Python is known for its simple and easy-to-read features, but efficient programming skills can help you achieve twice the result with half the effort. This article summarizes ten time-saving tips shared by senior Python programmers to help you improve Python programming efficiency.
Python is loved by programmers due to its ease of learning, object-oriented features, byte compilation methods, open source and free. It has runtime type checking, comprehensive and fast support, and rich libraries to easily deal with various tasks.
Efficient Python programming skills:
Avoid using semicolons: Semicolons are optional in Python, and using semicolons will actually reduce the readability of the code. Python relies on indentation to distinguish code blocks and keep the code concise and clear.
Select the right code editor: It is crucial to choose a code editor that supports real-time checks of flake8 and PEP8. This can help you discover and correct code style issues in a timely manner and improve code quality. (For editor selection, please refer to my previous article "Python Programmer Common Code Editor")
Follow Python code style:Following the PEP 8 code style guide can significantly improve code readability and save code review and debugging time. Python's design philosophy emphasizes the readability of code.
Good use of help()
Functions: help()
Functions are powerful built-in tools in Python that can quickly view the descriptions of other functions and save time finding documents.
Make full use of libraries: Python has a rich third-party library that can avoid repeated wheel creation. Making good use of various packages on PyPI (Python Package Index) can greatly improve development efficiency. For example, the scikit-image
library can easily achieve image blur, contrast enhancement, and scaling.
Frequent test: Testing each code component may seem time-consuming, but it can detect and fix bugs as early as possible, save post-debugging time, and deepen your understanding of the code. REPL (read-eval-print loop) is a commonly used test method.
Focus on a specific field: Focusing on a specific field, such as computer vision, biological computing or symbolic mathematics, and mastering related libraries (such as SimpleCV, Biopython, SymPy), can give you a deeper understanding Learn Python and solve specific problems efficiently.
Other suggestions:
I hope these tips can help you improve Python programming efficiency! What other tricks do you have to save time? Welcome to share in the comment section!
Python Programming FAQs:
Why is it not recommended to use semicolons in Python? Python's design goal is code readability, and semicolons will reduce readability. Python uses indentation to distinguish code blocks.
How does Python handle code comments? Python uses #
for single-line comments, and uses three single-quotes '''
or three double-quotes """
for multi-line comments.
What time-saving tips do Python programmers have? List comprehensions, zip
functions, multiple assignments, built-in functions and libraries can all save time.
Why is Python considered a high-level language? Python abstracts the underlying details, which are easy for humans to understand and write.
How does Python handle errors and exceptions? Python uses built-in exceptions and error messages, and exceptions can be caught and handled using try/except
blocks.
What is the indentation function in Python? Indentation is part of Python syntax and is used to define code blocks.
How to improve Python programming skills? Practice more, read excellent code, participate in code challenges and hackathons.
What are the best practices for writing Python code? Follow the PEP 8 style guide, write comments, use meaningful variable names, keep functions concise, handle exceptions, and write tests.
How to improve the running speed of Python code? Use built-in functions and libraries, use local variables, use list comprehensions and generator expressions, avoid unnecessary loops, use appropriate data structures, and code analysis.
What mistakes do beginners often make? Do not understand the indentation rules, do not use built-in functions and libraries, do not write comments, do not handle exceptions, do not test code, and do not use Pythonic.
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