Files

Deeman 2db66efe77 feat: migrate transform to 3-layer architecture with per-layer schemas

Remove raw/ layer — staging models now read landing JSON directly.
Rename all model schemas from padelnomics.* to staging.*/foundation.*/serving.*.
Web app queries updated to serving.planner_defaults via SERVING_DUCKDB_PATH.
Supervisor gets daily sleep interval between pipeline runs.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

2026-02-22 19:04:40 +01:00

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CLAUDE.md — Padelnomics

This file tells Claude Code how to work in this repository.

Project Overview

Padelnomics is a SaaS application built with Quart (async Python), HTMX, and SQLite.

It includes a full data pipeline:

External APIs → extract → landing zone → SQLMesh transform → DuckDB → web app

Packages (uv workspace):

web/ — Quart + HTMX web application (auth, billing, dashboard)
extract/padelnomics_extract/ — data extraction to local landing zone
transform/sqlmesh_padelnomics/ — 3-layer SQL transformation (staging → foundation → serving)
src/padelnomics/ — CLI utilities, export_serving helper

Skills: invoke these for domain tasks

Working on extraction or transformation?

Use the data-engineer skill for:

Designing or reviewing SQLMesh model logic
Adding a new data source (extract + staging model)
Performance tuning DuckDB queries
Data modeling decisions (dimensions, facts, aggregates)
Understanding the 3-layer architecture

/data-engineer  (or ask Claude to invoke it)

Working on the web app UI or frontend?

Use the frontend-design skill for UI components, templates, or dashboard layouts.

Working on payments or subscriptions?

Use the paddle-integration skill for billing, webhooks, and subscription logic.

Key commands

# Install all dependencies
uv sync --all-packages

# Lint & format
ruff check .
ruff format .

# Run tests
uv run pytest tests/ -v

# Dev server
./scripts/dev_run.sh

# Extract data
LANDING_DIR=data/landing uv run extract

# SQLMesh plan + run (from repo root)
uv run sqlmesh -p transform/sqlmesh_padelnomics plan
uv run sqlmesh -p transform/sqlmesh_padelnomics plan prod

# Export serving tables (run after SQLMesh)
DUCKDB_PATH=local.duckdb SERVING_DUCKDB_PATH=analytics.duckdb \
    uv run python -m padelnomics.export_serving

Architecture documentation

Topic	File
Extraction patterns, state tracking, adding new sources	`extract/padelnomics_extract/README.md`
3-layer SQLMesh architecture, materialization strategy	`transform/sqlmesh_padelnomics/README.md`
Two-file DuckDB architecture (SQLMesh lock isolation)	`src/padelnomics/export_serving.py` docstring

Pipeline data flow

data/landing/
  ├── overpass/{year}/{month}/courts.json.gz
  ├── eurostat/{year}/{month}/urb_cpop1.json.gz
  └── playtomic/{year}/{month}/tenants.json.gz

data/lakehouse.duckdb       ← SQLMesh exclusive (staging → foundation → serving)

analytics.duckdb            ← serving tables only, web app read-only
  └── serving.*             ← atomically replaced by export_serving.py

Environment variables

Variable	Default	Description
`LANDING_DIR`	`data/landing`	Landing zone root (extraction writes here)
`DUCKDB_PATH`	`local.duckdb`	SQLMesh pipeline DB (exclusive write)
`SERVING_DUCKDB_PATH`	`analytics.duckdb`	Read-only DB for web app

Coding philosophy

Simple and procedural — functions over classes, no "Manager" patterns
Idempotent operations — running twice produces the same result
Explicit assertions — assert preconditions at function boundaries
Bounded operations — set timeouts, page limits, buffer sizes

Read coding_philosophy.md (if present) for the full guide.

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