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crop-planning/README.md
Crop Planning β€” Agricultural Crop Planning & Input Tracking Automation

Crop Planning & Input Tracking Automation

Production-grade Python patterns for automating crop planning, input tracking, and EPA/USDA compliance across modern field operations.

🌱 Live site β†’ www.crop-planning.com

Crop Planning is a deep, code-first reference for the engineers, farm managers, and AgTech teams who run modern agriculture as software. It covers the load-bearing work that rarely makes the demos but always breaks in production: turning fragmented machine telemetry, geospatial data, and regulatory text into deterministic Python pipelines that survive a full planting season β€” and generate audit-ready records that withstand third-party scrutiny.

Every page is written for real operational systems, not toy examples. The code is typed for Python 3.10+, retry-aware, structured-logged, and instrumented for observability, with each regulatory claim cited to the authoritative agency (EPA, USDA NRCS, USDA FSA, FAO).

What you'll find

The site is organised into four in-depth tracks, each with practical subtopics and hands-on guides:

  • Farm Data Ingestion & Field Boundary Synchronization β€” resilient pipelines that normalise equipment telemetry, validate schemas, reconcile GPS traces against canonical field polygons, version boundary changes, and ingest seed/fertilizer/pesticide inventory.
  • Crop Application Timing & Agronomic Validation β€” align inputs with growth stages, weather windows, buffer zones, and tunable thresholds through deterministic, auditable rule evaluation.
  • Automation Architecture & Compliance β€” compliance-first system design: spatial-temporal schemas, EPA/USDA rule mapping, RBAC, fallback routing, tamper-evident audit ledgers, hash chaining, and statutory PDF/CSV reporting.
  • Season Planning & Crop Rotation Optimization β€” turn agronomic rules into executable plans: model rotation constraints, optimise planting schedules against growing degree days, and generate variable-rate prescription maps.

Highlights

  • 50 in-depth guides spanning ingestion, agronomic timing, compliance architecture, and season planning β€” every one grounded in runnable, typed Python.
  • Real compliance encoding β€” restricted-entry intervals, maximum application rates, buffer-zone setbacks, and nutrient-management limits expressed as versioned, machine-readable logic.
  • Hand-authored diagrams β€” every page carries an original, theme-aware inline SVG that explains its hardest concept, with full accessibility metadata.
  • Structured data throughout β€” Article, Breadcrumb, HowTo, and FAQ JSON-LD on every page.

How it's built

The site is a fast, fully static build with no client-side framework:

  • Eleventy (11ty) static site generator with Nunjucks templates and a Markdown content model.
  • Prism for server-side syntax highlighting.
  • Hand-authored inline SVG diagrams, responsive tables, and a light/dark meadow-green design system.
  • Deployed to Cloudflare Pages.

Local development

npm install
npm run serve   # local dev server with live reload
npm run build   # production build β†’ _site/

Contributing & feedback

Issues and suggestions are welcome β€” open one on the GitHub repository. If a code sample, a compliance reference, or a diagram could be clearer or more correct, we want to know.

License & use

The guides are published for practitioners building agricultural automation. Treat the code samples as reference implementations to adapt to your own operation and jurisdiction β€” always validate regulatory logic against the current rules that apply to you before relying on it in production.


Built and maintained by Crop Planning Β· www.crop-planning.com

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    Production-grade Python patterns for automating crop planning, input tracking, and EPA/USDA compliance across field operations. Live at www.crop-planning.com

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