Python Practical Information and Mastery
Python is used in many areas thanks to its wide library and community support. For this reason, we wanted to prepare a special guide for you about frequently used functions and practical information. In this guide, we will help you have a faster and more effective learning process by touching on many topics that you may encounter while learning Python.
Basic Concepts and Good Practices
Zen of Python: Use the “import this” command to understand the philosophy of Python. Take care to write readable and simple code.
PEP 8: Follow the PEP 8 document for Python coding standards. It will be a positive situation for you to be familiar and informed with the PEP 8 structure. A consistent code style will increase readability for both you and other developers.
Virtual Environments: Make dependency management easier by creating different virtual environments for your projects.
Version Control: Track and roll back your code changes using a version control system like Git.
Do not forget to learn libraries, Docker, Redis, RESTful API, Git-Github, Cloud concepts along with the programming language and reinforce your knowledge.
While improving your programming language skills, be sure to learn auxiliary concepts and improve your projects. In the following articles, I plan to write more detailed articles about PEP 8, PEP 20, Pythonista and Pythoneer, AWS, DevOPS, Python libraries and concepts.
Lots of Practical and New Projects
Clone projects are used in many courses and training programs while learning a programming language.
Clone projects may make sense in terms of understanding many architectures and structures, but the most important topics in techniques that will improve your programming skills are, be sure to keep your information up to date and follow the agenda.
For example, examine different people’s open source projects and do not forget to read articles. Update your information by following new generation projects.
- Watch different training sets. For example, you have brought yourself to a certain point by watching the training sets of people X, Z. Watch the training sets of people such as Y, N, L by learning about different people, and be sure to record their methods and the practical information they offer you.
- Develop projects. Develop different and independent, simple and practical projects. For example, you can develop many programs and applications on resources such as Youtube, continue to develop the applications and programming you develop by adding new functions and new skills.
- Learn Cloud. If you are working on projects that use Python and Ruby today, you definitely need to learn Cloud technology and database systems. For example, MongoDB, NoSQL database logic, etc.
- Case Studies. Case logic is perhaps one of the most important topics in mastering Python that we mentioned. Case Studies can help you understand the working logic and algorithms of real-life projects and help you develop more professionally.
- Baby Steps. Becoming an expert and becoming more professional is a great topic, but please try to progress step by step. First, understand the topics better and try to discover practical ways. For example, understand Functions, Methods, Tools and libraries well.
- Roadmap. Determine your goal and purpose well and proceed by creating a quality roadmap. Analyze multiple roadmaps and other people’s learning programs.
You can gain basic Network knowledge. Basic network knowledge will be useful to you professionally in many areas.
It is not the most important function or the most important topics. What is important is to learn a programming language at 3 different levels,
The basic topics you should prioritize while learning Python and the advanced topics you can deepen later:
Basic Concepts
Variables and Data Types: Learn basic data types such as numbers, text, lists, dictionaries, and how to use them.
Control Flow: Manage the flow of your program with decision structures (if-else), loops (for, while).
Functions: Define functions to make code snippets reusable.
Modules: Import modules to use code from other Python files.
Error handling: Catch and handle errors with try-except blocks.
Intermediate Topics
Object-Oriented Programming (OOP): Understand OOP concepts such as classes, objects, and inheritance.
File Operations: Read, write, and manipulate files.
Data Structures: Perform operations on data structures such as lists, tuples, sets, and dictionaries.
Algorithms: Know basic algorithms such as sorting and searching.
Libraries: Perform more complex operations using popular libraries such as NumPy, Pandas, and Matplotlib.
Advanced Topics
Decorators: Use decorators to change the behavior of functions.
Generators: Using generators to optimize memory usage.
Asynchronous programming: Learning asynchronous programming concepts to run multiple tasks simultaneously.
Metaprogramming: Using code to generate code.
Combining C and Python: Writing C extensions with CPython.
Learn to use Github and develop simple projects.
What can be done with Python?
Python is one of the most popular programming languages today and its areas of use are quite wide.
Our advice is to specialize professionally in a field. For example, Web Development or Automation, etc.
It is preferred by both beginners and experienced developers thanks to its simple syntax, wide library support and readability. So, what can be done with Python? Here is a comprehensive answer for you:
1. Web Development
Dynamic websites: You can develop complex web applications with powerful web frameworks such as Django and Flask.
API development: You can exchange data between different applications by creating RESTful APIs.
Web scraping: You can use libraries such as BeautifulSoup, Scrapy to collect data from websites.
2. Data Analysis and Visualization
Data cleaning and processing: You can clean and analyze large data sets with the Pandas library.
Statistical analysis: You can do numerical calculations with the NumPy library.
Data visualization: You can create impressive graphics with libraries such as Matplotlib, Seaborn.
Machine learning: You can develop predictive models with libraries like Scikit-learn.
3. Artificial Intelligence and Machine Learning
Deep learning: You can create artificial neural networks with libraries like TensorFlow and PyTorch.
Natural language processing: You can analyze texts with the NLTK library.
Image processing: You can perform operations on images with the OpenCV library.
4. Automation
Automate repetitive tasks: You can automate tedious tasks like file operations, data entry.
Test automation: You can automate software tests by writing scripts.
System management: You can manage systems remotely with protocols like SSH, FTP.
5. Scientific Computations
Simulations: You can use libraries like NumPy and SciPy for scientific calculations and simulations.
Data analysis: You can use libraries like Pandas and Statsmodels to analyze scientific data.
6. Game Development
2D and 3D games: You can develop simple 2D games with the Pygame library.
Complex games: You can develop more complex games by integrating with game engines such as Unity or Unreal Engine.
7. Mobile Application Development
Kivy: You can develop mobile applications for both iOS and Android with the Kivy library.
React Native: You can also develop mobile applications with React Native, a JavaScript-based framework.
8. IoT (Internet of Things)
Sensor data collection: You can collect and analyze sensor data with devices such as Raspberry Pi.
Smart home systems: You can develop home automation systems.
9. Education
Creating educational materials: You can create interactive educational materials with tools such as Jupyter Notebook.
Student projects: You can offer students the opportunity to do projects with Python.
Among the reasons why Python is so popular:
Readable syntax: It has a structure close to English.
Wide library ecosystem: You can find a library that you can use in almost every field.
Platform independence: It can run on different operating systems such as Windows, macOS, Linux.
Open source: It can be used and developed for free.
A large community: There is a large community where you can get help if you have any questions.
Python is an easy-to-learn, fun-to-use, and versatile programming language. In addition to the fields listed above, you can use Python in many areas such as artificial intelligence, data science, cybersecurity, etc.
What should you do to get started?
Learn the basics: Build a solid foundation by learning basic concepts such as variables, data types, control flow, and functions.
Practice: Practice a lot to reinforce what you have learned.
Develop projects: You can make the learning process more fun by developing your own projects.
Join communities: You can learn new things by interacting with other Python users.
