Data Structures and Algorithms
Data structure (English: data structure) is the way data is stored and organized in a computer.
A data structure is a collection of data elements that has a certain logical relationship, applies a certain storage structure in a computer, and encapsulates corresponding operations. It includes three aspects: logical relationship, storage relationship, and operations.
Different kinds of data structures are suitable for different kinds of applications, and some are even specifically designed for particular tasks. For example, computer networks rely on routing tables for operation, and B-trees are highly suitable for database encapsulation.
Why learn data structures and algorithms?
As applications become increasingly complex and data becomes more abundant, data in the millions, billions, or even tens of billions appears. Operations like searching, inserting, or sorting such large amounts of data become slower and slower. Data structures are used to solve these problems.
Learning data structures and algorithms can:
- Improve Code Efficiency: Good data structures and algorithms can make programs run faster and use less memory.
- Solve Complex Problems: Many practical problems require specific data structures and algorithms to be solved effectively.
- Interview Essentials: It is almost a mandatory knowledge point in technical interviews.
- Programming Basics: It is the cornerstone of all advanced programming techniques.
What do you need to know before reading this tutorial?
Before you start reading this tutorial, you must have basic programming knowledge, such as concepts of programming like Python or Java.
If you don't yet understand these concepts, we suggest you first read ourPython TutorialorJava Tutorial。
We recommend using Python as the learning language because:
| Features | Python | Java | C++ |
|---|---|---|---|
| Learning Difficulty | ⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐⭐ |
| Syntax Conciseness | High | Medium | Low |
| Execution Efficiency | Medium | High | Very High |
| Community Support | Rich | Rich | Rich |
| Recommendation Index | ⭐⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐ |
Data structures and algorithms explained
Data StructuresIt is like the way we organize items. Imagine your bookshelf:
- If books are piled randomly, finding one will be difficult (inefficient data structure).
- If they are arranged by category, author, or alphabetical order, finding a book is fast (efficient data structure).
AlgorithmsIt is the steps and methods for solving problems. Just like a cooking recipe:
- The same ingredients (data), different methods (algorithms) will produce different results.
- Some methods are fast and good, while others are time-consuming and laborious.
Basic Terms
| Term | Life Analogy | Technical Definition |
|---|---|---|
| Data | Items | The carrier of information, symbols that describe objective things. |
| Data Element | Single Item | Basic Unit of Data |
| Data Structures | Way to Organize Items | A collection of one or more specific relationships that exist between data elements. |
| Algorithms | Steps | Clear instructions for solving problems, completed within a limited time. |
Common Data Structures
- Stack:A stack is a special linear list. It can only perform insertion and deletion operations on data nodes at one fixed end of the list.
- Queue:A queue is similar to a stack and is also a special linear list. Unlike a stack, a queue only allows insertion at one end of the list and deletion at the other end.
- Array:An array is an aggregate data type. It is a collection that organizes several variables of the same type in an ordered manner.
- Linked List:A linked list is a data structure in which data elements are stored according to a chained storage structure. This storage structure has the characteristic of being physically non-continuous.
- Tree:A tree is a typical nonlinear structure. It is a finite set K that includes 2 nodes.
- Graph:A graph is another nonlinear data structure. In a graph structure, data nodes are generally called vertices, and edges are ordered pairs of vertices.
- Heap:A heap is a special tree data structure. The heap generally discussed is a binary heap.
- Hash Table:A hash table originates from a hash function. The idea is that if a record with a key equal to T exists in the structure, then the record can be found at the storage location F(T). In this way, the desired record can be obtained directly without performing comparison operations.
Common Algorithms
The content of data structure research: how to organize data according to a certain logical structure, and choose appropriate storage representation methods to store the logically organized data into computer memory. The purpose of algorithm research is to process data more effectively and improve the efficiency of data operations. Data operations are defined on the logical structure of data, but the specific implementation of operations must be carried out on the storage structure. Generally, there are several common operations:
- Search:Retrieval is to find nodes that meet certain conditions in a data structure. Generally, given a value of a certain field, find the node with that field value.
- Insert:Add a new node to the data structure.
- Delete:Remove the specified node from the data structure.
- Update:Change the value of one or more fields of the specified node.
- Sort:Rearrange nodes in a specified order, for example, increasing or decreasing.
References
Hello Algo:https://github.com/krahets/hello-algo
Python algorithm implementation:https://github.com/TheAlgorithms/Python。
Play-with-Algorithms: https://github.com/liuyubobobo/Play-with-Algorithms。
other extensions