


PyCharm Practical Guide: Best Practice Tips for Project Creation
Get started with PyCharm quickly: best practices for project creation, specific code examples are required
Introduction:
PyCharm is a powerful Python integrated development environment ( IDE), which provides many powerful tools and features to help Python developers improve their work efficiency. Project creation is the first step in using PyCharm. The correct way to create a project can lay a solid foundation for our development work. This article will introduce the best practices for PyCharm project creation and provide specific code examples to help readers better understand.
1. Create a project:
Creating a project in PyCharm is very simple. We can click "File->New Project" in the menu bar, then select a directory where the project is saved, then select the project's interpreter, and finally click the "Create" button to complete the project creation. The following is a sample code:
from flask import Flask app = Flask(__name__) @app.route('/') def hello(): return "Hello, World!" if __name__ == '__main__': app.run()
2. Project structure:
After the project is created, we need to organize the structure of the project according to certain specifications. The following is an example of a commonly used project structure:
- myproject/ - app/ - __init__.py - views.py - models.py - tests/ - __init__.py - test_views.py - config.py - requirements.txt - README.md - .gitignore
In this example, we put the application code in a package called "app", and we also have a package called "tests" Packages are used to store test code. In addition, other directories can be added to meet the needs of the project. The root directory of the project usually also contains a configuration file "config.py", a dependency description file "requirements.txt", and a project description file "README.md". To avoid bringing unnecessary files into version control, we can also create a ".gitignore" file to ignore specific files and directories.
3. Code editing:
PyCharm provides many code editing functions to help developers improve code quality and efficiency. The following are some commonly used code editing functions and corresponding code examples:
- Code completion:
PyCharm can automatically complete the code we enter according to the context, and press the Tab key during the input process The code can be completed. For example, after entering "pr" and pressing the Tab key, PyCharm will automatically complete it as "print". - Code Navigation:
We can use the shortcut key Ctrl B (or right-click the mouse) to jump to the definition of the code or return from the definition. For example, we can hover the mouse over the function name and then press the Ctrl key. PyCharm will display the definition of the function and jump to the corresponding location when clicked. - Code Refactoring:
PyCharm provides rich refactoring functions to help us quickly improve the structure and quality of the code. For example, we can use the shortcut key Shift F6 to rename a specific variable, function or class name, and PyCharm will automatically modify all related code. - Code formatting:
PyCharm can help us automatically format code to comply with Python's PEP 8 code style specification. For example, we can use the shortcut key Ctrl Alt L to format the selected code.
4. Code running and testing:
In PyCharm, we can easily run our code, debug and test. The following are some commonly used code running and testing functions and corresponding code examples:
- Code running:
We can right-click the Python file and select "Run" to run our code. For example, with the sample code above, we can start a run server by right-clicking on the file and selecting "Run". - Code debugging:
PyCharm provides powerful code debugging functions. We can use the debugger to check the values of variables and the execution flow of the code. For example, we can add breakpoints in the code and use the shortcut key F9 to start debugging mode. - Unit testing:
PyCharm allows us to easily write and execute unit tests. We can use the shortcut key Shift Ctrl T to quickly create a test file and add test cases. For example, we can write a simple test to verify the functionality of the above example code.
5. Summary:
This article introduces the best practices for creating PyCharm projects and provides some specific code examples to help readers understand better. By following these best practices, we can use PyCharm to develop Python projects more efficiently. Of course, in addition to the functions and practices mentioned in this article, PyCharm has many other powerful functions waiting for us to explore and use. I hope this article can help readers get started with PyCharm quickly and gain a better development experience in daily development.
References:
- PyCharm official documentation: https://www.jetbrains.com/pycharm/
- Flask official documentation: https://flask. palletsprojects.com/
The above is the detailed content of PyCharm Practical Guide: Best Practice Tips for Project Creation. For more information, please follow other related articles on the PHP Chinese website!

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

MantisBT
Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

Dreamweaver Mac version
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

PhpStorm Mac version
The latest (2018.2.1) professional PHP integrated development tool

WebStorm Mac version
Useful JavaScript development tools