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Python data types: parsing data structures in simple terms

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Python 数据类型:深入浅出解析数据结构

  • List (list): A collection that stores ordered elements
  • Tuple (tuple): An immutable collection that stores ordered elements
  • Set (set): A collection that stores unordered and non-repeating elements
  • Dictionary (dict): A collection of key-value pairs

3. Data structure

Data structure is a way of organizing data for efficient storage, retrieval and processing of data. python Provides built-in data structures, including:

  • Array (array): A linear data structure that efficiently stores elements of the same type
  • Linked list: A linear data structure that uses pointers to link elements
  • Stack: A linear data structure that follows the last-in-first-out (FILO) principle
  • Queue(queue): A linear data structure that follows the first-in-first-out (FIFO) principle
  • Tree (tree): Non-linear data structure with hierarchical structure
  • Heap: A tree data structure that satisfies the properties of a heap

4. Data type selection

Choosing the appropriate data type is critical to Python the performance and reliability of your program. The following are the selection criteria:

  • The size of the data type: affects memory usage and processing speed
  • Collection: used to store collections or single elements
  • Variability: Whether to allow dynamic modification of the data structure
  • Sequentiality: Whether the elements are arranged in a specific order
  • Access mode: Different access methods to the data structure (for example, sequential, random)

5. Common mistakes

Common mistakes when using Python data types include:

  • Mixed data types: Store different types of data in one data structure
  • Using the wrong data structure: Select a data structure that is not suitable for the required operation
  • Data structure limit exceeded: Attempt to store data that exceeds its capacity
  • Not properly initialized: The data structure was not initialized to appropriate values ​​before use

6. Best Practices

When using Python data types, follow these best practices:

  • Choose the appropriate data type: Carefully select the most appropriate type according to your needs
  • Clear data type: Clear data type through type annotation or variable declaration
  • Consistency: Maintain consistent data type conventions throughout the program
  • Avoid uninitialization: Always initialize data structures before use
  • Consider performance: Use efficient data structures on large data sets
  • Consider maintainability: Choose data structures that are easy to understand and maintain

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