Always Ship Performant Code
Codeflash finds the fastest version of your Python code through AI-powered optimizations, verifies correctness, and automatically delivers performance gains.
Codeflash Automates Performance Optimization
Focus on writing features - Codeflash figures out how to make them blazing fast.
Curious? Try optimizing a real repository with Codeflash!
Continuously Optimize Your Code
Optimize entire projects
Find every optimization opportunity in your entire project.
Optimize your GitHub PRs
Install Codeflash as a GitHub action and never ship slow code again.
Unlock your applications' performance
What developers say
Codeflash enables our team to ship blazing-fast computer vision models without sacrificing development speed. We've achieved 25% faster object detection and improved throughput from 80 to 100 FPS-letting our customers run more video streams on fewer GPUs while our engineers focus on building new features which are made performant by Codeflash.
We've used Codeflash in the Pydantic codebase (300M+ downloads / month) to help optimize logic including repeated attribute access patterns and recursive algorithms. We're particularly impressed by the thorough testing and explanations provided by Codeflash which give us confidence in merging the recommended changes.
With Codeflash I can now focus only on writing the code and don't have to worry about optimizations. I feel like I have an extra expert engineer optimizing performance for me all the time.
Keeping a large open-source project performant can be quite hard to do. With Codeflash we can be more confident that every new PR is optimized.
I've been working on Albumentations, an image augmentation library, for years now. The library is already well optimized. But the Codeflash team submitted over 10 pull requests in just one week, each making our functions significantly faster. The speedups range from 2× to 55× in some cases. I'm now adding Codeflash to our GitHub actions workflow so every PR will automatically get checked for potential performance improvements. It will help make the library even faster and teach everyone who contributes to Albumentations how to write more performant code.
Codeflash enables our team to ship blazing-fast computer vision models without sacrificing development speed. We've achieved 25% faster object detection and improved throughput from 80 to 100 FPS-letting our customers run more video streams on fewer GPUs while our engineers focus on building new features which are made performant by Codeflash.
We've used Codeflash in the Pydantic codebase (300M+ downloads / month) to help optimize logic including repeated attribute access patterns and recursive algorithms. We're particularly impressed by the thorough testing and explanations provided by Codeflash which give us confidence in merging the recommended changes.
With Codeflash I can now focus only on writing the code and don't have to worry about optimizations. I feel like I have an extra expert engineer optimizing performance for me all the time.
Keeping a large open-source project performant can be quite hard to do. With Codeflash we can be more confident that every new PR is optimized.
I've been working on Albumentations, an image augmentation library, for years now. The library is already well optimized. But the Codeflash team submitted over 10 pull requests in just one week, each making our functions significantly faster. The speedups range from 2× to 55× in some cases. I'm now adding Codeflash to our GitHub actions workflow so every PR will automatically get checked for potential performance improvements. It will help make the library even faster and teach everyone who contributes to Albumentations how to write more performant code.
Codeflash enables our team to ship blazing-fast computer vision models without sacrificing development speed. We've achieved 25% faster object detection and improved throughput from 80 to 100 FPS-letting our customers run more video streams on fewer GPUs while our engineers focus on building new features which are made performant by Codeflash.
We've used Codeflash in the Pydantic codebase (300M+ downloads / month) to help optimize logic including repeated attribute access patterns and recursive algorithms. We're particularly impressed by the thorough testing and explanations provided by Codeflash which give us confidence in merging the recommended changes.
With Codeflash I can now focus only on writing the code and don't have to worry about optimizations. I feel like I have an extra expert engineer optimizing performance for me all the time.
Keeping a large open-source project performant can be quite hard to do. With Codeflash we can be more confident that every new PR is optimized.
I've been working on Albumentations, an image augmentation library, for years now. The library is already well optimized. But the Codeflash team submitted over 10 pull requests in just one week, each making our functions significantly faster. The speedups range from 2× to 55× in some cases. I'm now adding Codeflash to our GitHub actions workflow so every PR will automatically get checked for potential performance improvements. It will help make the library even faster and teach everyone who contributes to Albumentations how to write more performant code.
Never ship slow
code again
