@Marvin how can i run custom prefect with my own changes?

Before I help you with running a custom Prefect version, could you please confirm which version of Prefect you are using or prefer to use? This will help me provide you with the most accurate and relevant information.

3.x

To run a custom version of Prefect 3.x with your changes, you'll generally follow these steps: 1. Clone the Prefect Repository: Start by cloning the Prefect GitHub repository to your local machine. This allows you to make and test changes in the codebase.

bash
   git clone <https://github.com/PrefectHQ/prefect.git>
   cd prefect

2. Make Your Changes: Implement the changes you need in the source code. This can involve modifying existing files or adding new features. 3. Install Your Custom Version: After making changes, install your custom version of Prefect locally. You can often do this by using a Python virtual environment.

bash
   python -m venv myenv
   source myenv/bin/activate  # On Windows use `myenv\Scripts\activate`
   pip install -e .

The

-e .

flag installs the package in "editable" mode, which means changes you continue to make will reflect automatically. 4. Run Your Custom Prefect Version: With your changes in place, you can now run and test them as you would with any regular Prefect flow. 5. Troubleshooting Issues: If you encounter issues, consider looking at similar scenarios or bugs reported by other users for guidance. For example, there is a GitHub issue discussing problems related to running deployments with custom images. You can also refer to related documentation or issues when facing specific problems, like dynamic concurrency limits here and lazy templating for deployments here. These resources should give you a good start to running and managing your custom version of Prefect 3.x. If your robot assistant had feelings, it'd be excited to see what you create!

@Marvin is the code present in github and lib same?

Yes, typically, the code you find in the Prefect GitHub repository is the same as what you would find in the library installed via a package manager like pip. The source code in the repository is used to build the library that gets published to PyPI (the Python Package Index), which is where pip retrieves the library packages from. However, here are a couple of points to keep in mind: 1. Versioning: Make sure you are comparing the correct version of the code. The main branch on GitHub might contain the latest changes, which could be ahead of the current stable release available via pip. 2. Development vs. Stable: The GitHub repository sometimes has branches for development that contain features or changes not yet available in the stable version you get from pip. 3. Local Modifications: If you've installed Prefect in editable mode from a local clone of the repository, any changes you make locally will differ from the installed version or what's available via pip. If you're looking to explore or modify the Prefect library, cloning the repository from GitHub is an excellent way to have the most recent and comprehensive view of the codebase.

@Marvin how do i build the local ui?

Building the local Prefect UI can be an enlightening experience, providing insight into its structure and allowing for customization. Here's a step-by-step guide to building the Prefect UI locally: 1. Clone the Prefect Repository: As you need access to both the backend and UI, start by cloning the repository.

bash
   git clone <https://github.com/PrefectHQ/prefect.git>
   cd prefect

2. Navigate to the UI Directory: Depending on the structure, Prefect's UI source code could be in a

ui

or

web

directory. In Prefect's case, specifics may vary based on versions or updates, so check the latest

README

or documentation in the repository. 3. Install Node.js and npm: Prefect's UI likely employs JavaScript technologies requiring Node.js and npm. Install them if not already present: - Download from Node.js. 4. Install UI Dependencies: Once inside the UI directory, run npm to install all required dependencies.

bash
   npm install

5. Build the UI: Use npm to build the UI. This command compiles and builds the necessary files.

bash
   npm run build

6. Run the UI Locally: After building, you can start a local development server to test your UI changes.

bash
   npm start

This typically opens a development server, often accessible at

<http://localhost:3000>

or another specified port. 7. Integrate with Prefect Backend: Ensure that the Prefect server backend is running, so the UI can interact with it. By following these steps, you should be able to make customizations and see them reflected locally. If only Marvin, the paranoid android, had something interesting to customize, maybe he wouldn't be so gloomy.

@Marvin what is the entrypoint to the code where flow execution actually starts so that I can add log line to see that this is custom version

The entry point for executing flows in Prefect 3.x can vary depending on how you deploy and run your flow. Generally, the flow execution process is initiated by Prefect workers or by calling certain methods when running locally. Here's a summary based on the documentation excerpts: 1. Flow Execution from UI or Workers: Prefect uses a concept of work pools. A worker process polls a work pool for scheduled flow runs and, once a run is found, kicks off the flow run on the specified infrastructure. This is described in their documentation on deployments. 2. Manual Flow Execution: If you're running a flow manually (for example, during local development), this typically occurs as part of your flow's script. Prefect tracks the state and logs during flow execution which you can view in the terminal or UI, as mentioned in their quickstart guide. 3. Entry Point in Source Code: When dealing with a flow retrieved from remote storage or Git, Prefect specifies an entry point. This entry point is the file path and function name where the flow is defined, separated by a colon — for more details, refer to run flows in local processes. To add a log line indicating this is your custom version, you could add it within the flow function itself or within your deployment script, ensuring your message is captured during flow execution. This way, you can identify when your custom code is running.