Introduction Set data structure in Python is an unordered collection data type that is iterable, mutable, and has no duplicate elements. The major advantage of using a set, as opposed to a list, is that it has a highly optimized method for checking whether a specific element is contained in [...]
Introduction Dictionary data structure in Python is an unordered collection of data values, used to store data values like a map. Dictionary holds key:value pair. Each key-value pair in a Dictionary is separated by a colon :, whereas each key is separated by a ‘comma’. Dictionaries and lists share the [...]
Introduction Tuple is similar to a List. The difference between the two is that we cannot change the elements of a tuple once it is assigned whereas, in a list, elements can be changed. Creating a Tuple A tuple is created by placing all the items (elements) inside parentheses (), [...]
Comprehensions provide us with a short and concise way to construct new sequences using sequences which have been already defined. Common applications are to make new sequences where each element is the result of some operations applied to each member of another sequence or iterable, or to create a subsequence [...]
Introduction List data structure in Python is a compound data types often referred to as sequences. Lists need not be homogeneous. A single list may contain data types like Integers, Strings, as well as Objects. Lists are mutable, and hence, they can be altered even after their creation. List in [...]
Introduction Generators are used to create iterators. Simply speaking, a generator is a function that returns an object (iterator) which we can iterate over (one value at a time). If a function contains at least one yield statement (it may contain other yield or return statements), it becomes a generator [...]
Introduction Python has an interesting feature called decorators to add functionality to an existing code. This is also called metaprogramming as a part of the program tries to modify another part of the program at compile time. Even though it is the same underlying concept, we have two different kinds [...]
Introduction Operators are special symbols in Python that carry out arithmetic or logical computation. The value that the operator operates on is called the operand. Operator falls into below categories: Arithmetic Operator Comparison Operators Assignment Operator Logical Operator Membership Operator Identity Operator Bitwise Operator Arithmetic Operators Arithmetic operators are [...]
The decimal module provides support for fast correctly-rounded decimal floating point arithmetic. It offers several advantages over the float datatype: Decimal is based on a floating-point model but also provide an arithmetic that works in the same way as the arithmetic that people learn at school. Decimal numbers can be [...]
Every value in Python has a datatype. Since everything is an object in Python programming, data types are actually classes and variables are instance (object) of these classes. This post list the commonly used native data types supported in Python. Numeric Data Numeric data types supported in Python 3xx are [...]