Building Neo4j Applications with Python -run the course locally

General Graph Academy
1

I try to begin course Building Neo4j Applications with Python with locally instance but I'm not sure which movie data set is correct to configure my database.

I try to use default dataset "load-movies.cypher" from neo browser samples but it doesn't work. My question : What dataset I should use locally in this course?

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Clarifying Problems with Running "Building Neo4j Applications with Python" Locally

Hi,

I'm going through the "Building Neo4j Applications with Python" course and while the beginner-level courses were very well explained, I'm running into several problems trying to complete this one locally.

Here’s what’s unclear or not working:

1. Which dataset should I use?

The course doesn’t clearly say what movie dataset needs to be imported.
I tried using the default load-movies.cypher available in the Neo4j Browser’s "Sample Data" panel, but after running it, the unit test (pytest -s tests/02_movie_list__test.py) still fails, even when I have pasted the "Working Solution" code from the course into the project.

2. Where to get the answer I'm supposed to enter on the course page?

I understand that answers must be typed into the course platform (e.g., the title of the highest-rated movie), but even after implementing the challenge locally, it's not clear where to read the expected value from—should I look at the web app (localhost:3000)? Logs? Neo4j Browser?

3. How to run and interact with the web app?

Should I:

  • Manually start the Flask app and use http://localhost:3000?
  • Or should I rely on the sandbox terminal and browser in the course interface?

The course doesn’t clearly explain which method is expected when working locally.

4. GitPod integration is unclear

When I try opening the GitHub project in GitPod, I’m not sure:

  • How to run the app from there
  • Which port to expose to access the web UI
  • How to test the changes and find answers to submit

Suggestion:

It would help a lot if the course included:

  • A clear, working dataset (e.g., a specific load-movies.cypher matching the course)
  • A quick-start guide or video showing how to set up and run the project locally
  • Instructions on where to view the app and extract results for answers
  • Clarification on GitPod usage (how to preview Flask UI, etc.)

Maybe I’m asking obvious questions here—but as a data engineer, I usually live in the backend world :grinning_face: of TensorFlow, Ray, and Pandas, writing backend pipelines and scripts. I rarely touch web interfaces, and Flask is a rare guest in my environment.

Thanks in advance for any guidance,
Peter

3

Hi Peter,

This course uses the "recommendations" dataset - GitHub - neo4j-graph-examples/recommendations: Neo4j Graph Example Movies Recommendation

However...

GraphAcademy assumes that you are using the assigned sandbox that was created for you when you enrolled in the course.

This is so GraphAcademy can check the sandbox instance you are using when verifying you have complete challenges, setup data specific to certain lessons, and setup environment variables in the IDE.

My advice would be to use the supplied sandbox for the course, and migrate to a local Neo4j instance once you have completed the course if you want to continue your learning.

The answers to the questions are output when running the tests e.g.

image
image1017Ă—379 26.1 KB

There are some instructions in the README about running the application, in summary, enter the following commands into the terminal.

export FLASK_APP=api
export FLASK_ENV=development
flask run

When the application runs you can open it using the preview which gives a side by side view:

image
image1912Ă—980 122 KB

I will be migrating this course off gitpod soon and will make some changes to update the content and I will take your feedback into account. Thanks.

Martin

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