Python Programming Language is an interpreted high-level programming language for general-purpose programming. Created by Guido van Rossum and first released in 1991, Python features a dynamic type system and automatic memory management. It supports multiple programming paradigms, including object-oriented, imperative, functional and procedural, and has a large and comprehensive standard library.
Python’s key advantages
Python’s success revolves around several advantages it provides for beginners and experts alike.
Python Programming Language is easy to learn and use
The number of features in the language itself is modest, requiring relatively little investment of time or effort to produce your first programs. The Python syntax is designed to be readable and straightforward. This simplicity makes Python an ideal teaching language, and it lets newcomers pick it up quickly. As a result, developers spend more time thinking about the problem they’re trying to solve and less time thinking about language complexities or deciphering code left by others.
- What Python is used for
The most basic use case for Python is as a scripting and automation language. Python isn’t just a replacement for shell scripts or batch files; it is also used to automate interactions with web browsers or application GUIs or to do system provisioning and configuration in tools such as Ansible and Salt. But scripting and automation represent only the tip of the iceberg with Python.
- “Glue code” in Python Programming Language
Python is often described as a “glue language,” meaning it can let disparate code (typically libraries with C language interfaces) interoperate. Its use in data science and machine learning is in this vein, but that’s just one incarnation of the general idea.
- How Python makes progamming simple
Python’s syntax is meant to be readable and clean, with little pretense. A standard “hello world” in Python 3.x is nothing more than:
Python provides many syntactical elements to concisely express many common program flows. Consider a sample program for reading lines from a text file into a list object, stripping each line of its terminating newline character along the way:
with open(‘myfile.txt’) as my_file: file_lines = [x.strip(‘\n’) for x in my_file]
The with/as construction is a context manager, which provides an efficient way to instantiate an object for a block of code and then dispose of it outside that block. In this case, the object is my_file, instantiated with the open() function. This takes the place of several lines of boilerplate to open the file, read individual lines from it, then close it up.
- How to Upgrade WordPress php Version 5.6 to 7 Beginner Guide
- Beginner Guide to Submit Blogger Sitemap Google Bing and Yahoo
The [x … for x in my_file] construction is another Python idiosyncrasy, the list comprehension. It lets an item that contains other items (here, my_file and the lines it contains) be iterated through, and it lets each iterated element (that is, each x) be processed and automatically appended to a list.
You could write such a thing as a formal for… loop in Python, much as you would in another language. The point is that Python has a way to economically express things like loops that iterate over multiple objects and perform a simple operation on each element in the loop, or to work with things that require explicit instantiation and disposal.
Constructions like this let Python developers balance terseness and readability.
Python’s other language features are meant to complement common use cases. Most modern object types—Unicode strings, for example—are built directly into the language. Data structures—like lists, dictionaries (that is, hashmaps), tuples (for storing immutable collections of objects), and sets (for storing collections of unique objects)—are available as standard-issue items.
- Is Python Programming Language too slow? It doesn’t have to be
One common caveat about Python is that it’s slow. Objectively, it’s true. Python programs generally run much more slowly than corresponding programs in C/C++ or Java. Some Python programs will be slower by an order of magnitude or more.
Why so slow? It isn’t just because most Python runtimes are interpreters rather than compilers. It is also due to the fact that the inherent dynamism and the malleability of objects in Python make it difficult to optimize the language for speed, even when it is compiled. That said, Python’s speed may not be as much of an issue as it might seem, and there are ways to alleviate it.
I hope this tutorial of what is Python Programming Language is very helpful to all of you if you like this please share it with your friends! and if you have any question regarding this post then you can ask me in below comment box.