Python is among the top programming languages that have been used in recent years in designing high-end technologies, such as Machine Learning, artificial intelligence, and data science. Programmers also use Python as their language of choice in developing large-scale applications that scale several products and services. This is why reputed companies hire candidates with good knowledge in coding with Python and other programming skills.

However, despite all these, some python myths can be a concern for aspiring developers. Below are some of the python programming myths you can easily come across.

1. Python is Slow

While Python is admissibly slower than Java and C++, it responds faster than JavaScript, Ruby, and other languages. Python features have specific runtimes and are not slower than other languages. Therefore, using Python for complicated applications saves time, and you’ll be done in a few minutes.

Some years ago, CPUs and memory were costly. However, currently, you can buy better-performing hardware at an affordable price to support programming with Python. Python also supports several programming paradigms, making it functional and imperative.

2. Python is Not Compiled and Only Used for Scripting

Python is generally an interpreted coding language since it falls in this category but is also considered a compiled language like Java and other programming languages. The compiling process is automated, making it difficult to detect, and a separate compiler isn’t required. It mostly compiles on virtual machines.

Python isn’t a scripting language wholly but more of a general-purpose coding language that can be used for scripting. Like most scripting languages, Python doesn’t have networking, regular expression, and exception features. This makes it a reliable and trusted programming language that can automate several tasks.

3. Learning to Code with Python is difficult and Time-consuming

Learning to program with Python is easy as it doesn’t require any prior programming knowledge. However, coding experts are advantaged as they can easily relate to its concepts. Python is a high-level language that can easily be implemented. Most of its syntax is simple mathematical instructions and calculations.

Most statements written in python programs look familiar with the English language as it contains less syntax. That said, learning to code with Python can take between three to six months, depending on your commitment. Besides, there are plenty of learning resources and a large supporting community that is ready to help learners.

4. Python is Not Scalable

Contrary to what most people believe, Python can scale both horizontally and vertically better than other languages. However, there is some confusion about this. The scaling process isn’t automated, thus requires some engineering effort. Scaling Python isn’t a straightforward process as it requires several entities.

For instance, you should make the most from the underlying memory, enhance single systems into distributed form, and more. Nonetheless, with proper architecture, scaling Python won’t be a problem.

5. Coding with Python is Expensive

You are highly mistaken if you think python programming is expensive. Unlike other coding languages, Python is an open-source language that can be downloaded for free from its official website. Python was officially developed in 1991 and is managed under the Python Software Foundation, which guarantees small and large scale users an Open Source License.

However, most of Python’s licenses remain open-source, though others are not. Some contributions, especially those from the General Public License, require users to pay a fee to access customizations added by other developers.

6. Python has Support and Security Issues

Another common myth is that Python isn’t secure, and code lines can easily be hacked. Most programmers believe the assumption that python codes are prone to cyberattacks. In contrast, Python has been used to build networking security systems. The language is also used to develop security testing tools and automation testing, which perform faster compared to others.

On the other hand, Python’s support team is always on standby and ready to assist in case of security issues affecting python programmers. You can contact them anytime, and your details will be kept confidential. Python has also adapted PayPal, eBay, and other highly-secured third-party payment gateways to prove its legitimacy.

7. Python Cannot be used for Big Projects

Just because Python is a simple language doesn’t mean it cannot be applied in big projects. Python has reusable codes and an extensive predefined library, which allow developers to create new codes tailored to suit project needs. Python libraries are also reusable, reducing the amount of time and effort required to write codes. Other languages are quite complicated and take long before a program is designed and implemented. This explains why tech giants, including Google, Facebook, YouTube, and Instagram, use this language.

Major websites / internet services written in Python

The Bottom Line

There is a lot to discover about Python and other programming languages in general. You shouldn’t agree easily to some of these baseless and unproven myths and misconceptions, which often arise during specific situations. That said, if you have some python programming basics, check out this course to learn UX/UI design and advance your skills to also expand your applications to cover front end as well.

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