


Heap, stack, dictionary, red-black tree and other data structures in Go language
With the development of computer science, data structure has become an important subject. In software development, data structures are very important. They can improve program efficiency and readability, and can also help solve various problems. In the Go language, data structures such as heap, stack, dictionary, and red-black tree are also very important. This article will introduce these data structures and their implementation in Go language.
- Heap
Heap is a classic data structure used to solve priority queue problems. A priority queue refers to a queue that takes out elements in order of their priority. The heap can be used to quickly locate the highest priority element in the queue, so that insertion, deletion, and search operations can be implemented within O(log n) time complexity.
In the Go language, the heap can be implemented using the container/heap package. This package provides an interface definition, which needs to implement three methods:
// Len returns the number of elements in the heap
func (h *heap) Len() int {
// ...
}
// Less compares the priorities of two elements, and returns true to indicate that the first element has a higher priority
func (h *heap) Less(i, j int) bool {
// ...
}
// Swap swaps the positions of two elements
func (h *heap) Swap(i, j int) {
// ...
}
Among them, the Less method needs to implement the comparison logic of element priority according to actual needs.
After implementing these three methods, you can convert a slice into a heap through the heap.Init method. When you need to add or remove elements, you can use the heap.Push and heap.Pop methods in the container/heap package.
- Stack
Stack is another common data structure, which can realize first-in, last-out data storage. The stack is mainly used in scenarios such as program calls and recursion. It can record the order of function calls and facilitate function returns.
In the Go language, you can use the list structure in the container/list package to implement the stack. It should be noted that the push and pop operations of the stack need to be implemented using list.PushBack and list.Back().Value.(type) respectively.
- Dictionary
Dictionary (Map) is a commonly used data structure, which can realize the storage and query of key-value pairs. Dictionaries are also a very important data structure in the Go language and are often used to record configuration, statistical information, etc.
In the Go language, dictionaries can be defined directly using the map keyword. As follows:
// Define a dictionary
m := make(map[string]int)
// Add key-value pair
m["apple"] = 2
m["banana"] = 3
// Query key-value pair
fmt.Println(m["apple"]) // Output 2
// Delete Key-value pair
delete(m, "banana")
It should be noted that the key type of the dictionary must be a data type that supports the == operator, such as string, int, etc. Similarly, the value type of the dictionary also needs to comply with the regulations in the Go language.
- Red-Black Tree
Red-Black Tree (Red-Black Tree) is a self-balancing binary search tree, which can be in O(log n) Implement insertion, deletion, and search operations within time complexity. The nodes of the red-black tree have two colors, red and black. They have the following characteristics:
- The root node is black;
- All leaf nodes are black and empty Node (that is, leaf nodes do not store data);
- All red nodes must have two black child nodes (the red-black tree guarantees that all paths from the root node to the leaf node have the same number of black nodes) ;
- All paths from any node to its leaf nodes contain the same number of black nodes.
In the Go language, you can use the container/rbtree package to implement a red-black tree. This package provides an interface definition, and the methods that need to be implemented are:
// Less compares the size of two elements, and returns true to indicate that the first element is smaller
func (x *MyStruct) Less( than item) bool {
// ...
}
Among them, the Less method needs to implement the size comparison logic of elements according to actual needs. During specific implementation, the MyStruct structure needs to be embedded in the Item structure, as shown below:
type MyStruct struct {
item.Item // ...
}
After implementing the Less method of MyStruct, you can use the container The Root method in the /rbtree package obtains the root node of the tree, and inserts, deletes, and queries the red-black tree through the Insert, Delete, and Get methods. It should be noted that the Get method provided by this package returns the matching node, not the node value.
Summary
This article introduces the commonly used data structures in Go language: heap, stack, dictionary, red-black tree. These data structures are very common in daily development, and mastering their use can improve the efficiency and readability of our code.
In actual development, we need to choose the appropriate data structure based on actual needs. For example, you can use a heap when you need to implement a priority queue, you can use a dictionary when you need to store key-value pairs, you can use a red-black tree when you need to implement fast search, etc.
Using appropriate data structures can make our code more efficient, concise and easy to maintain. I hope this article will be helpful to your learning and use of data structures.
The above is the detailed content of Heap, stack, dictionary, red-black tree and other data structures in Go language. For more information, please follow other related articles on the PHP Chinese website!

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