Python is a programming language known for its simplicity and versatility. It’s an interpreted, object-oriented, high-level language with dynamic semantics. What makes Python strong is its built-in, high-level data structures. This makes it a powerful choice for various applications.
The Python interpreter, along with its extensive standard library, is accessible on all major platforms at no cost. Python enhances productivity with its quick edit-test-debug cycle. This is because there is no compilation step. Python promotes modularity and code reuse through modules and packages.
Debugging Python programs is user-friendly because errors result in exceptions, not segmentation faults. And the debugger, written in Python, showcases Python’s introspective capabilities. So, what makes this debugger special?
The debugger inspects variables
Evaluates expressions
Sets breakpoints
Steps through code
Python introduction
Python introduction
Let’s say you’re new to Python and trying to set up the required hardware and software to start practicing. Where do you start? You should have at least 4 GB of RAM for optimal Python performance. Ensure that you have a minimum of 5 GB of disk space for the installation, and consider extra space for libraries and project files. Supported operating systems include Windows (7 and later), MacOS (10.9 and later), and various Linux distributions. There is a different installation process for Windows, MacOS, and Linux, so you need to visit the official Python website and download the appropriate installer for the respective operating system. That said, Linux usually comes with Python pre-installed.
Let’s say you’re new to Python and trying to set up the required hardware and software to start practicing. Where do you start? You should have at least 4 GB of RAM for optimal Python performance. Ensure that you have a minimum of 5 GB of disk space for the installation, and consider extra space for libraries and project files. Supported operating systems include Windows (7 and later), MacOS (10.9 and later), and various Linux distributions. There is a different installation process for Windows, MacOS, and Linux, so you need to visit the official Python website and download the appropriate installer for the respective operating system. That said, Linux usually comes with Python pre-installed.
Basics of Python
- Data types: Python supports various data types to handle different kinds of information. These include integers (int), floating-point numbers (float), and strings.
- Compound data structures: Python provides versatile compound data structures like lists, tuples, and dictionaries. They can efficiently organize and manage data collections.
- Conditionals, loops, and functions: Python includes powerful tools like conditionals, loops, and functions to create structured and dynamic programs.
- Object-oriented programming and external libraries: Python supports object-oriented programming principles and allows for the seamless integration of external libraries, expanding its capabilities and functionality.
Why Python?
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Improved productivity: Python’s straightforward syntax enables developers to achieve more with fewer lines of code, saving time and effort.
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Supportive community: Python has a vast and supportive user community, offerring you extensive documentation, tutorials, and helpful tips to help you master the language.
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Academic significance: Python is used extensively in academia, from early education to advanced research. Python also has applications in diverse STEM fields — from solving equations to simulating scientific phenomena.
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Corporate demand: Python’s versatility makes it a top sought-after skill among job seekers, with high demand in both development and data analysis roles, as reported by recruiters worldwide in 2022.
Python is an ideal choice for building applications in the following realms:
- Web development
- Game development
- Machine learning and artificial intelligence
- Data science and data visualization
- Desktop GUI
- Web scraping applications
- Business applications
- Audio and video applications
- CAD applications
- Embedded applications
Python is an ideal choice for building applications in the following realms:
- Web development
- Game development
- Machine learning and artificial intelligence
- Data science and data visualization
- Desktop GUI
- Web scraping applications
- Business applications
- Audio and video applications
- CAD applications
- Embedded applications
What is Python used for?
What is Python used for?
The following are some of the most popular applications of Python:
- Creating web applications on servers
- Creating workflow in software
- Providing database system connectivity and file-handling capabilities
- Managing big data and complex mathematical tasks
- Providing rapid prototyping and production-ready software development
Some of the companies that use Python are Amazon, Google, IBM, Meta, Uber Technologies, Cisco, Quora, Youtube and more.
The following are some of the most popular applications of Python:
- Creating web applications on servers
- Creating workflow in software
- Providing database system connectivity and file-handling capabilities
- Managing big data and complex mathematical tasks
- Providing rapid prototyping and production-ready software development
Some of the companies that use Python are Amazon, Google, IBM, Meta, Uber Technologies, Cisco, Quora, Youtube and more.
Is Python difficult to learn?
No, Python isn’t difficult to pick up. It’s actually regarded as one of the most user-friendly programming languages. Learning Python may require time and patience. You might face moments of frustration along the way, even if you’re a professional. But we can help you make this learning experience smoother with the courses below. See which ones fit your skill level and time availability.
print("Hello World")
How to learn Python?
If you’ve already started devising a study plan, think about the following priorities first:
- Understand why other beginners encounter difficulties
- Determine your personal motivation
- Learn the basic syntax quickly
- Start working on structured projects
- Tackle Python projects independently
- Challenge yourself with increasingly complex projects
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