Advice for Enhancing Dash App Performance

[emilysmith]

Hey everyone!

I’ve been using Dash for a while now to build some pretty cool data visualizations. However, as my app grows in complexity and more users are interacting with it, I’ve noticed a bit of a performance dip- especially when handling larger datasets or more detailed graphs.

I was wondering if anyone has tips or tricks for optimizing Dash app performance? I’ve already tried things like reducing callback complexity and caching, but I feel like I could be missing out on some best practices. When I was Googling for the same I came across these resources/articles Performance | Dash for Python Documentation | Plotly Kubernetes vs Docker however they are good but I want to learn more from community members.

Any advice, suggestions, or even resources to point me in the right direction would be super helpful.

Thanks in advance!
Emily

[AnnMarieW]

Hi @emilysmith
You might find this article about profiling your app here:

Performance Profiling Dash apps with Werkzeug

Hi! Just wanted to share some tips on using the Werkzeug profiler in your Dash app. I’ve found this to be really useful for finding bottlenecks in an app’s performance. Hope that this is helpful for others out there. Install and set up profiling tool Install werkzeug Edit your index.py or app.py file to include from werkzeug.middleware.profiler import ProfilerMiddleware if __name__ == "__main__": if os.getenv("PROFILER", None): app.server.config["PROFILE"] = True app.se…