Python Introduction Notes
Python is a user-friendly, high-level, interpreted programming language. In 1991, Guido van Rossum produced it, and it became available. The Python design philosophy places a strong emphasis on the readability of code, simplicity, and a clear, simple syntax.
Some Key Features of Python include:
- Dynamically typed: Python's variable types were decided upon at runtime in contrast to languages that use static typing, such as C++ or Java.
- Object-oriented: Python supports classes and inheritance as well as object-oriented programming.
- Interpreted: Python code is compile-time, which facilitates testing and debugging.
- Large standard library: A sizable library of included modules and functions in Python's installation make it simple to carry out a variety of routine operations.
- Cross-platform: Linux, Windows, and macOS are just a few of the several operating systems that Python code is compatible with.
- Indentation: Python uses indentation to delimit blocks of code, instead of using curly braces or other symbols.
Some Advantages of Using Python:
- Python has a sizable and active developer community that contributes to access new projects and offers help via forums or mailing lists.
- Python provides both conventional and function programming styles, and it can be used to create large-scale programmes as well as scripts.
- With to libraries like NumPy, Pandas, and Matplotlib, Python is frequently used in data analysis and scientific computing. Python is also a suitable choice for novices because of its simple syntax.
- Python is an interpreted language, which means that you can run code directly from the command line without needing to compile it first.
- Python has dynamic typing, so variables can have their types change while the programme is running.
- Many different businesses, like website designing, computer science, data processing, machine learning, and many others, use Python extensively. Among the well-known Python frameworks as well as technologies are Django, Flask, NumPy, and Pandas.
Python Syntax:
- Python's use of indentation to define code blocks makes it simple to read and comprehend.
- There are built-in data types like strings, lists, and dictionaries, and variables are dynamically typed.
- The procedural, OOPS, and programming paradigms are all supported by Python's sizable standard library.
- Its success has spawned a sizable developer community that produces and distributes libraries as well as packages to increase its functionalities.
Python Variable and Data Types:
- Since variables in Python are dynamically typed, you don't need to explicitly define their type.
- They are made when you give them a value, and over time, their kind may change.
- Python provides a number of built-in data types, including dictionaries, lists, tuples, booleans, strings, integers, and floating-point numbers.
- You can manipulate as well as process the data using a specific set of methods and functions for each type of data.
- It is essential to comprehend variables and data types when writing in Python.
Python Operators:
- The symbols or keywords known as operators in the Python programming language are used to manipulate values or variables.
- Common operators include assignment operators (=, +=, -=), comparison operators (==, !=, >), logical operators (and, or, not), arithmetic operators (+, -, *, /), and membership operators (in, not in).
- If two variables belong to the same memory object, Python's identification operators (is, is not) can be used to determine this.
- To run calculations and work with data in Python, one must have a solid understanding of operators.
Python Numbers:
- Numeric values are represented using numbers, a built-in data type in Python.
- They consist of complex numbers, integers, and floating-point numbers.
- Addition, subtraction, multiplication, and division are just a few of the common mathematical operations that Python provides.
- Other mathematical functions, including trigonometric and logarithmic functions, are also available thanks to the built-in math library.
- Python number manipulation skills are necessary for doing calculations in the sciences and math.
Python String:
- The built-in data type for representing text values in Python is called a string.
- When defining multi-line strings, they can be enclosed in single, double, or triple quotations.
- String manipulation tools like slicing, concatenated, and formatting are all included in a variety of ways in Python.
- In order to process strings in a sophisticated manner, it also enables regular expressions.
- For text processing and information analysis jobs, proficiency with Python's string-handling syntax is required.
Python List, Tuple and Dictionary:
- To store collections of values, Python comes with built-in data structures like lists, tuples, and dictionaries.
- Square brackets are used to define lists, and they can be changed after they are created.
- Parentheses are used to define tuples, and they are immutable.
- Key-value pairs are stored in dictionaries, which are constructed using curly brackets.
- These data structures may be processed and manipulated using a variety of built-in functions as well as methods in Python, which makes them effective instruments for data analysis as well as manipulation.