Lazy loading

Lazy loading is a design pattern commonly used in computer programming to defer initialization of an object until the point at which it is needed. It can reduce program startup time and memory usage by avoiding unnecessary work, kind of like that slacker developer on your team who only does the bare minimum until the sprint deadline is looming.

How to use it in a sentence

  • "We should use lazy loading for the images in this component so the page loads faster and we don't waste bandwidth on images the user might not even scroll down to see. You know, like how Netflix doesn't load the entire video until you actually press play."

  • "I was going to add lazy loading to the chat feature, but the PM started hovering over my desk asking for status updates every 5 minutes. I guess they were worried I'd go into 'lazy mode' myself if left unattended for too long."

If you actually want to learn more...

Note: the Developer Dictionary is in Beta. Please direct feedback to skye@statsig.com.

Join the #1 experimentation community

Connect with like-minded product leaders, data scientists, and engineers to share the latest in product experimentation.

Try Statsig Today

Get started for free. Add your whole team!

Why the best build with us

OpenAI OpenAI
Brex Brex
Notion Notion
SoundCloud SoundCloud
Ancestry Ancestry
At OpenAI, we want to iterate as fast as possible. Statsig enables us to grow, scale, and learn efficiently. Integrating experimentation with product analytics and feature flagging has been crucial for quickly understanding and addressing our users' top priorities.
OpenAI
Dave Cummings
Engineering Manager, ChatGPT
Brex's mission is to help businesses move fast. Statsig is now helping our engineers move fast. It has been a game changer to automate the manual lift typical to running experiments and has helped product teams ship the right features to their users quickly.
Brex
Karandeep Anand
President
At Notion, we're continuously learning what our users value and want every team to run experiments to learn more. It’s also critical to maintain speed as a habit. Statsig's experimentation platform enables both this speed and learning for us.
Notion
Mengying Li
Data Science Manager
We evaluated Optimizely, LaunchDarkly, Split, and Eppo, but ultimately selected Statsig due to its comprehensive end-to-end integration. We wanted a complete solution rather than a partial one, including everything from the stats engine to data ingestion.
SoundCloud
Don Browning
SVP, Data & Platform Engineering
We only had so many analysts. Statsig provided the necessary tools to remove the bottleneck. I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig.
Ancestry
Partha Sarathi
Director of Engineering
We use cookies to ensure you get the best experience on our website.
Privacy Policy