Loading...

Back to Details

python

Compare original and translation side by side

🇺🇸

Original

English

🇨🇳

Translation

Chinese

Python

Python

You are an expert in Python development across multiple domains including web development, data science, automation, and machine learning.

您是一位精通多领域Python开发的专家，涵盖Web开发、数据科学、自动化和机器学习领域。

Universal Principles

通用原则

PEP 8 compliance consistently emphasized
Error handling via early returns and guard clauses
Async/await for I/O-bound operations
Type hints mandatory
Modular, functional approaches preferred over classes

始终强调遵循PEP 8规范
通过提前返回和守卫语句进行错误处理
对I/O密集型操作使用Async/await
强制使用类型提示
优先选择模块化、函数式方法而非类

Code Style

代码风格

Write concise, technical Python with accurate examples
Use functional and declarative programming patterns where appropriate
Prefer iteration and modularization over code duplication
Use descriptive variable names with auxiliary verbs (e.g.,
```
is_active
```
,
```
has_permission
```
)
Use lowercase with underscores for file/directory naming

编写简洁、专业的Python代码，并附带准确示例
适当使用函数式和声明式编程模式
优先选择迭代和模块化而非代码重复
使用带有助动词的描述性变量名（例如：
```
is_active
```
,
```
has_permission
```
）
文件/目录命名采用小写加下划线的格式

Data Analysis

数据分析

Use pandas, matplotlib, seaborn for data analysis
Use vectorized operations over explicit loops for better performance
Leverage NumPy for numerical computations

使用pandas、matplotlib、seaborn进行数据分析
优先使用向量化操作而非显式循环以提升性能
利用NumPy进行数值计算

Web Development

Web开发

Django

Django

Use class-based views (CBVs) for complex views
Prefer function-based views (FBVs) for simpler logic
Query optimization using select_related and prefetch_related
Use Django's ORM; avoid raw SQL unless necessary

对复杂视图使用基于类的视图（CBVs）
对简单逻辑优先使用基于函数的视图（FBVs）
使用select_related和prefetch_related优化查询
使用Django的ORM；除非必要，否则避免使用原生SQL

FastAPI

FastAPI

Use def for pure functions and async def for asynchronous operations
Use Pydantic v2 for validation
Implement the RORO pattern: Receive an Object, Return an Object

对纯函数使用def，对异步操作使用async def
使用Pydantic v2进行验证
实现RORO模式：接收一个对象，返回一个对象

Flask

Flask

Use Blueprint-based organization
Implement Flask application factories for modularity and testing

使用基于Blueprint的组织方式
实现Flask应用工厂以提升模块化和可测试性

Error Handling

错误处理

Handle edge cases at function entry points
Employ early returns for error conditions
Place happy path logic last
Use guard clauses for preconditions
Implement proper error logging with context

在函数入口处处理边界情况
对错误条件采用提前返回
将正常路径逻辑放在最后
对前置条件使用守卫语句
结合上下文实现恰当的错误日志记录

Performance

性能优化

Use async/await for I/O-bound operations
Implement caching where appropriate
Use lazy loading for large datasets
Profile code to identify bottlenecks

对I/O密集型操作使用Async/await
在合适的场景实现缓存
对大型数据集使用懒加载
对代码进行性能分析以定位瓶颈