


JavaScript event delegation technology example analysis_javascript skills
This article analyzes JavaScript event delegation technology with examples. Share it with everyone for your reference. The specific analysis is as follows:
If there are a large number of buttons in a whole page, we need to bind event handlers to each button. This will affect performance.
First of all, every function is an object, and the object will occupy a lot of memory. The more objects in the memory, the worse the performance.
Secondly, an increase in the number of DOM visits will lead to delayed page loading. In fact, there are still good solutions for how to make good use of event handlers.
Event delegate:
The solution to the problem of too many event handlers is event delegation technology.
Event delegation technology takes advantage of event bubbling. Just specify an event handler.
We can bind event handlers to a parent element that needs to trigger an event.
<ul id="mylist"> <li id="li_1">sdsdsd</li> <li id="li_2">sdsdsd</li> <li id="li_3">sdsdsd</li> </ul>
Now we need to bind event handlers for these 3 li's..
Only need to bind the event handler in ul.
obj.eventHandler($("mylist"),"click",function(e){ e = e || window.event; switch(e.target.id){ //大家应该还记得target是事件目标, //只要点击了事件的目标元素就会弹出相应的alert. case "li_1": alert("li_1"); break; case "li_2": alert("li_2"); break; case "li_3": alert("li_3"); break } })
If in a complex web application, this kind of event delegation is very practical.
If you don’t use this method, binding them one by one will result in countless event handlers.
I hope this article will be helpful to everyone’s JavaScript programming design.

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



StableDiffusion3’s paper is finally here! This model was released two weeks ago and uses the same DiT (DiffusionTransformer) architecture as Sora. It caused quite a stir once it was released. Compared with the previous version, the quality of the images generated by StableDiffusion3 has been significantly improved. It now supports multi-theme prompts, and the text writing effect has also been improved, and garbled characters no longer appear. StabilityAI pointed out that StableDiffusion3 is a series of models with parameter sizes ranging from 800M to 8B. This parameter range means that the model can be run directly on many portable devices, significantly reducing the use of AI

Trajectory prediction plays an important role in autonomous driving. Autonomous driving trajectory prediction refers to predicting the future driving trajectory of the vehicle by analyzing various data during the vehicle's driving process. As the core module of autonomous driving, the quality of trajectory prediction is crucial to downstream planning control. The trajectory prediction task has a rich technology stack and requires familiarity with autonomous driving dynamic/static perception, high-precision maps, lane lines, neural network architecture (CNN&GNN&Transformer) skills, etc. It is very difficult to get started! Many fans hope to get started with trajectory prediction as soon as possible and avoid pitfalls. Today I will take stock of some common problems and introductory learning methods for trajectory prediction! Introductory related knowledge 1. Are the preview papers in order? A: Look at the survey first, p

This paper explores the problem of accurately detecting objects from different viewing angles (such as perspective and bird's-eye view) in autonomous driving, especially how to effectively transform features from perspective (PV) to bird's-eye view (BEV) space. Transformation is implemented via the Visual Transformation (VT) module. Existing methods are broadly divided into two strategies: 2D to 3D and 3D to 2D conversion. 2D-to-3D methods improve dense 2D features by predicting depth probabilities, but the inherent uncertainty of depth predictions, especially in distant regions, may introduce inaccuracies. While 3D to 2D methods usually use 3D queries to sample 2D features and learn the attention weights of the correspondence between 3D and 2D features through a Transformer, which increases the computational and deployment time.

In September 23, the paper "DeepModelFusion:ASurvey" was published by the National University of Defense Technology, JD.com and Beijing Institute of Technology. Deep model fusion/merging is an emerging technology that combines the parameters or predictions of multiple deep learning models into a single model. It combines the capabilities of different models to compensate for the biases and errors of individual models for better performance. Deep model fusion on large-scale deep learning models (such as LLM and basic models) faces some challenges, including high computational cost, high-dimensional parameter space, interference between different heterogeneous models, etc. This article divides existing deep model fusion methods into four categories: (1) "Pattern connection", which connects solutions in the weight space through a loss-reducing path to obtain a better initial model fusion

Written above & The author’s personal understanding is that image-based 3D reconstruction is a challenging task that involves inferring the 3D shape of an object or scene from a set of input images. Learning-based methods have attracted attention for their ability to directly estimate 3D shapes. This review paper focuses on state-of-the-art 3D reconstruction techniques, including generating novel, unseen views. An overview of recent developments in Gaussian splash methods is provided, including input types, model structures, output representations, and training strategies. Unresolved challenges and future directions are also discussed. Given the rapid progress in this field and the numerous opportunities to enhance 3D reconstruction methods, a thorough examination of the algorithm seems crucial. Therefore, this study provides a comprehensive overview of recent advances in Gaussian scattering. (Swipe your thumb up

jQuery is a popular JavaScript library that can be used to simplify DOM manipulation, event handling, animation effects, etc. In web development, we often encounter situations where we need to change event binding on select elements. This article will introduce how to use jQuery to bind select element change events, and provide specific code examples. First, we need to create a dropdown menu with options using labels:

The GPT-4o model released by OpenAI is undoubtedly a huge breakthrough, especially in its ability to process multiple input media (text, audio, images) and generate corresponding output. This ability makes human-computer interaction more natural and intuitive, greatly improving the practicality and usability of AI. Several key highlights of GPT-4o include: high scalability, multimedia input and output, further improvements in natural language understanding capabilities, etc. 1. Cross-media input/output: GPT-4o+ can accept any combination of text, audio, and images as input and directly generate output from these media. This breaks the limitation of traditional AI models that only process a single input type, making human-computer interaction more flexible and diverse. This innovation helps power smart assistants

Combination of Golang and front-end technology: To explore how Golang plays a role in the front-end field, specific code examples are needed. With the rapid development of the Internet and mobile applications, front-end technology has become increasingly important. In this field, Golang, as a powerful back-end programming language, can also play an important role. This article will explore how Golang is combined with front-end technology and demonstrate its potential in the front-end field through specific code examples. The role of Golang in the front-end field is as an efficient, concise and easy-to-learn
