Python is incredibly popular because it's easy to learn, versatile, and has thousands of useful libraries for data science. But one thing it is not is fast.
In this article, we will see the reasons Why is Python so popular despite being so slow. Python is a high-level, object-oriented, dynamic, and multipurpose programming language i.e multi-paradigm language. Python's syntax, dynamic typing, and interpreted nature make it an excellent scripting language.
The python language is one of the most accessible programming languages available because it has simplified syntax and not complicated, which gives more emphasis on natural language. Due to its ease of learning and usage, python codes can be easily written and executed much faster than other programming languages.
Python is unusually slow at recursion, doing a recursive Fibonacci gets infeasibly slow at just fib(30) Python function calls are slow — contributing to the recursion issue. Java w/o JIT optimization can be really slow, even slower than Python for some things.
It is Easy to Use and Learn:
The first and topmost reason why python is the most popular programming language is due to the fact that it is easy to use and learn. Due to this ease, it is considered as the most fresher-friendly programming language. Python is one of the most approachable programming languages available.
Julia is becoming more popular lately.
Python has been a popular programming language for many years, but there is speculation that Julia may gradually replace it. Julia is a newer language that has been gaining popularity due to its speed and flexibility.
Yes, Python is worth the investment of your time and money. As one of the most popular coding languages, Python enjoys tremendous versatility, giving Python developers the freedom to enter a wide range of applications from software development, machine learning, data science, and web development.
If you're looking for a general answer, here it is: If you just want to learn the Python basics, it may only take a few weeks. However, if you're pursuing a data science career from the beginning, you can expect it to take four to twelve months to learn enough advanced Python to be job-ready.
In general, it takes around two to six months to learn the fundamentals of Python. But you can learn enough to write your first short program in a matter of minutes. Developing mastery of Python's vast array of libraries can take months or years.
On average, it can take anywhere from five to 10 weeks to learn the basics of Python programming, including object-oriented programming, basic Python syntax, data types, loops, variables, and functions.
Exploit Writing: Python is a general-purpose programming language and used extensively for exploit writing in the field of hacking. It plays a vital role in writing hacking scripts, exploits, and malicious programs.
Besides the given reasons, Python is the most loved programming language used by hackers since it's an open-source language which means that hackers can use the stuff that other hackers have previously made. Besides being free and high-level language, it also comes with a bank of genius support.
Python and Java are two of the most popular and robust programming languages. Java is generally faster and more efficient than Python because it is a compiled language. As an interpreted language, Python has simpler, more concise syntax than Java. It can perform the same function as Java in fewer lines of code.
Conclusion. Generally, C is preferred for tasks that require to be executed quickly, and hence the programmer has to deal with minimum runtime. The cost paid while using C is the absence of functionalities provided by other languages. Hence C is the fastest language.
C++ is often considered the hardest language, but it's not the only challenging one. Other programming languages that are categorized as unusually difficult are Prolog, LISP, Haskell, and Rust.
In terms of speed, Java is faster than Python as it is a compiled language. It takes less time to execute a code. Python is an interpreted language and it determines the type of data at run time which makes it slower comparatively.
For sure yes , if you have the desired skills and knowledge . No one will ever care about the age , there are plenty of jobs available in the field of python . Beside this you can also go for freelancing as an option.
Python is used in many different areas. You can search for a job as a Python developer, data scientist, machine learning specialist, data engineer, and more. These jobs are interesting and in-demand. And, like other Python jobs, they pay good salaries.
3 months is enough if you want to start with a basic job. A basic job only requires you to know the basics of python. After learning the basic python programming, you will have to learn some advanced topics to be professional in it and have a job. Making projects is also important.
Learn Python in 3 hours is a fast-paced, action-packed course that maximizes your time; it's designed from the ground up to bring you from zero to hero in the shortest time. The course is based on many years of Python development experience in both large enterprises and nimble startups.
Therefore, the best age to learn Python is as early as possible. Parents can enroll their children for learning Python anywhere from as young as elementary school students to high school students meaning ages ranging from 5 - 18 years old.
If you study 2 to 3 hours a day, you will be able to learn python fairly quickly, even without a programming background. Python is a simple language that commonly used as a language to teach programming. At Boston University, freshman engineering and computer science students learn python as a first language.
The answer to how much time it takes to learn python depends on the time you spent learning. Ask yourself how much time you can dedicate to learning and practicing Python. Generally, it is recommended to dedicate one hour every day to Python learning.
Python can be regarded as the future of programming languages. As per the latest statistics, Python is the main coding language for around 80% of developers. The presence of extensive libraries in Python facilitates artificial intelligence, data science, and machine learning processes.
Python has become a staple in data science, allowing data analysts and other professionals to use the language to conduct complex statistical calculations, create data visualizations, build machine learning algorithms, manipulate and analyze data, and complete other data-related tasks.