Skip to main content
In this lesson, we explore how Cursor AI leverages your project’s full context—its file structure, code contents, environment variables, and more—to generate precise, actionable terminal commands.

Project Context Overview

Below is the entry point for our Flask-based Task Manager. Cursor AI reads this file to understand imports, configuration, and helper functions:
With this context loaded, Cursor AI can suggest commands and scaffolding that align perfectly with your codebase.

1. Installing PyTest and Updating Dependencies

To add testing support to your project:
You can prompt Cursor AI with:
Install PyTest and update requirements.txt
…and it will execute the above two commands for you.
Pin your test dependencies to avoid version conflicts. For example, add pytest>=8.0,<9.0 in your requirements.txt.

2. Generating a Test Suite

Cursor AI can scaffold test files based on your code structure. For example:
And populate it with:

3. Running Tests and Interpreting Failures

To run your tests:
Example output:
Failures like these are expected. Refining your prompt—by specifying file paths, function names, or expected output—will help Cursor AI generate more accurate assertions.

4. Profiling Data Processing

To profile your app.py or any CPU-bound function:
Analyze the results:

5. Handling Port Conflicts

When you start the Flask server and port 5000 is occupied, you’ll see an error:
If you encounter a port conflict, restart the server on a different port:

Best Practices for Context-Aware Commands

Example Prompt Context

Inline Terminal Questions

You can ask quick questions directly in the terminal:
Cursor AI responds:
A .pylintrc file is the configuration for pylint, a static code analysis tool for Python.

Watch Video