distinct function usage distance function c usage tutorial
std::unique removes adjacent duplicate elements in the container and moves them to the end, returning an iterator pointing to the first duplicate element. std::distance calculates the distance between two iterators, that is, the number of elements they point to. These two functions are useful for optimizing code and improving efficiency, but there are also some pitfalls to be paid attention to, such as: std::unique only deals with adjacent duplicate elements. std::distance is less efficient when dealing with non-random access iterators. By mastering these features and best practices, you can fully utilize the power of these two functions.
Exploring the secret of std::unique
and std::distance
: C container's weapon
Are you often troubled by repeating elements or the need to calculate the iterator distance when working with C containers? This article will dive into the two powerful standard library functions, std::unique
and std::distance
, to take you through their charm in optimizing code, improving efficiency, and to reveal some potential pitfalls and best practices. After reading this article, you will be able to use these two functions proficiently to write more efficient and elegant C code.
Basic knowledge: Iterators and algorithms
Before we go into the deeper explanation of std::unique
and std::distance
, we need to review the concept of C iterator. An iterator is a generic pointer to access container elements. It allows us to operate various containers in a unified way (such as std::vector
, std::list
, std::deque
, etc.). Standard library algorithms, such as std::unique
, rely on iterators to manipulate elements in containers.
std::unique
: a tool for removing weight
Instead of directly removing duplicate elements, std::unique
function moves adjacent duplicate elements in the container to the end of the container and returns an iterator pointing to the position of the first duplicate element. This sounds a bit confusing, but if you understand how it works, you will find it very practical.
Let's look at an example:
<code class="c ">#include <iostream> #include <algorithm> #include <vector> int main() { std::vector<int> numbers = {1, 1, 2, 2, 3, 4, 4, 5}; auto it = std::unique(numbers.begin(), numbers.end()); // it现在指向第一个重复元素的位置,也就是第二个'2' numbers.erase(it, numbers.end()); // 移除重复元素for (int num : numbers) { std::cout </int></vector></algorithm></iostream></code>
This code first uses std::unique
to move the repeating elements to the end, and then uses the erase
method to remove these elements. Note that std::unique
itself does not change the size of the container, it just rearranges the elements.
std::distance
: Iterator distance calculator
std::distance
function calculates the distance between two iterators, that is, the number of elements they point to. This function is very useful in many algorithms, such as calculating the length of a subsequence, or determining the position of an element in a container.
<code class="c ">#include <iostream> #include <algorithm> #include <vector> #include <iterator> int main() { std::vector<int> numbers = {1, 2, 3, 4, 5}; auto it1 = numbers.begin() 1; auto it2 = numbers.end() - 1; std::cout </int></iterator></vector></algorithm></iostream></code>
This code calculates the distance between iterators it1
and it2
, and the result is 3.
Traps and optimization
When using std::unique
, you need to be careful that it only deals with adjacent duplicate elements . If your duplicate elements are not adjacent, you need to sort the container first (for example using std::sort
).
std::distance
is very efficient when dealing with random access iterators (such as std::vector
's iterators) because the difference can be calculated directly. But for other types of iterators (such as the iterators of std::list
), it requires linear time complexity and is therefore less efficient. In performance-critical code, you should try to avoid using std::distance
on non-random access iterators.
Best Practices
- Before using
std::unique
, consider whether you need to sort the container first. - For performance-sensitive applications, choose the appropriate container type and algorithm to avoid unnecessary iterator traversal.
- Write clear and readable code and add necessary comments for easy understanding and maintenance.
All in all, std::unique
and std::distance
are very useful tools in the C standard library, and mastering them can help you write more efficient and elegant code. Only by remembering their characteristics and potential pitfalls can they fully exert their power. I hope this article can help you better understand and use these two functions.
The above is the detailed content of distinct function usage distance function c usage tutorial. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics



C Reasons for continuous use include its high performance, wide application and evolving characteristics. 1) High-efficiency performance: C performs excellently in system programming and high-performance computing by directly manipulating memory and hardware. 2) Widely used: shine in the fields of game development, embedded systems, etc. 3) Continuous evolution: Since its release in 1983, C has continued to add new features to maintain its competitiveness.

To create a data table using phpMyAdmin, the following steps are essential: Connect to the database and click the New tab. Name the table and select the storage engine (InnoDB recommended). Add column details by clicking the Add Column button, including column name, data type, whether to allow null values, and other properties. Select one or more columns as primary keys. Click the Save button to create tables and columns.

Steps to set up an automatic growth ID in phpMyAdmin: Open phpMyAdmin and connect to the database. Select the table to create the automatic growth ID. In the Structure tab, check the Automatically grow check box in the Primary Key section. Enter the Start and End values for the Automatically Grow ID in the From and To fields. Click the "Save" button. Advantages of setting up an automatic growth ID include: Simplified data insertion. Ensure uniqueness. Optimize performance. Easy to identify. Things to note: Ensure that the range of automatic growth IDs is large enough. Repeat values may not be possible

Creating an Oracle database is not easy, you need to understand the underlying mechanism. 1. You need to understand the concepts of database and Oracle DBMS; 2. Master the core concepts such as SID, CDB (container database), PDB (pluggable database); 3. Use SQL*Plus to create CDB, and then create PDB, you need to specify parameters such as size, number of data files, and paths; 4. Advanced applications need to adjust the character set, memory and other parameters, and perform performance tuning; 5. Pay attention to disk space, permissions and parameter settings, and continuously monitor and optimize database performance. Only by mastering it skillfully requires continuous practice can you truly understand the creation and management of Oracle databases.

To create an Oracle database, the common method is to use the dbca graphical tool. The steps are as follows: 1. Use the dbca tool to set the dbName to specify the database name; 2. Set sysPassword and systemPassword to strong passwords; 3. Set characterSet and nationalCharacterSet to AL32UTF8; 4. Set memorySize and tablespaceSize to adjust according to actual needs; 5. Specify the logFile path. Advanced methods are created manually using SQL commands, but are more complex and prone to errors. Pay attention to password strength, character set selection, tablespace size and memory

The core of Oracle SQL statements is SELECT, INSERT, UPDATE and DELETE, as well as the flexible application of various clauses. It is crucial to understand the execution mechanism behind the statement, such as index optimization. Advanced usages include subqueries, connection queries, analysis functions, and PL/SQL. Common errors include syntax errors, performance issues, and data consistency issues. Performance optimization best practices involve using appropriate indexes, avoiding SELECT *, optimizing WHERE clauses, and using bound variables. Mastering Oracle SQL requires practice, including code writing, debugging, thinking and understanding the underlying mechanisms.

Python is suitable for data science, web development and automation tasks, while C is suitable for system programming, game development and embedded systems. Python is known for its simplicity and powerful ecosystem, while C is known for its high performance and underlying control capabilities.

Redis uses the dynamic data structure "Redis Objects" to store data, including strings, hashes, lists, collections, and ordered collections. These objects are represented internally in RDB format and optimized with different encoding types according to data characteristics. The life cycle of a Redis object is affected by the creation, acquisition, modification, and deletion operations, and the expiration time (TTL) can be set to automatically delete the object after the TTL.
