Python is a dynamic scripting programming language, which, due to its versatility, is widely used in developing various mobile, web, and server solutions. Even Google appreciates Python’s flexibility, scalability, and vast possibilities—most of their current services are based on this language.
Advantages often include open-source code (common to many modern scripting languages), clean syntax, many modules in the standard distribution, and a simple but powerful development environment.
Particular solutions are necessary for specific projects; however, Python can be precisely what is needed to implement a ready-made solution or develop a custom one.
What Are Data Types, And Why Are They Important?
The data type is an attribute that tells the computer system strictly how this or that value should be interpreted and how to interpret its value. Thanks to data types, the accuracy of the collected data is ensured. That is, each type of data must be correctly recorded and interpreted.
For example, profiles often indicate first and last name, age, and address. Each of these fields are different types of data and must be correctly displayed in the system so that it “understands” and interprets them.
Python belongs to languages with implicit strict dynamic typing. Implicit typing means that when declaring a variable, its type is not specified (whereas with explicit typing, the variable type is necessarily specified). For languages with dynamic typing, the variable type is determined directly at program execution.
Programming languages with dynamic typing are characterized by the following:
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any variable is a reference;
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the type of a variable is what it refers to;
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the type of a variable can change arbitrarily during code execution when the variable starts to refer to another object
Key Python Data Types
A data type is a set of values and operations on these values. In Python, different data types can be divided into built-in and non-built-in types, which can be used when importing the corresponding modules. Let’s take a closer look at Python’s built-in data types:
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None: NoneType
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Numeric: int, float, complex
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String: str
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Sequence: list, tuple, range
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Binary: bytes, bytearray, memoryview
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Mapping: dict
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Boolean: bool
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Set: set, frozenset
Numeric data type
It is used to hold numeric data. There are three types of numbers: integers, floating point numbers, and complex numbers.
Numbers are created using numeric literals or as the result of built-in functions and operators. Integer literals (including hexadecimal, octal, and binary) yield integers. Numeric literals containing a decimal point or exponent sign produce floating-point numbers. Python fully supports mixed arithmetic, and the int(), float(), and complex() constructors can be used to create numbers of a specific type.
Use:
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int() for signed integers of non-limited length;
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float() for floating precision numbers;
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complex() for complex numbers
String data type
Textual data in Python is handled using str or string objects. Strings are immutable sequences of unicode characters. It is important to remember that the syntax of the text is essential to how it will be interpreted.
For example, string literals that are part of the same expression and have only spaces between them will be converted to a single string. That is, (“hello ” “world”) = “hello world”.
Single or double quotes are used to represent strings. Multiline strings can be represented by triple quotes, “” or “” ”.
Single = ‘Welcome’ or Multi = ” ‘Welcome” ‘
Multiline: “Python is an interpreted high-level programming language for general-purpose programming. ”
or
” ‘Python is an interpreted high-level programming language for general-purpose programming.” ‘
Strings can also be created from other objects using the str constructor.
Sequence types
There are three main types of sequences: lists, tuples, and range objects. Sequences of the same type support comparisons.
For example, Python tuples and lists are compared lexicographically by comparing the corresponding elements. This means that to compare equally, each element must be compared equally, and the two sequences must be of the same type and length.
The key specificity of Python lists is that they can hold a variety of information at the same time, such as numeric and text. A tuple is immutable and write-protected. The range type also represents an immutable sequence of numbers and is typically used to repeat a specified number of times in for loops.
Binary
The principal built-in types for handling binary data are bytes and bytearray.
Bytes objects are immutable sequences of individual bytes. Many major binary protocols are based on ASCII text encoding. Note that bytes objects offer several methods that are only valid when working with ASCII-compatible data and can be related to string objects in several ways.
Only ASCII characters are allowed in byte literals (regardless of the declared encoding of the source code). Any binary values above 127 must be entered into byte literals using the appropriate control sequence.
Bytearray objects are variable analogs of bytes objects.
There is no dedicated literal syntax for bytearray objects; instead, they are always created by calling the constructor.
Creating an empty instance: bytearray()
Create a zero-padded instance with the given length: bytearray(10)
From integer iteration: bytearray(range(20))
Copy existing binary data using buffer protocol: bytearray(b’Hi!’)
Mapping
The mapping object maps hashable values to arbitrary objects. Mappings are mutable objects. Currently, there is only one standard display type, dictionary.
Dictionary keys are almost arbitrary values that are not hashable—that is, values that contain lists, dictionaries, or other mutable types (which are compared by value rather than by object identity)—and can’t be used as keys. The numeric types used for keys obey the usual rules for numeric comparison: if two numbers are compared (for example, 1 and 1.0), they can be used interchangeably.
Dict = {1:’Hi’,2:7.5, 3:’Class’} print(Dict)
Output: {1: ‘Hello’, 2: 7.5, 3: ‘Class’}
Boolean type
Although the boolean data type is often classified as numeric, it is not actually correct. In Python, a boolean value is true or false, which corresponds to the machine logic of understanding 1s and 0s. For example, the expression 1 <= 2 is True, while 0 == 1 is False.
Set
A set is an unordered collection of individual hashable objects. Typical uses include testing membership, removing duplicates from a sequence, or computing mathematical operations such as intersection, union, difference, and symmetric difference.
There are two built-in set types: set and frozenset. The set type is mutable, which means the contents can be changed using methods such as add() and remove(). Because it is a variable, it does not have a hash value and cannot be used either as a dictionary key or as an element of another set. And the frozenset type is immutable and hashable — its contents can’t be changed after creation, so it can be used as a dictionary key or as an element of another set.
Python Programming allows for dynamic, variable possibilities
Python language is constantly changing, and from version to version, new options appear that can significantly change the functioning of programs. Although the category of data types is static at first glance , the variability of their representation requires attention and a high concentration level.
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