It is worth asking the question: Why do we program in Python?
The answer is not simple, because programming in this language has many very different aspects and applications.
Here are some advantages of this language:
- Python has a simple, very economical syntax, and basic elements can be written quickly
- It is an interpreted language, so in many cases changes to an application can be implemented much faster
- It is a very efficient language, and it is not without reason that it is used for processing large portions of data (big data, data science)
- The language is easily integrable with other languages in many different projects (web, mobile, others)
- Python is a language that is being rapidly adopted by many companies, creating a need to hire programmers who can use this language at various skill levels
- Python has very many applications: Arduino, Raspberry Pi, Cybersecurity, IoT, Marketing, Science, Statistics, QA, machine learning and deep learning, AI algorithms, web programming
- Python in its latest version is a powerful language; many well-known applications have been written in Python: Dropbox, Google, Spotify, Netflix
- Python has a great many extensions
- This language is well documented, it is a cult language, and there is a very broad community of programmers of this language
In one sentence, it is worth undertaking the effort to learn Python, because it provides many benefits.
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Python Language Fundamentals
Introduction to Python:
- Introduction - Python language and environment
- Built-in types
- Scalar types
- Sequential and iterable types
- Data structures: lists, arrays
- Data structures: tuples, dictionaries, and sets
- Control statements
Functions
- Creating functions
- Parameterized functions
Data Processing in Python:
- Vectors, matrices, and other arrays
- Data frames
- String processing
Modules in Python:
- Overview of available language extensions
- Importing and using modules
Creating Your Own Software:
- Modules
- Namespaces in modules
- Program modularization
Object-Oriented Programming:
- Object-oriented programming paradigms
- Creating objects, Classes
- Abstraction
- Operator overloading
- Application of classes
- Examples of object-oriented applications
Data Structures:
- XML language
- JSON data sources
Exception Handling in Python
- Catching exceptions
- Propagation
- Exception handling tools
Multithreaded Programming in Python
- Introduction to multithreaded programming in CPython
- The thread, threading, and concurrent.futures modules
- Thread synchronization
- Parallel execution of functions with different arguments
Metaprogramming:
- Metaclasses
- Type extensions
- Decorators
Dr. Eng. Marcin Albiniak
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Frequently Asked Questions
Is Python suitable for large-scale enterprise applications?
Yes, Python is used by major companies like Google, Netflix, Spotify, and Dropbox for large-scale systems. While it may be slower than compiled languages for certain tasks, its extensive ecosystem of optimized libraries and ease of integration with other technologies make it highly effective for enterprise use.
How long does it take to learn Python for a complete beginner?
A beginner can learn Python fundamentals in a few weeks of dedicated study, thanks to its simple and readable syntax. Reaching a level where you can build practical applications typically takes two to three months, though mastering advanced topics like multithreading and metaprogramming requires longer practice.
What makes Python different from other programming languages?
Python stands out for its highly readable, economical syntax that allows developers to write less code to accomplish more. It is an interpreted language enabling faster development cycles, and its massive ecosystem of extensions covers everything from web development and data science to IoT and artificial intelligence.
Can Python be used for mobile app development?
While Python is not the primary choice for mobile development, frameworks like Kivy and BeeWare allow building cross-platform mobile applications in Python. Python is more commonly used for backend services and APIs that power mobile apps, as well as for prototyping and data processing tasks.