Production-grade Python patterns for automating crop planning, input tracking, and EPA/USDA compliance across modern field operations.
🌱 Live site → 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 — 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).
The site is organised into four in-depth tracks, each with practical subtopics and hands-on guides:
- Farm Data Ingestion & Field Boundary Synchronization — 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 — align inputs with growth stages, weather windows, buffer zones, and tunable thresholds through deterministic, auditable rule evaluation.
- Automation Architecture & Compliance — 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 — turn agronomic rules into executable plans: model rotation constraints, optimise planting schedules against growing degree days, and generate variable-rate prescription maps.
- 50 in-depth guides spanning ingestion, agronomic timing, compliance architecture, and season planning — every one grounded in runnable, typed Python.
- Real compliance encoding — restricted-entry intervals, maximum application rates, buffer-zone setbacks, and nutrient-management limits expressed as versioned, machine-readable logic.
- Hand-authored diagrams — every page carries an original, theme-aware inline SVG that explains its hardest concept, with full accessibility metadata.
- Structured data throughout — Article, Breadcrumb, HowTo, and FAQ JSON-LD on every page.
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.
npm install
npm run serve # local dev server with live reload
npm run build # production build → _site/Issues and suggestions are welcome — 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.
The guides are published for practitioners building agricultural automation. Treat the code samples as reference implementations to adapt to your own operation and jurisdiction — always validate regulatory logic against the current rules that apply to you before relying on it in production.
Built and maintained by Crop Planning · www.crop-planning.com