


Detailed explanation of the functions and shortcut keys of the PyCharm editor
PyCharm is an integrated development environment (IDE) developed by JetBrains for Python development. PyCharm integrates many functions to make Python development more efficient and convenient. The following will introduce the commonly used functions of PyCharm and the corresponding shortcut keys.
- Code prompts and auto-completion
PyCharm's code prompts and auto-completion functions can help programmers quickly complete the code and reduce duplication of work in the writing process. The shortcut key is Ctrl+Space. - Code Navigation
Locating specific code blocks in large projects is time-consuming and laborious, and PyCharm's code navigation function can help programmers quickly jump to specified lines of code. The shortcut key is Ctrl B. - Code Refactoring
Refactoring is an important part of software development, which can help programmers optimize and reorganize the code structure. PyCharm provides rich refactoring functions, such as renaming, extracting methods, extracting variables, etc. The shortcut key is Shift F6. - Find and replace
PyCharm supports powerful search and replace functions, which can help programmers quickly locate specified content and replace it with new content. The shortcut keys are Ctrl F (find) and Ctrl R (replace). - Debugging
Debugging is an essential step in the development process. PyCharm provides powerful debugging functions, including setting breakpoints, viewing variable values, single-step execution, etc. The shortcut keys are Ctrl F8 (add/remove breakpoints), F9 (continue execution), and F7 (enter function). - Version Control
PyCharm integrates a variety of version control tools, such as Git, SVN, etc., which can facilitate programmers to manage code versions. The shortcut keys are Ctrl K (submit code) and Ctrl T (update code). - Refactoring code
Refactoring is an important step in software development, which can help programmers optimize the code structure and improve code quality. PyCharm provides a variety of refactoring functions, such as renaming, extracting methods, extracting variables, etc. The shortcut keys are Shift F6, Ctrl Alt M, etc. - Code formatting
Good code format can enhance the readability of the code. PyCharm provides a code formatting function that can automatically adjust the indentation, spaces and other formats of the code. The shortcut key is Ctrl Alt L. - Running and debugging
PyCharm can easily run and debug Python programs, supporting a variety of running configurations and debugging options. The shortcut keys are Shift F10 (run the program) and Shift F9 (debug the program). - Collection of Shortcut Keys
In addition to the shortcut keys mentioned above, PyCharm also has a large number of other shortcut keys that can help programmers improve work efficiency. Programmers can learn and use these shortcut keys according to their own usage habits and needs.
In general, PyCharm, as a powerful Python integrated development environment, provides many practical functions and shortcut keys to help programmers develop Python projects more efficiently. Mastering these common functions and shortcut keys can make development work easier and more efficient.
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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.

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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.

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