/* Full-Stack Platform */

Agspire Advisor Portal_

Agricultural management platform built to oversee field data programs, from validated field and lab data collection, to consolidated reports and analytics for stakeholders.

FastAPIPythonSQLAlchemyPostgreSQLPostGISReactTypeScriptTanStack RouterTanStack QueryTanStack TableZustandTailwinddbtTerraformAzure
~44.6KBackend Lines of Code
~134KFrontend Lines of Code
182API Endpoints
77Database Migrations
>95%Application Test Coverage

Overview_

/* What it does and why it exists */

What it does

Agspire Portal manages the full lifecycle of an agricultural field data program: administrators define exactly what data a project needs to collect — custom schemas, field types, and shared picklists — without waiting on a code release, then teams collect structured field and lab data against those schemas and roll it up into consolidated reports and analytics for stakeholders.

The platform is built for organizations that need both flexibility and control: every program may need a different data structure, but the underlying system still has to enforce permissions, prevent duplicate or corrupted records, and produce trustworthy reports across all of them.

The problem it replaces

Before this platform, defining a new program's data requirements meant ad-hoc spreadsheets and one-off data formats — inconsistent, hard to validate, and requiring a code change and deployment any time a program's data structure changed.

/* replaced with */

A single system where administrators self-service new data schemas, the platform enforces permissions and data integrity automatically, and every program's data rolls up into consistent, trustworthy reports.

Architecture_

/* Client-server, domain-organized, contract-generated, PostGIS-extended */

Backend~44.6K LOC
  • FastAPI + Repository PatternThin routers; service layer talks to the database exclusively through a Repository pattern
  • SQLAlchemy 2.0 (async) + AlembicAsync ORM with 77 incremental, reversible migrations
  • PostgreSQL 17 + PostGIS 3.5Relational DB with native geographic query support
  • Auto-generated API clientOpenAPI spec drives the frontend's TypeScript client, TanStack Query hooks, and Zod validation schemas
Frontend~134K LOC
  • React 19.2 + TypeScriptComponent-based UI with full type safety
  • TanStack Router, Query & TableFile-based routing, data-fetching/caching, and tabular UI
  • Tailwind 4 + Radix UIStyling and accessible component primitives
  • ZustandLocal state management

/* 20 backend feature modules, consolidated into 14 shared frontend domains */

ProjectsSchema DefinitionsSchema ResponsesPicklistsField DataLab DataReportsAnalyticsUsersPermissionsAuditNotificationsAuthOrganizations

The backend splits a few of these areas into narrower, single-responsibility modules — 20 in total — while the frontend groups the corresponding UI into 14 feature folders. Either side, a developer touches one well-defined domain rather than hunting through a monolith.

Key Challenges_

/* Complex problems, solved deliberately */

Production Readiness_

/* CI/CD · Testing · Infrastructure as Code */

CI/CD Pipelines

  • ·Path-filtered CI triggered on every PR
  • ·Backend linting, pytest against a real Postgres service container, and static type-checking
  • ·Frontend linting, type-checking, unit/component tests, and a mocked Playwright e2e pass
  • ·Full integrated e2e suite (real database) gated behind all of the above passing
  • ·Pre-commit hooks mirror these checks locally

Testing

  • ·65 backend test files, 37 frontend test files, 151 end-to-end test files
  • ·Mocked and integrated Playwright suites both wired into CI as gates
  • ·Regression tests simulate concurrency races directly, not just happy paths
  • ·Type-safe, generated API client eliminates integration drift

Infrastructure

  • ·Deployed on Azure — Container Apps, Static Web Apps, Key Vault, Container Registry
  • ·Terraform IaC with plan-on-PR, apply-on-merge, authenticated via OIDC
  • ·Database migrations and the dbt pipeline run as one-off Container Apps Jobs at deploy time
  • ·Application configuration validated at startup; missing env vars fail immediately
  • ·Secrets stored in Key Vault and injected at deploy time, never committed

Lessons Learned_

/* Trade-offs made honestly */

Trade-off made

Synchronous Report Generation

Report generation currently runs synchronously within the request, because its sections share a single database session — a deliberate simplification the codebase itself flags as a scaling constraint. As report complexity or data volume grows, introducing a task queue to generate reports asynchronously would decouple generation time from request/response time.

Trade-off made

In-Process-Only Caching

Caching today is limited to in-process, request-scoped memoization rather than a shared external cache. Reasonable at current scale, but it means cached data can't be shared across instances, and invalidation is implicitly tied to process lifetime.

Future investment

Deeper End-to-End Coverage

The mocked and integrated Playwright suites are correctly wired into CI as a gate, but currently cover only a small number of top-level workflows. Broadening the scenarios they cover would catch integration issues earlier.

Future investment

Shared Caching Layer

Moving from in-process memoization to a shared cache would improve hit rates and make invalidation explicit and observable.

/* Open to new opportunities */

Have a problem to solve?

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and start building something awesome.