dart-logic-patterns
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ChineseAlgorithms & Logic
算法与逻辑
The efficiency of your business logic directly impacts battery life and responsiveness.
业务逻辑的效率会直接影响电池续航和应用响应速度。
Complexity Analysis
复杂度分析
- Big O Awareness: Understand the cost of your operations. Avoid O(n²) or higher on the main thread for datasets larger than a few hundred items.
- Data Structure Selection:
- : Fast key-based lookups.
Map - : Fast unique item management.
Set - : Fast indexing and sequential access.
List - : Preserves insertion order while providing fast lookups.
LinkedHashSet/Map
- 大O表示法认知:了解你所执行操作的开销。对于包含数百项以上的数据集,避免在主线程中使用O(n²)或更高复杂度的操作。
- 数据结构选择:
- :基于键的快速查找
Map - :高效的唯一元素管理
Set - :快速索引和顺序访问
List - :保留插入顺序的同时提供快速查找能力
LinkedHashSet/Map
Logic Patterns
逻辑模式
- Debouncing: Delay execution until a user stops interacting (e.g., search-as-you-type).
- Throttling: Limit execution to at most once every interval (e.g., scrolling events).
- Memoization: Cache the results of expensive pure functions based on their arguments. Use or custom implementations.
package:memoize
- Debouncing(防抖):延迟执行直到用户停止交互(例如:输入实时搜索场景)。
- Throttling(节流):限制执行频率,每个时间间隔内最多触发一次(例如:滚动事件处理)。
- Memoization(记忆化):基于入参缓存高开销纯函数的执行结果,可使用或自定义实现。
package:memoize
Search & Sort
搜索与排序
- Binary Search: Use for sorted lists to transform O(n) searches into O(log n).
- Efficient Sorting: Use Dart's built-in , which uses highly optimized algorithms. Provide targeted
list.sort()implementations for custom objects.Comparable
- Binary Search(二分查找):在有序列表中使用,可将O(n)复杂度的搜索优化为O(log n)。
- 高效排序:使用Dart内置的,它采用了高度优化的算法,针对自定义对象可提供对应的
list.sort()实现。Comparable
Business Logic Organization
业务逻辑组织
- Pure Functions: Keep business logic in pure, testable functions outside of UI classes.
- Fail Fast: Use guard clauses to handle edge cases and invalid states early.
- Validation Logic: Keep complex validation in a separate domain layer, reusable across different screens.
- 纯函数:将业务逻辑保存在UI类之外的可测试纯函数中。
- 快速失败:使用卫语句提前处理边界情况和非法状态。
- 校验逻辑:将复杂的校验逻辑放在独立的领域层,可在不同页面间复用。