Migrate Auth/Brewery/Location repositories to pure Dapper; rename Timer to RowVersion (#237)

* Integrate Spectre.Console into seed application, use async data loading

* Replace stored-procedure repositories with Dapper-based repositories

Removes the USP_* stored procedures for Auth, Location, and Brewery
data access in favour of services built with Dapper.

Adds a new Features.Locations slice and optimistic concurrency support
for the Brewery slice.

* Add new documentation for Dapper migration/database schema

* Update FluentAssertions to most recent open source ver

* Update XML doc comment in backend projects

* Modify brewery location dto to include denormalized data

* - Updated column names from 'Timer' to 'RowVersion' in schema.sql for
- Introduced new BeerPost entity and updated BreweryPost and BreweryPostLocation entities to use 'RowVersion' for concurrency.
- Modified UserAccount, UserCredential, UserVerification, City, StateProvince, and Country entities to use 'RowVersion' instead of 'Timer'.
- Updated tests and command handlers to reflect changes in concurrency token from 'Timer' to 'RowVersion'.
- Adjusted BreweryDto and BreweryDtoMapper to include 'RowVersion' and updated mapping logic accordingly.
- Ensured all repository methods and interfaces are aligned with the new concurrency handling approach.

* updates

* Add BeerStyle entity and related properties; refactor BreweryDto to remove BeerPosts

* Fix Api.Specs test failures: stale Timer column refs and missing test.user fixture

* Remove repository tests, usages of registration dto used in repo

* archive old stored procs/functions

* update stale docs

* Add instructions for generating cryptographically secure base64 secrets on macOS/Linux and Windows

README.md

@@ -4,7 +4,7 @@ The Biergarten App is a full-stack directory and discovery platform for
 breweries. It provides:
 
 - JWT-based user authentication, with email confirmation and refresh-token
-  rotation
+  reissue
 - A searchable database of brewery locations
 - An offline data-generation pipeline that uses large language models (LLMs)
   via Llama.cpp and Wikipedia to synthesize realistic seed data
@@ -24,6 +24,7 @@ Website + backend (active stack):
 
 - [Getting Started](docs/website/getting-started.md)
 - [Architecture](docs/architecture.md)
+- [Database](docs/website/database.md)
 - [Docker Guide](docs/website/docker.md)
 - [Testing](docs/website/testing.md)
 - [Environment Variables](docs/website/environment-variables.md)