https://github.com/mondo-mob/santas-helper

Santa's Helper allocation demonstration code
https://github.com/mondo-mob/santas-helper

Last synced: 8 months ago
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Santa's Helper allocation demonstration code

• Host: GitHub
• URL: https://github.com/mondo-mob/santas-helper
• Owner: mondo-mob
• License: mit
• Created: 2022-11-23T21:01:11.000Z (almost 3 years ago)
• Default Branch: main
• Last Pushed: 2022-12-14T03:52:17.000Z (almost 3 years ago)
• Last Synced: 2025-01-16T06:58:27.999Z (9 months ago)
• Language: Jupyter Notebook
• Size: 10.5 MB
• Stars: 2
• Watchers: 6
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
![Mondo Ventures Intro](etc/docs/images/mondo-post-202212-Santas-helper.jpg)

# Santa's Helper

This is the companion code for the [Santa's Helper](https://medium.com/@marc_at_mondo/santas-helper-7eca86c64e14) 

blog. The blog explains what the code is trying to do, but focuses on the logic output - rather than the "how to". 

This code is the "how to".

In order to setup and run this code, you will need a [Google Cloud](https://cloud.google.com/) account, with a 

credit card attached (this project requires some paid resources - although it won't cost much to run so long 

as you shut everything down once you've finished).

Next, create a new project in your GCP (Google Cloud Platform) account. The one used here and with the demonstration 

has a project id of `mv-santas-helper` (if you let Google select a random project id, you can see what it is 

by navigating to the `Cloud Overview` page).

![Cloud Overview - Project Id](etc/docs/images/00-cloud-overview.png)

## Technology

There are a number of technologies used for this project, which are listed below along 

with their respective usages.

- [BigQuery](https://cloud.google.com/bigquery) - Used as the underlying RDB (Relational Database). Sample child & 

  present data is created using views. Additional views are then added as required in order to 

  obtain the *score* for every child/parent combination.

- [Vertex AI](https://cloud.google.com/vertex-ai/) - Specifically, we are using a hosted/managed 

  [Jupyter](https://jupyter.org/) Notebook to review the data in BigQuery and demonstrate the allocation logic.

## Setup Steps

There are few steps required to setup your environment to make all the code run. These are listed below - in the 

order they should be executed.

- [Notebook Setup](etc/docs/notebook-setup.md) - Setting up the managed Jupyter Notebook in GCP

- [Service Account Setup](etc/docs/service-acc-setup.md) - Setting up the GCP Service Account - required by the 

  Jupyter Notebook to create and access the data in BigQuery.

- [BigQuery Setup](etc/docs/bigquery-setup.md) - Initialising BigQuery for use by the Notebook - specifically creating 

  a dataset.

- [Running the Notebook](etc/docs/running-the-notebook.md) - working through the algorithm and allocating presents.