I Automated Leetcode using Claude’s 3.5 Sonnet API and Python. The script completed 633 problems in 24 hours, completely autonomously. It had a 86% success rate, and cost $9 in API credits.
I Automated LeetCode Using Claude’s 3.5 Sonnet API and Python
In a remarkable feat of automation and programming, I recently implemented a script that solved a staggering 633 LeetCode problems in just 24 hours, all on its own. The results were impressive: an 86% success rate, and all of this for a mere $9 in API credits. This experience not only highlighted the power of AI in solving coding challenges but also raised interesting discussions in the developer community.
The Journey of Automation
The journey began when I decided to leverage the capabilities of Claude’s 3.5 Sonnet API, a cutting-edge AI model that excels in understanding and generating code. My goal was to automate the process of solving LeetCode problems, which are widely used by developers to prepare for technical interviews.
Using Python as my primary programming language, I built a script that autonomously tackled problems from various difficulty levels. The approach was straightforward: the script would fetch problems, generate code solutions, and submit them for testing. The automation not only saved time but also provided an excellent opportunity to analyze the efficacy of AI in coding.
The Results: 633 Problems in 24 Hours
The numbers speak for themselves. In just one day, my script methodically approached and attempted to solve 633 problems. The success rate of 86% is quite commendable, especially considering that these problems come with varying degrees of complexity.
While some might argue that an 86% success rate is not perfect, it is essential to consider the nature of the task. Many LeetCode problems require nuanced understanding, and the fact that the AI was able to adapt and learn from its failures is a testament to the advancements in machine learning.
Community Reactions
The reception to this project has been overwhelmingly positive. A notable comment from a community member stated, “If there are any hiring managers or folks willing to refer my dude here, do reach out to him, he’s looking out for an opportunity and he seems like a great asset :)” This reflects the growing interest in AI-driven solutions and the potential for individuals who can harness these technologies.
Another user praised the script’s success rate, noting, “Nice script, that’s a pretty high success rate.” They shared their own experience with LeetCode Wizard, which uses GPT-4o and took significant tweaking to achieve over 90% success. This comparison illustrates the rapid evolution of AI in solving coding challenges and the healthy competition in this space.
Analyzing Failures for Success
One of the standout features of my script was its ability to analyze failed test results. After encountering a problem it couldn’t solve, the script would evaluate the reasons for its failure and modify its approach accordingly. This retry mechanism, based on analyzing current attempts and test results, enabled it to improve and eventually solve many of the problems that it initially struggled with.
This aspect of the automation process underscores the importance of feedback loops in AI systems. By incorporating a learning mechanism, the script became more adept at solving problems over time, much like a human coder would learn from mistakes.
Conclusion
Automating the process of solving LeetCode problems using Claude’s 3.5 Sonnet API and Python has been an incredible experience. With the ability to solve 633 problems autonomously, an 86% success rate, and minimal cost, it’s clear that AI is making significant strides in coding and problem-solving.
As AI technologies continue to advance, the possibilities for automation in various fields, including programming, are boundless. This project not only showcases the potential of AI but also opens up discussions about the future of coding, learning, and the role of AI in technical interviews.
If you’re interested in exploring automation in coding or have thoughts on the future of AI in programming, I’d love to hear from you in the comments!
This blog post captures the essence of your project while providing context, community feedback, and insights into the potential of AI in coding automation.