wish to consult the following resources for additional information on this topic. While these are provided in the hope that they will be useful, please note that we cannot vouch for the accuracy or timeliness of externally hosted materials.

• Python.org web site
• Python documentation
• Python Package Index (PyPI) repository
• Python Beginner Guide
• Python downloads page
• Django
• Flask
• TensorFlow
• PyTorch
• NumPy
• SciPy
• Python licensing site