This is a Next.js project bootstrapped with create-next-app.

Getting Started

First, run the development server:

npm run dev
# or
yarn dev
# or
pnpm dev
# or
bun dev

Open http://localhost:3000 with your browser to see the result.

You can start editing the page by modifying app/page.tsx. The page auto-updates as you edit the file.

This project uses next/font to automatically optimize and load Inter, a custom Google Font.

Learn More

To learn more about Next.js, take a look at the following resources:

• Next.js Documentation - learn about Next.js features and API.
• Learn Next.js - an interactive Next.js tutorial.

You can check out the Next.js GitHub repository - your feedback and contributions are welcome!

Deploy on Vercel

The easiest way to deploy your Next.js app is to use the Vercel Platform from the creators of Next.js.

Check out our Next.js deployment documentation for more details.

Architecture

flowchart LR
    classDef todo stroke-dasharray: 5 5

    subgraph "fairhold-data"
        S1[(Source 1)] <---> Script
        S2[(Source 2)] <---> Script
        S3[(Source 3)] <---> Script
    end

    subgraph "DB tools"
        LD[(Local disk)] --> UpdateData
        LD <--> Backup
        LD --> Restore
    end

    subgraph "Local development"
        NextLocal[Next.js App]
        PrismaLocal[Prisma]
        LocalDB[(Database)]
        PrismaLocal <--> NextLocal
        LocalDB <--> PrismaLocal
    end
    
    subgraph "CI/CD"
        GitHub["GitHub actions"]
    end


    subgraph "Production (Vercel)"
        NextProd[Next.js App]
        PrismaProd[Prisma]
        ProdDB[(Database)]
        PrismaProd <--> NextProd
        ProdDB <--> PrismaProd
    end

    Script -- Writes to --> LD

    Restore -- .env.local --> LocalDB
    Backup <-- .env.production --> ProdDB
    UpdateData:::todo -- .env.production --> ProdDB
    
    PrismaLocal -- "Migration files" --> GitHub
    GitHub -- "Merge to main" --> ProdDB

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Calculator docs

See our Github Wiki for data sources and decisions around why we calculate things a certain way.

Data update

1. Download the latest relevant datasets. A list of all sources can be found in the Wiki. NB: we now use the most recent release per-dataset, which means that years are inconsistent.
2. Clone the fairhold-data repo and put relevant datasets into their relevant directories, update any file names / paths as well as any column names or data shapes, if they have changed. Run main.py to generate all of the relevant CSVs.
3. Run convertToSQL.py to generate SQL that can be run against the database.
4. Update your local dev database by manually running all of the SQL, truncating tables first. (There is a backup of all the SQL in the Fairhold GDrive, which we didn't want to commit directly to the repo). You can do this in pgAdmin, using the variables in .env.local (see Fairhold 1Password vault). The prices_paid dataset is best run by copying straight from a CSV, since it's so large. On windows, you'll have to copy the file into Docker from Powershell to update the data in your local db: docker cp "path\to\your\csv\prices_paid.csv" fairhold-dashboard-postgres-1:/tmp/prices_paid.csv. A success message should show. You can then connect to the db by running psql -h localhost -p 5400 -U <username> -d <database>. Then, from COPY prices_paid FROM '/tmp/prices_paid.csv' WITH (FORMAT csv, HEADER true);
5. Run prisma:pull, prisma:generate and prisma:studio to confirm that all data has been updated as expected.
6. Check that all tests pass
7. If all is well, run the same SQL on production.