How can cursor+deepseek be used to minimize the cost of learning a component library!

#ai #webdev #javascript #programming

In today's software development field, developers are facing the challenges of constantly improving development efficiency and reducing the cost of getting started. The core purpose of this document is to help developers achieve this goal, especially by ingeniously using the official website documentation of components, combined with tools such as Cursor and DeepSeek, to allow AI to automatically generate the required code. Next, we will take the VTable table component in the VisActor visualization library as an example to elaborate the entire process in detail.

Introduction to the VTable component

VTable is a powerful table component in the VisActor visualization library. It is specially designed to meet the diverse needs of data display, with a high degree of flexibility and customizability. Whether it is a simple list of data or a complex data analysis display scenario, VTable can provide excellent solutions.
VTable has the following core features:

Supports multiple table types: basic table, pivot table, transposed table, pivot chart, etc.
Powerful interaction functions: sorting, filtering, row and column dragging, cell editing, etc.
Rich cell types: text, chart, progress bar, checkbox, mini-chart, etc.
High-performance rendering: supports smooth display of millions of data
Multi-terminal adaptation: perfectly supports mainstream frameworks such as Vue and React

Development steps

Create a project

First, we need to create an initialization project (take Vue as an example). Run relevant commands to build the basic environment for subsequent use of the VTable component.

Configure the deepseek model in the cursor.

Invoke the AI interaction panel in Cursor and generate code

After the project environment is set up, use cmd + i to invoke the AI interaction panel. We directly ask the AI to generate a basic table code of VTable for inserting into the file.

However, the initial generation result shows that the AI does not recognize the ListTable of the VTable, possibly because it cannot accurately identify the configuration of the VTable's ListTable.

Inject the official website tutorial into @Docs

To solve the above problems, we inject the official website tutorial into @Docs.

Explicitly specify "VisActor VTable" in @Docs in the prompt. After this operation, we were pleasantly surprised to find that the AI can correctly write the implementation logic according to the option in the VTable.

Code Application and Effect Demonstration

Copy the generated code into the corresponding file, run the project, and you can see the initial effect that the table has been correctly generated.

After that, we continued to ask the AI to modify the table style. The AI gave reasonable modification suggestions.

After running the project again, we got a presentation effect that is more in line with the requirements:

The advantages of combining the VTable component library with Cursor

Enhance development efficiency
Quick access: Directly consult the VTable API documentation through Cursor
Intelligent prompts: Precise code completion based on the VTable documentation
Enhance the development experience
Seamless integration: Directly obtain VTable usage guidance in the development environment
Real-time feedback: Quickly verify the code effect
Reduce learning costs
Document assistance: Consult VTable official examples at any time
Code generation: Automatically generate code that complies with VTable specifications
Improve code quality
Specification check: Ensure that the code complies with VTable best practices
Performance optimization: Automatically generate high-performance table configurations VisActorVTable provides developers with a powerful table solution. Combined with the use of AI****tools, it can significantly improve development efficiency and reduce learning costs. Welcome to visit the VisActor official website to learn more about VTable functions and cases.