Vibe Coding a Python Library
I was looking for a real use case to test out “vibe coding”. Although I have used Cursor for almost a year now, it was mostly in bits and pieces. I wanted to really test-drive the capability of all its aspects to build a fully working system. Today, I built and launched a fully-functioning Python repository - Cloudinary People using vibe coding!
What is the use case?
Cloudinary has launched a capability to identify people in uploaded images. An API was made available to handle 3 use cases:
At this point, no SDK support is available since it is relatively new. So I wanted to take Cursor out for a test-drive and build an SDK for these endpoints.
How did I do it?
Step 1: Generate the basic code
I used Cursor, alternating between the Plan and Build modes. Just to give a glimpse, I started with this initial prompt:
I would like to build a full Python SDK for the Cloudinary people search feature. The documentation for this feature is available here: In this SDK, user will support their API Key, API Secret and Cloud Name parameters.
Users will need to use the following features:
1. List recognized people (https://cloudinary.github.io/api-schemas/index.html?schema=api&viewer=stoplight#/operations/listPeople )
2. Get person details (https://cloudinary.github.io/api-schemas/index.html?schema=api&viewer=stoplight#/operations/getPerson )
3. Update a person (https://cloudinary.github.io/api-schemas/index.html?schema=api&viewer=stoplight#/operations/updatePerson )
For this SKD, I'd like to use pydantic for type checking. Provide a "verbose" option to print debug information where necessary.
Add self-documentation as well. If needed, I may use this SDK as a foundation to develop a CLI. For now, don't worry about CLI.
Can you plan this project?
This step created a detailed step-by-step plan for the project. I then asked Cursor to create the code.
Step 2: Review the code
Once this code was ready, I wanted to ensure code quality. So I started a new agent and asked it to review the code.
@cloudinary_people_sdk_910195c7.plan.md (1-71) Take a look at the project specs and the code created. Analyze the code from the perspective of a Senior or Principal Software Engineer. Identify potential issues in logic or problems with maintainability. Suggest changes that can make this code be better.
Cursor gave a whole set of recommendations in a separate markdown file. It identified 3 critical issues, about 5 maintainability issues and a few other issues related to tests and packaging.
I asked Cursor to implement all the recommendations.
I followed it up with some minor changes. I wanted the code to support a specific mechanism of authentication that Cloudinary SDKs use. It was able to incorporate it easily.
Step 3: Package and publish
At this stage, I was confident of the code, but I wanted one more peer review. So I asked Cursor to do another round of checks, again starting in Plan mode followed by Build mode.
I would like to publish this repository to pypi. Before doing this, I'd like you to run a security audit.
1. is this code safe to publish?
2. are there any dependencies having security vulnerabilities? if so, how can I work-around them?
3. From a code documentation and README perspective, is this reasonably complete?
Basically, I want a peer review before I publish.
It identified the following:
- Medium: CVE-2024-35195 in requests < 2.32.0 - a security issue
- Bug 1: verbose=True parameter does not exist - a bug
- No LICENSE file
and a few more minor things.
After fixing this, I was all set.
Step 4: Publish
To test out my confidence 😄, I switched to Cursor’s agent CLI. I asked it to package and publish my repo to pypi.
It first published the code to pypi test and asked me to verify. Only after I confirmed, it went ahead and published to pypi.
Step 5: Generate a hero image
The last step was to make it attractive. For this, I used Gemini. I simply provided my github URL to the LLM and asked it to create a hero image.
I would like to create a hero image for my python project at https://pypi.org/project/cloudinary-people/. Can you generate a prompt that would be suitable for this project? I plan to use Gemini/Nano-Banana to create the image.
After some trials, it generated an image that worked for me!
Conclusion
Vibe-coding is real! If you know the system that you want to build and have clarity in mind, the tools are simply amazing. I developed the entire library + hero image in about 4 hours! This would have normally taken weeks of effort since this is not my day job.
Vibe-coding is a strong enabler for developers. If we know what we want, getting the agent to do it on our behalf is liberating. That said, if I ever need to deep-troubleshoot this library, I’ll be hesitant. I did not “code” each line, so my ability to support it will be limited!
Are you seeing something similar in your world? Do share your thoughts!