From 7dfa328e8c0c5903374615290c53f21e398cb6c4 Mon Sep 17 00:00:00 2001 From: Felipe Alirio Baruja <210749711+BarujaFe1@users.noreply.github.com> Date: Mon, 13 Jul 2026 14:56:51 -0300 Subject: [PATCH] chore: improve portfolio quality, docs, tests and stability Co-authored-by: Cursor --- .env.example | 11 +- .github/workflows/ci.yml | 53 + .gitignore | 2 + README.md | 497 +-- SECURITY_NOTES.md | 23 + apps/api/app/api/cohorts.py | 7 +- apps/api/app/api/demo.py | 7 +- apps/api/app/api/events.py | 11 +- apps/api/app/api/friction.py | 13 +- apps/api/app/api/funnel.py | 7 +- apps/api/app/api/health.py | 8 +- apps/api/app/api/journeys.py | 9 +- apps/api/app/api/segments.py | 7 +- apps/api/app/models/schemas.py | 125 + apps/api/app/services/analytics.py | 136 +- apps/api/requirements.txt | 1 - apps/api/ruff.toml | 6 + apps/api/tests/test_api.py | 60 +- apps/web/.env.example | 3 +- apps/web/app/globals.css | 243 +- apps/web/app/layout.tsx | 4 +- apps/web/app/page.tsx | 262 +- apps/web/components/CohortMatrix.tsx | 54 + apps/web/components/FunnelChart.tsx | 61 + apps/web/components/KpiCard.tsx | 17 + apps/web/components/SkeletonGrid.tsx | 12 + apps/web/eslint.config.mjs | 14 + apps/web/lib/api.ts | 10 +- apps/web/lib/demo-snapshot.json | 230 +- apps/web/lib/lab.ts | 42 +- apps/web/package-lock.json | 4912 ++++++++++++++++++++++++-- apps/web/package.json | 9 +- apps/web/types/index.ts | 34 + apps/web/vercel.json | 3 +- docs/ARCHITECTURE.md | 74 + docs/AUDIT_REPORT.md | 82 + docs/DEPLOYMENT.md | 54 + docs/HANDOFF.md | 66 + docs/TECHNICAL_DECISIONS.md | 31 + docs/TESTING.md | 49 + docs/technical_methodology.md | 11 +- package.json | 12 + vercel.json | 2 +- 43 files changed, 6372 insertions(+), 902 deletions(-) create mode 100644 .github/workflows/ci.yml create mode 100644 SECURITY_NOTES.md create mode 100644 apps/api/app/models/schemas.py create mode 100644 apps/api/ruff.toml create mode 100644 apps/web/components/CohortMatrix.tsx create mode 100644 apps/web/components/FunnelChart.tsx create mode 100644 apps/web/components/KpiCard.tsx create mode 100644 apps/web/components/SkeletonGrid.tsx create mode 100644 apps/web/eslint.config.mjs create mode 100644 docs/ARCHITECTURE.md create mode 100644 docs/AUDIT_REPORT.md create mode 100644 docs/DEPLOYMENT.md create mode 100644 docs/HANDOFF.md create mode 100644 docs/TECHNICAL_DECISIONS.md create mode 100644 docs/TESTING.md create mode 100644 package.json diff --git a/.env.example b/.env.example index 0f96e56..2ad7845 100644 --- a/.env.example +++ b/.env.example @@ -1,15 +1,12 @@ # BehaviorGraph — environment template # Copy to .env and fill values. Never commit real secrets. -# Backend BEHAVIORGRAPH_ENV=development -DUCKDB_PATH=./data/uploads/behavior.duckdb + +# Optional: only needed if you wire a remote API later SUPABASE_URL= SUPABASE_ANON_KEY= -SUPABASE_SERVICE_ROLE_KEY= # Frontend (Next.js) -NEXT_PUBLIC_API_BASE=http://127.0.0.1:8000 - -# Optional -GITHUB_TOKEN= +# Leave empty to use the embedded synthetic snapshot (static lab mode). +NEXT_PUBLIC_API_URL=http://127.0.0.1:8000 diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml new file mode 100644 index 0000000..02b2bc3 --- /dev/null +++ b/.github/workflows/ci.yml @@ -0,0 +1,53 @@ +name: CI + +on: + push: + branches: [main, "chore/**"] + pull_request: + +jobs: + api: + name: API (pytest + ruff) + runs-on: ubuntu-latest + defaults: + run: + working-directory: apps/api + steps: + - uses: actions/checkout@v4 + - uses: actions/setup-python@v5 + with: + python-version: "3.12" + cache: pip + cache-dependency-path: apps/api/requirements.txt + - name: Install + run: | + python -m pip install --upgrade pip + pip install -r requirements.txt + - name: Ruff + run: ruff check app tests + - name: Pytest + run: pytest -q + + web: + name: Web (lint + typecheck + build) + runs-on: ubuntu-latest + defaults: + run: + working-directory: apps/web + steps: + - uses: actions/checkout@v4 + - uses: actions/setup-node@v4 + with: + node-version: "20" + cache: npm + cache-dependency-path: apps/web/package-lock.json + - name: Install + run: npm ci + - name: Lint + run: npm run lint + - name: Typecheck + run: npm run typecheck + - name: Build + run: npm run build + env: + GITHUB_PAGES: "false" diff --git a/.gitignore b/.gitignore index f8f175d..2cf23da 100644 --- a/.gitignore +++ b/.gitignore @@ -49,3 +49,5 @@ Thumbs.db *.duckdb.wal .gh-pages-tmp/ BehaviorGraph-gh-pages/ +apps/api/.venv/ +apps/web/out/ diff --git a/README.md b/README.md index 43b08a1..3e98545 100644 --- a/README.md +++ b/README.md @@ -3,18 +3,16 @@

BehaviorGraph

-

Eventos de uso em jornadas, funis, cohorts, fricções e sinais de adoção.

-

Turn product events into journeys, funnels, cohorts, friction and adoption signals.

+

Which paths lead to activation, abandonment, or habit?

+

Behavioral analytics lab: event taxonomy → nested funnel → retention cohorts → journey graph → product opportunity memo.

🌐 Live Demo • - PT-BR / English Overview • - Preview • - Screenshots • - Stack • - Architecture • - Quick Start • - Author + Problem • + Solution • + Architecture • + Quick Start • + Portfolio value

@@ -23,8 +21,7 @@ Python FastAPI NetworkX - DuckDB - Product Analytics + Responsible Analytics

@@ -34,456 +31,238 @@ --- -## 1. Visão Geral / Overview +## Status -O **BehaviorGraph** é um produto de behavioral analytics criado para transformar eventos de uso em **jornadas, segmentos, fricções, cohorts e sinais de adoção**. +| Item | State | +|---|---| +| Scope | Portfolio lab / MVP (synthetic seed) | +| Live Demo | [barujafe1.github.io/BehaviorGraph](https://barujafe1.github.io/BehaviorGraph/) | +| Repo homepage | configured | +| CI | GitHub Actions (API + Web) | +| Production tracking | **Out of scope** | -Ele existe para responder não apenas *“quantos usuários converteram?”*, mas *“quais caminhos levam à ativação, abandono ou uso recorrente?”*. Em vez de tratar tracking como log bruto, o BehaviorGraph organiza taxonomia, funil de ativação, retenção, grafo de caminhos e um memo de oportunidade de produto. +> **Responsible Product Analytics Notice** +> Synthetic SaaS onboarding events only. Not production telemetry, not Mixpanel, and not causal attribution from path graphs. -O projeto foi desenvolvido por **Felipe Alirio Baruja** como peça de portfólio, conectando product analytics, instrumentação e narrativa de decisão de produto. +--- -> **Responsible Product Analytics Notice** -> O BehaviorGraph usa dataset sintético no MVP. Ele **não** deve ser tratado como telemetria de produção, atribuição causal automática ou substituto de suites completas de product analytics. +## Problem -### 🌐 Live Demo +Digital products collect events, but teams still struggle to answer: -**Demo pública (lab):** [https://barujafe1.github.io/BehaviorGraph/](https://barujafe1.github.io/BehaviorGraph/) +- Which activation steps lose users? +- Which session transitions dominate? +- Which cohorts retain after week 0? +- Where is friction high enough to deserve a product bet? -A demo é **frontend-only** com snapshot sintético embutido (taxonomia, funil, cohorts, journey graph, friction e opportunity memo). O projeto Vercel `behaviorgraph` já está linkado para produção quando a cota diária resetar (`https://behaviorgraph.vercel.app`). O FastAPI local continua disponível para o fluxo full-stack via `start.bat`. +Conversion vanity metrics (“how many signed up?”) hide the path. --- -## ✨ Product Preview +## Solution -

- BehaviorGraph Behavior Cockpit -

+**BehaviorGraph** converts a synthetic event stream into a product narrative: -O BehaviorGraph apresenta uma experiência de mapa comportamental: cockpit de ativação, taxonomia de eventos, funil, cohorts, journey graph, friction radar e opportunity memo. +1. **Event taxonomy** — owned contract (name, category, owner) +2. **Nested activation funnel** — unique users remaining in prior steps +3. **Retention cohorts** — first-seen week with true W0–W4 offsets +4. **Journey graph** — NetworkX session transitions +5. **Segments + friction radar** — activated / at-risk / power + drop severity +6. **Opportunity memo** — hypotheses with explicit limitations --- -## 2. Por que este projeto importa? / Why this project matters +## Core features -* **Eventos sem narrativa não viram decisão:** times coletam tracking, mas não traduzem o rastro em caminhos de ativação e abandono. -* **Conversão sozinha é métrica rasa:** o valor está em entender *quais sequências* levam a hábito ou churn precoce. -* **Taxonomia é contrato de produto:** sem ownership de eventos, funis e cohorts mentem com elegância. -* **Produto full-stack, não notebook:** FastAPI + Next.js com fluxo ponta a ponta para demo e entrevista. +- Taxonomy center for instrumentation discussions +- Nested unique-user activation funnel (+ conversion from start) +- Retention cohort heat matrix +- Journey path edges with weights +- Friction severity bands (`low` / `medium` / `high`) +- Product opportunity memo (action + impact hypothesis + limits) +- Static lab snapshot for reliable public demos +- Optional FastAPI backend for local full-stack runs --- -## 🧠 O diferencial do BehaviorGraph / What makes BehaviorGraph different - -### Português -O BehaviorGraph não é um dashboard genérico de métricas. Ele combina taxonomia, funil de ativação, cohorts, grafo de jornada e fricção em uma experiência de product analytics. +## Architecture -Ele mostra não apenas o volume de eventos, mas também: -- quais passos da ativação perdem usuários; -- quais transições dominam as sessões; -- quais segmentos merecem atenção (activated / at-risk / power); -- onde a fricção aparece no caminho; -- quais hipóteses de produto fazem sentido — e quais limites impedem overclaim. +```text +CSV seed → FastAPI analytics (Pandas/NetworkX/Pydantic) + ↓ + demo-snapshot.json (static) + ↓ + Next.js cockpit (Recharts + matrix) +``` -### English -BehaviorGraph is not a generic metrics dashboard. It combines taxonomy, activation funnel, cohorts, journey graph and friction into one product-analytics experience. +Details: [docs/ARCHITECTURE.md](./docs/ARCHITECTURE.md) · decisions: [docs/TECHNICAL_DECISIONS.md](./docs/TECHNICAL_DECISIONS.md) -It shows not only event volume, but also: -- which activation steps lose users; -- which transitions dominate sessions; -- which segments deserve attention (activated / at-risk / power); -- where friction appears on the path; -- which product hypotheses make sense — and which limits block overclaiming. +

+ BehaviorGraph architecture +

--- -## 🎯 Problema que resolve / The problem it solves +## Stack -Em produtos digitais, equipes costumam sofrer com: -- eventos coletados sem taxonomia clara; -- funis baseados em contagem bruta em vez de usuários únicos; -- ausência de leitura de jornada (path); -- cohorts frágeis ou mal definidos; -- fricção invisível até o churn já ter acontecido; -- relatórios que mostram “quantos”, mas não “por qual caminho”. - -O **BehaviorGraph** cria uma camada interpretável entre o evento bruto e a decisão de produto. +| Layer | Choices | +|---|---| +| Frontend | Next.js 15, React 19, TypeScript, Recharts | +| Backend | FastAPI, Pydantic v2, Pandas, NetworkX | +| Data | Synthetic CSV seed (`data/seed`) | +| Quality | Pytest, Ruff, ESLint, `tsc`, GitHub Actions | +| Hosting | GitHub Pages (live) + Vercel-ready static export | --- -## 🧩 Proposta / Analytical Pipeline - -O BehaviorGraph processa eventos sintéticos (MVP) e entrega uma visão estruturada de ativação, retenção, caminhos e oportunidades: - -```txt -Synthetic Event Stream / Demo Dataset - ↓ -Event taxonomy validation - ↓ -Activation funnel (unique users) - ↓ -Retention cohorts (week-based) - ↓ -Journey path graph (NetworkX transitions) - ↓ -Segmentation (activated / at-risk / power) - ↓ -Friction radar (drops + error-like events) - ↓ -Product opportunity memo -``` - ---- - -## 📸 Screenshots +## Screenshots - - - -
- Event Taxonomy Center -
- Event Taxonomy Center — owned event contract, categories and product ownership. - 		Activation Funnel -
- Activation Funnel — unique-user conversion across onboarding steps. +
Activation Funnel — nested unique-user conversion
Retention Cohorts -
- Retention Cohorts — week-based retention matrix for demo cohorts. - 		- Journey Path Graph -
- Journey Path Graph — NetworkX session transitions as a behavioral map. +
Retention Cohorts — first-seen week matrix
- Feature Adoption Board -
- Feature Adoption Board — which features stick after activation. + Journey Graph +
Journey Graph — session transitions 		- Friction Radar -
- Friction Radar — drop severity and error-like event signals. + Opportunity Memo +
Opportunity Memo — hypotheses + limits
--- -## 📄 Product Opportunity Memo - -

- BehaviorGraph Opportunity Memo -

- -O memo consolida drops do funil, hipóteses de produto, ações sugeridas e limitações explícitas — pronto para discussão de discovery e priorização. - ---- - -## 📌 Estudo de Caso / Case Study - -### 📌 Estudo de Caso: Onboarding SaaS Sintético -O dataset demo simula onboarding de um SaaS com ~220 usuários, milhares de eventos e sessões com signup, onboarding, feature use, ativação, abandono e retorno. O BehaviorGraph monta o funil de ativação, cohorts semanais, grafo de transições e um radar de fricção. - -A leitura é exploratória e orientada a produto: drops entre passos, segmentos at-risk e hipóteses de melhoria de instrumentação/UX — sem pretender atribuição causal automática. - -### 📌 Case Study: Synthetic SaaS Onboarding -The demo dataset simulates SaaS onboarding with ~220 users, thousands of events and sessions covering signup, onboarding, feature use, activation, abandonment and return visits. BehaviorGraph builds the activation funnel, weekly cohorts, transition graph and a friction radar. - -The reading is exploratory and product-oriented: step drops, at-risk segments and instrumentation/UX hypotheses — without claiming automatic causal attribution. - ---- - -## 🧭 Visual Story / Jornada Analítica - -A experiência do BehaviorGraph foi pensada como uma jornada de product analytics: -```txt -1. Carregar o dataset sintético de eventos -2. Revisar a taxonomia (contrato de eventos) -3. Ler o cockpit de ativação (users / events / rate) -4. Percorrer o funil e localizar o maior drop -5. Inspecionar cohorts de retenção -6. Explorar o journey path graph -7. Segmentar activated / at-risk / power -8. Abrir o friction radar -9. Fechar com o product opportunity memo e limitações -``` - ---- - -## ⚙️ Funcionalidades Principais / Core Features - -### Event Taxonomy Center -Contrato de eventos com categoria, descrição e ownership — base para funis e cohorts confiáveis. - -### Activation Funnel -Funil de ativação por usuários únicos, com conversão passo a passo e leitura de drop. - -### Retention Cohorts -Cohorts semanais a partir do first-seen, com retenção por offset de semana. - -### Journey Path Graph -Grafo de transições de sessão construído com NetworkX para mapear caminhos frequentes. - -### Segment Explorer -Segmentos iniciais: Activated, At-risk/friction e Power explorers. - -### Friction Radar + Opportunity Memo -Drops priorizados, sinais de erro/abandono e hipóteses de produto com limitações explícitas. - ---- - -## 🛠️ Stack / Tecnologias - -### Frontend -- **Framework:** Next.js 15 (App Router) & React 19 -- **Linguagem:** TypeScript -- **Visualização:** Recharts & React Flow (`@xyflow/react`) -- **Ícones:** Lucide Icons - -### Backend / Analytics -- **Framework API:** FastAPI & Uvicorn (Python) -- **Processamento:** Pandas + NumPy -- **Grafos:** NetworkX -- **Exploração:** DuckDB (preparado no scaffold) -- **Validação:** Pydantic v2 -- **Testes:** Pytest - -### Infra sugerida (roadmap) -- Supabase/Postgres para persistência -- Vercel para frontend -- Endpoint de ingestão de eventos (Fase 3 / SDK) - ---- - -## 🧱 Arquitetura / Architecture +## Quick Start -O projeto adota um monorepo simplificado: - -```text -BehaviorGraph/ -├── apps/ -│ ├── web/ # Frontend Next.js (App Router) -│ │ ├── app/ # Cockpit principal -│ │ ├── components/ # UI / charts / graph views -│ │ ├── lib/ # API client -│ │ └── types/ # Tipos TypeScript -│ │ -│ └── api/ # Backend FastAPI -│ ├── app/ -│ │ ├── api/ # Endpoints (/demo, /funnel, /journeys, ...) -│ │ ├── models/ # Schemas -│ │ └── services/ # Funnel, cohorts, graph, friction -│ └── tests/ # Pytest -│ -├── data/ -│ └── seed/ # events_demo.csv + event_taxonomy.csv -│ -├── docs/ # Pitch, metodologia e roadmap -├── assets/ # Ícone, hero, architecture e screenshots -├── scripts/ # Geração de seed e assets -├── start.bat # Inicializador Windows -└── README.md # Esta documentação -``` - ---- - -## 🧱 Visual Architecture - -

- BehaviorGraph visual architecture -

+### Prerequisites +- Node.js 20+ +- Python 3.12 recommended +- Git -BehaviorGraph follows a traceable behavioral flow: events enter through taxonomy, become funnel/cohorts/graph insights, then surface as friction and product opportunity narrative. - ---- - -## 🔁 Data Flow Pipeline - -```txt -Raw / Synthetic Events - ↓ -Taxonomy mapping & ownership - ↓ -Activation funnel (unique users) - ↓ -Retention cohorts (first-seen week) - ↓ -Session transition graph (NetworkX) - ↓ -Segments + friction severity - ↓ -Opportunity memo (hypotheses + limits) - ↓ -Next.js cockpit -``` - ---- - -## 🚀 Quick Start / Início Rápido - -### Pré-requisitos -- **Node.js** v20 ou superior -- **Python** v3.10 ou superior (preferencialmente 3.12) -- **Git** - -### Opção 1 — Execução integrada no Windows -Na pasta raiz do projeto: +### Option A — Windows one-click ```bash start.bat ``` -O script cria o venv Python, instala dependências, sobe FastAPI em `:8000`, Next.js em `:3000` e abre o navegador. -### Opção 2 — Execução manual +### Option B — Static web lab only +```bash +cd apps/web +npm install +npm run dev +``` +Open [http://localhost:3000](http://localhost:3000) — uses embedded snapshot (no API required). -#### 1. Backend FastAPI (`apps/api`) +### Option C — Full-stack local ```bash +# API cd apps/api python -m venv .venv -.venv\Scripts\activate # Windows -source .venv/bin/activate # Linux/macOS +.venv\Scripts\activate # Windows +# source .venv/bin/activate # Linux/macOS pip install -r requirements.txt uvicorn app.main:app --reload --port 8000 -``` -*API em [http://127.0.0.1:8000](http://127.0.0.1:8000). Docs em `/docs`.* -#### 2. Frontend Next.js (`apps/web`) -```bash +# Web (new terminal) cd apps/web +# set NEXT_PUBLIC_API_URL=http://127.0.0.1:8000 in .env.local npm install npm run dev ``` -*Frontend em [http://localhost:3000](http://localhost:3000).* -#### 3. Regenerar seed / assets (opcional) -```bash -python scripts/generate_seed.py -pip install pillow -python scripts/generate_assets.py -``` +### Environment variables +See [`.env.example`](./.env.example) and [`apps/web/.env.example`](./apps/web/.env.example). + +| Variable | Purpose | +|---|---| +| `NEXT_PUBLIC_API_URL` | Optional FastAPI base URL; empty = snapshot lab mode | +| `GITHUB_PAGES=true` | Adds `/BehaviorGraph` basePath for Pages builds | + +Never commit `.env.local` or secrets. See [SECURITY_NOTES.md](./SECURITY_NOTES.md). --- -## 🧪 Scripts e Testes / Scripts and Testing +## Tests & quality -### Backend (Pytest) ```bash +# API cd apps/api -.venv\Scripts\python -m pytest -``` +.venv\Scripts\python -m pytest -q +.venv\Scripts\ruff check app tests -### Frontend -```bash +# Web cd apps/web npm run lint npm run typecheck npm run build ``` ---- - -## 📊 Metodologia / Behavioral Methodology - -* **Unique-user funnel:** conversão por usuários distintos em cada passo de ativação. -* **Week cohorts:** first-seen define a cohort; retenção mede presença em semanas seguintes. -* **Path graph:** transições ordenadas por `session_id` agregadas com NetworkX. -* **Friction bands:** drops classificados por severidade (`low` / `medium` / `high`). -* **Explicit limits:** memo de oportunidade declara o que o MVP não prova (causalidade, produção, atribuição Markov). +More: [docs/TESTING.md](./docs/TESTING.md) · Deploy: [docs/DEPLOYMENT.md](./docs/DEPLOYMENT.md) --- -## 🛡️ Escopo, Ética e Boas Práticas +## Trade-offs -* **Synthetic-first MVP:** sem tracking real de produção. -* **Sem overclaim causal:** caminhos são exploratórios. -* **Taxonomia antes de volume:** qualidade do evento > quantidade de eventos. -* **Não é clone de Mixpanel:** foco em narrativa de produto e instrumentação. +| Choice | Gain | Cost | +|---|---|---| +| Static snapshot demo | Reliable public URL | Must regenerate after analytics changes | +| Nested funnel | Honest drop-offs | Stricter than independent counts | +| Transition graph | Clear journey story | Not attribution / not causal | +| Lab scope | Portfolio clarity | Not a full product-analytics suite | --- -## 🧭 Roadmap do Produto +## Roadmap -* **MVP:** tracker demo, dataset sintético, taxonomia, funil, cohorts, path graph, segmentos, friction, opportunity memo. -* **Fase 2:** eventos órfãos, análise de sequência, cohorts comportamentais, alertas de ativação, recomendações de instrumentação. -* **Fase 3:** SDK mínimo, ingestão near-real-time, experiment tags, app demo + assistant de perguntas de produto. -* **Não entra:** competir com Mixpanel; dashboard genérico; tracking real no MVP. +- **MVP (now):** taxonomy, nested funnel, cohorts, graph, friction, memo, static demo, CI +- **Phase 2:** orphan events, sequence analysis, behavioral cohorts, activation alerts +- **Phase 3:** minimal SDK, near-real-time ingest, experiment tags, product Q&A assistant ---- - -## 💼 Valor para Portfólio / Portfolio Value - -O BehaviorGraph demonstra competências para **Product Analytics, Analytics Engineering e Product Data**: -- design de taxonomia de eventos; -- funis e cohorts com definição explícita; -- grafos de jornada e leitura de fricção; -- conexão entre evidência comportamental e decisão de produto; -- arquitetura full-stack (Next.js + FastAPI). - ---- - -## 📚 Documentação Complementar - -- [docs/portfolio_pitch.md](./docs/portfolio_pitch.md) — roteiro de entrevista e demo de 3 minutos -- [docs/technical_methodology.md](./docs/technical_methodology.md) — schema, funil, cohorts e grafo -- [docs/product_roadmap.md](./docs/product_roadmap.md) — MVP, Fase 2 e Fase 3 +Non-goals: Mixpanel clone, generic metrics dashboard, production tracking in MVP. --- -## 🖼️ GitHub Social Preview +## What this project demonstrates -Uma imagem para visualização social está disponível em: -```txt -assets/social-preview.png -``` -*Dimensão recomendada: 1280x640, <1MB. Upload em: Repository Settings → Social Preview.* +- Product analytics thinking (instrumentation → narrative → decision) +- Correct funnel/cohort definitions (not vanity charts) +- Full-stack delivery (FastAPI + Next.js) with a resilient static demo mode +- Responsible analytics communication (limits stated in UI + docs) +- Engineering hygiene (Pydantic contracts, tests, CI, deploy docs) --- -## 🔖 GitHub Repository Metadata +## How I would present this in an interview -### About sugerido -```txt -Behavioral analytics studio: event taxonomy, activation funnels, retention cohorts, journey graphs and product opportunity memos. -``` +1. **Hook (20s):** “Conversion asks *how many*; BehaviorGraph asks *which paths*.” +2. **Taxonomy (40s):** Show owned events as a product contract. +3. **Funnel (60s):** Explain nested unique users and the largest drop. +4. **Cohorts (40s):** First-seen week + W1 retention — why offset math matters. +5. **Journey + friction (40s):** Transitions as exploration, not causation. +6. **Memo (40s):** Turn drops into hypotheses with limitations. +7. **Close (20s):** Lab scope honesty — what I’d build next vs what I refuse to overclaim. -### Topics sugeridos -```txt -product-analytics -behavioral-analytics -event-tracking -activation-funnel -retention-cohorts -journey-analytics -networkx -fastapi -nextjs -typescript -python -duckdb -portfolio-project -data-visualization -``` +Pitch notes: [docs/portfolio_pitch.md](./docs/portfolio_pitch.md) --- -## 👤 Autor / Author - -Desenvolvido por **Felipe Alirio Baruja**. +## Author -- **Portfolio:** [barujafe.vercel.app](https://barujafe.vercel.app/) -- **GitHub:** [@BarujaFe1](https://github.com/BarujaFe1) -- **LinkedIn:** [Gustavo Felipe Alirio Baruja](https://www.linkedin.com/in/barujafe/) +**Felipe Alirio Baruja** ---- +- Portfolio: [barujafe.vercel.app](https://barujafe.vercel.app/) +- GitHub: [@BarujaFe1](https://github.com/BarujaFe1) +- LinkedIn: [Gustavo Felipe Alirio Baruja](https://www.linkedin.com/in/barujafe/) -## 📄 Licença / License +## License -MIT License. Copyright (c) 2026 Felipe Alirio Baruja. -O código está disponível sob a licença MIT caso o arquivo `LICENSE` esteja presente no repositório. +MIT License © 2026 Felipe Alirio Baruja diff --git a/SECURITY_NOTES.md b/SECURITY_NOTES.md new file mode 100644 index 0000000..4b1d423 --- /dev/null +++ b/SECURITY_NOTES.md @@ -0,0 +1,23 @@ +# Security Notes — BehaviorGraph + +## Scope +Portfolio lab demo. Synthetic SaaS onboarding events only. No production user tracking. + +## Findings (quality pass) + +### Local Vercel OIDC token (handled) +- **Location:** `apps/web/.env.local` (developer machine only) +- **Content type:** Vercel CLI OIDC token for local project linking +- **Git status:** Ignored by `apps/web/.gitignore` (`.env.local`) and root `.gitignore` +- **Action taken:** Confirmed not tracked by git. Do not commit. Rotate via Vercel if the token was ever pasted into chat/logs. +- **Do not republish** the token value in issues, PRs, or docs. + +### Secrets policy +- Never commit `.env`, `.env.local`, service role keys, or Supabase credentials. +- Use `.env.example` templates only. +- Demo data under `data/seed/` is synthetic and safe to publish. + +### Responsible analytics +- The product must not claim causal attribution from journey graphs. +- Activation/retention metrics are exploratory on synthetic data. +- No PII is present in the seed CSVs (`user_XXXX` ids only). diff --git a/apps/api/app/api/cohorts.py b/apps/api/app/api/cohorts.py index 5025624..d85cebc 100644 --- a/apps/api/app/api/cohorts.py +++ b/apps/api/app/api/cohorts.py @@ -1,10 +1,11 @@ from fastapi import APIRouter +from app.models.schemas import CohortsResponse from app.services.analytics import build_retention_cohorts router = APIRouter(tags=["cohorts"]) -@router.get("/cohorts/retention") -def retention_cohorts() -> dict: - return build_retention_cohorts() +@router.get("/cohorts/retention", response_model=CohortsResponse) +def retention_cohorts() -> CohortsResponse: + return CohortsResponse.model_validate(build_retention_cohorts()) diff --git a/apps/api/app/api/demo.py b/apps/api/app/api/demo.py index 9cef9f2..0d0fe3b 100644 --- a/apps/api/app/api/demo.py +++ b/apps/api/app/api/demo.py @@ -1,10 +1,11 @@ from fastapi import APIRouter +from app.models.schemas import DemoSummary from app.services.analytics import load_demo_summary router = APIRouter(tags=["demo"]) -@router.get("/demo") -def demo_summary() -> dict: - return load_demo_summary() +@router.get("/demo", response_model=DemoSummary) +def demo_summary() -> DemoSummary: + return DemoSummary.model_validate(load_demo_summary()) diff --git a/apps/api/app/api/events.py b/apps/api/app/api/events.py index 140d718..97bd01f 100644 --- a/apps/api/app/api/events.py +++ b/apps/api/app/api/events.py @@ -1,15 +1,16 @@ -from fastapi import APIRouter +from fastapi import APIRouter, Query +from app.models.schemas import TaxonomyResponse from app.services.analytics import load_event_taxonomy, load_recent_events router = APIRouter(tags=["events"]) -@router.get("/events/taxonomy") -def event_taxonomy() -> dict: - return load_event_taxonomy() +@router.get("/events/taxonomy", response_model=TaxonomyResponse) +def event_taxonomy() -> TaxonomyResponse: + return TaxonomyResponse.model_validate(load_event_taxonomy()) @router.get("/events/recent") -def recent_events(limit: int = 50) -> dict: +def recent_events(limit: int = Query(default=50, ge=1, le=500)) -> dict: return {"events": load_recent_events(limit=limit)} diff --git a/apps/api/app/api/friction.py b/apps/api/app/api/friction.py index 8ce2999..3adf71b 100644 --- a/apps/api/app/api/friction.py +++ b/apps/api/app/api/friction.py @@ -1,15 +1,16 @@ from fastapi import APIRouter +from app.models.schemas import FrictionResponse, OpportunityMemo from app.services.analytics import build_friction_points, build_opportunity_memo router = APIRouter(tags=["friction"]) -@router.get("/friction") -def friction_points() -> dict: - return build_friction_points() +@router.get("/friction", response_model=FrictionResponse) +def friction_points() -> FrictionResponse: + return FrictionResponse.model_validate(build_friction_points()) -@router.get("/opportunities") -def opportunities() -> dict: - return build_opportunity_memo() +@router.get("/opportunities", response_model=OpportunityMemo) +def opportunities() -> OpportunityMemo: + return OpportunityMemo.model_validate(build_opportunity_memo()) diff --git a/apps/api/app/api/funnel.py b/apps/api/app/api/funnel.py index 18029b6..f97d8d0 100644 --- a/apps/api/app/api/funnel.py +++ b/apps/api/app/api/funnel.py @@ -1,10 +1,11 @@ from fastapi import APIRouter +from app.models.schemas import FunnelResponse from app.services.analytics import build_activation_funnel router = APIRouter(tags=["funnel"]) -@router.get("/funnel/activation") -def activation_funnel() -> dict: - return build_activation_funnel() +@router.get("/funnel/activation", response_model=FunnelResponse) +def activation_funnel() -> FunnelResponse: + return FunnelResponse.model_validate(build_activation_funnel()) diff --git a/apps/api/app/api/health.py b/apps/api/app/api/health.py index 3ecf23f..cac8d52 100644 --- a/apps/api/app/api/health.py +++ b/apps/api/app/api/health.py @@ -1,8 +1,10 @@ from fastapi import APIRouter +from app.models.schemas import HealthResponse + router = APIRouter(tags=["health"]) -@router.get("/health") -def health() -> dict[str, str]: - return {"status": "ok", "service": "behaviorgraph-api"} +@router.get("/health", response_model=HealthResponse) +def health() -> HealthResponse: + return HealthResponse(status="ok", service="behaviorgraph-api") diff --git a/apps/api/app/api/journeys.py b/apps/api/app/api/journeys.py index 377a4db..db7a9ce 100644 --- a/apps/api/app/api/journeys.py +++ b/apps/api/app/api/journeys.py @@ -1,10 +1,11 @@ -from fastapi import APIRouter +from fastapi import APIRouter, Query +from app.models.schemas import JourneyGraph from app.services.analytics import build_journey_graph router = APIRouter(tags=["journeys"]) -@router.get("/journeys/graph") -def journey_graph(limit_edges: int = 40) -> dict: - return build_journey_graph(limit_edges=limit_edges) +@router.get("/journeys/graph", response_model=JourneyGraph) +def journey_graph(limit_edges: int = Query(default=40, ge=1, le=200)) -> JourneyGraph: + return JourneyGraph.model_validate(build_journey_graph(limit_edges=limit_edges)) diff --git a/apps/api/app/api/segments.py b/apps/api/app/api/segments.py index 4cb97d2..4009c10 100644 --- a/apps/api/app/api/segments.py +++ b/apps/api/app/api/segments.py @@ -1,10 +1,11 @@ from fastapi import APIRouter +from app.models.schemas import SegmentsResponse from app.services.analytics import build_segments router = APIRouter(tags=["segments"]) -@router.get("/segments") -def segments() -> dict: - return build_segments() +@router.get("/segments", response_model=SegmentsResponse) +def segments() -> SegmentsResponse: + return SegmentsResponse.model_validate(build_segments()) diff --git a/apps/api/app/models/schemas.py b/apps/api/app/models/schemas.py new file mode 100644 index 0000000..7978ac2 --- /dev/null +++ b/apps/api/app/models/schemas.py @@ -0,0 +1,125 @@ +"""Pydantic response models for BehaviorGraph API.""" + +from __future__ import annotations + +from typing import Literal + +from pydantic import BaseModel, Field + + +class DemoSummary(BaseModel): + product: str + dataset: str + users: int = Field(ge=0) + events: int = Field(ge=0) + sessions: int = Field(ge=0) + activated_users: int = Field(ge=0) + activation_rate: float = Field(ge=0, le=1) + notice: str + + +class TaxonomyEvent(BaseModel): + event_name: str + category: str + description: str + owner: str + + +class TaxonomyResponse(BaseModel): + events: list[TaxonomyEvent] + + +class FunnelStep(BaseModel): + step: str + users: int = Field(ge=0) + conversion_from_previous: float = Field(ge=0, le=1) + conversion_from_start: float = Field(ge=0, le=1) + + +class FunnelResponse(BaseModel): + funnel: str + method: str = "nested_unique_users" + steps: list[FunnelStep] + + +class CohortWeek(BaseModel): + week_offset: int = Field(ge=0) + week: str + retained_users: int = Field(ge=0) + retention_rate: float = Field(ge=0, le=1) + + +class Cohort(BaseModel): + cohort_week: str + cohort_size: int = Field(ge=0) + weeks: list[CohortWeek] + + +class CohortsResponse(BaseModel): + cohorts: list[Cohort] + method: str = "first_seen_week" + + +class JourneyNode(BaseModel): + id: str + label: str + + +class JourneyEdge(BaseModel): + source: str + target: str + weight: int = Field(ge=0) + + +class JourneyGraph(BaseModel): + nodes: list[JourneyNode] + edges: list[JourneyEdge] + engine: str = "networkx" + + +class Segment(BaseModel): + id: str + name: str + users: int = Field(ge=0) + definition: str + + +class SegmentsResponse(BaseModel): + segments: list[Segment] + + +class FunnelDrop(BaseModel): + from_step: str + to_step: str + drop_users: int + drop_rate: float = Field(ge=0, le=1) + severity: Literal["low", "medium", "high"] + + +class ErrorSignal(BaseModel): + event_name: str + affected_users: int = Field(ge=0) + + +class FrictionResponse(BaseModel): + funnel_drops: list[FunnelDrop] + error_signals: list[ErrorSignal] + + +class Opportunity(BaseModel): + title: str + why: str + suggested_action: str + impact_hypothesis: str + + +class OpportunityMemo(BaseModel): + headline: str + summary: DemoSummary + opportunities: list[Opportunity] + limitations: list[str] + + +class HealthResponse(BaseModel): + status: str + service: str diff --git a/apps/api/app/services/analytics.py b/apps/api/app/services/analytics.py index 6c2d41a..21d6894 100644 --- a/apps/api/app/services/analytics.py +++ b/apps/api/app/services/analytics.py @@ -1,6 +1,7 @@ from __future__ import annotations from collections import Counter +from functools import lru_cache from pathlib import Path import networkx as nx @@ -19,14 +20,24 @@ ] +@lru_cache(maxsize=1) def _events() -> pd.DataFrame: + """Load and normalize the synthetic event seed (cached per process).""" if not SEED_EVENTS.exists(): return pd.DataFrame( columns=["event_id", "user_id", "event_name", "ts", "session_id", "properties"] ) df = pd.read_csv(SEED_EVENTS) - df["ts"] = pd.to_datetime(df["ts"], utc=True) - return df.sort_values("ts") + df["user_id"] = df["user_id"].astype(str) + df["event_name"] = df["event_name"].astype(str) + df["session_id"] = df["session_id"].astype(str) + # Normalize to UTC-aware then drop tz for stable weekly Period math + df["ts"] = pd.to_datetime(df["ts"], utc=True).dt.tz_convert(None) + return df.sort_values(["ts", "event_id"]).reset_index(drop=True) + + +def clear_event_cache() -> None: + _events.cache_clear() def load_demo_summary() -> dict: @@ -48,7 +59,10 @@ def load_demo_summary() -> dict: "sessions": sessions, "activated_users": activated, "activation_rate": activation_rate, - "notice": "Demo uses synthetic events only — not production tracking.", + "notice": ( + "Demo uses synthetic events only — not production tracking, " + "not Mixpanel, and not causal attribution." + ), } @@ -70,88 +84,115 @@ def load_event_taxonomy() -> dict: def load_recent_events(limit: int = 50) -> list[dict]: + limit = max(1, min(int(limit), 500)) df = _events().tail(limit) records = df.to_dict(orient="records") for row in records: - row["ts"] = row["ts"].isoformat() + row["ts"] = pd.Timestamp(row["ts"]).isoformat() + "Z" return records def build_activation_funnel() -> dict: + """Nested unique-user funnel (users must remain in prior step set).""" df = _events() - steps = [] + steps: list[dict] = [] prev_users: set[str] | None = None + start_users: set[str] | None = None + for name in ACTIVATION_STEPS: - users = set(df.loc[df["event_name"] == name, "user_id"].astype(str)) - count = len(users) - conversion_from_prev = ( - round(count / len(prev_users), 3) if prev_users else 1.0 + fired = set(df.loc[df["event_name"] == name, "user_id"].astype(str)) + if prev_users is None: + users = fired + start_users = fired + conversion_from_prev = 1.0 + else: + users = fired & prev_users + conversion_from_prev = ( + round(len(users) / len(prev_users), 3) if prev_users else 0.0 + ) + + conversion_from_start = ( + round(len(users) / len(start_users), 3) if start_users else 0.0 ) steps.append( { "step": name, - "users": count, + "users": len(users), "conversion_from_previous": conversion_from_prev, + "conversion_from_start": conversion_from_start, } ) prev_users = users - return {"funnel": "activation", "steps": steps} + + return { + "funnel": "activation", + "method": "nested_unique_users", + "steps": steps, + } def build_retention_cohorts() -> dict: + """First-seen ISO week cohorts with true week_offset retention.""" df = _events() if df.empty: - return {"cohorts": []} + return {"cohorts": [], "method": "first_seen_week"} - first = df.groupby("user_id")["ts"].min().rename("cohort_week") - first = first.dt.to_period("W").astype(str) - activity = df.assign(activity_week=df["ts"].dt.to_period("W").astype(str)) - activity = activity.merge(first, on="user_id") + first = df.groupby("user_id")["ts"].min().rename("first_ts") + first_week = first.dt.to_period("W-MON") + activity = df.merge(first_week.rename("cohort_week"), on="user_id") + activity = activity.assign(activity_week=activity["ts"].dt.to_period("W-MON")) cohorts: list[dict] = [] for cohort_week, group in activity.groupby("cohort_week"): - size = group["user_id"].nunique() - weeks = [] - for offset, week in enumerate(sorted(group["activity_week"].unique())): - retained = group.loc[group["activity_week"] == week, "user_id"].nunique() + size = int(group["user_id"].nunique()) + weeks: list[dict] = [] + for offset in range(0, 5): + target = cohort_week + offset + retained = int( + group.loc[group["activity_week"] == target, "user_id"].nunique() + ) weeks.append( { "week_offset": offset, - "week": week, - "retained_users": int(retained), + "week": str(target), + "retained_users": retained, "retention_rate": round(retained / size, 3) if size else 0.0, } ) cohorts.append( { - "cohort_week": cohort_week, - "cohort_size": int(size), - "weeks": weeks[:5], + "cohort_week": str(cohort_week), + "cohort_size": size, + "weeks": weeks, } ) - return {"cohorts": cohorts[:6]} + + cohorts.sort(key=lambda c: c["cohort_week"]) + return {"cohorts": cohorts[:6], "method": "first_seen_week"} def build_journey_graph(limit_edges: int = 40) -> dict: + """Session-ordered transition graph (exploratory, not attribution).""" df = _events() if df.empty: - return {"nodes": [], "edges": []} + return {"nodes": [], "edges": [], "engine": "networkx"} + limit_edges = max(1, min(int(limit_edges), 200)) transitions: Counter[tuple[str, str]] = Counter() - for _, session in df.groupby("session_id"): + for _, session in df.groupby("session_id", sort=False): names = session.sort_values("ts")["event_name"].tolist() - for a, b in zip(names, names[1:]): + for a, b in zip(names, names[1:], strict=False): if a != b: transitions[(a, b)] += 1 - G = nx.DiGraph() + graph = nx.DiGraph() for (src, dst), weight in transitions.most_common(limit_edges): - G.add_edge(src, dst, weight=weight) + graph.add_edge(src, dst, weight=weight) - nodes = [{"id": n, "label": n} for n in G.nodes] + nodes = [{"id": n, "label": n} for n in graph.nodes] edges = [ - {"source": u, "target": v, "weight": int(d["weight"])} - for u, v, d in G.edges(data=True) + {"source": u, "target": v, "weight": int(data["weight"])} + for u, v, data in graph.edges(data=True) ] return {"nodes": nodes, "edges": edges, "engine": "networkx"} @@ -163,10 +204,9 @@ def build_segments() -> dict: activated = set(df.loc[df["event_name"] == "activation_completed", "user_id"]) churn_signal = set(df.loc[df["event_name"] == "session_abandoned", "user_id"]) - power = ( + power_users = set( df.groupby("user_id").size().sort_values(ascending=False).head(20).index ) - power_users = set(power) segments = [ { @@ -199,13 +239,16 @@ def build_friction_points() -> dict: prev, cur = funnel[i - 1], funnel[i] drop = prev["users"] - cur["users"] drop_rate = round(drop / prev["users"], 3) if prev["users"] else 0.0 + severity = ( + "high" if drop_rate >= 0.35 else "medium" if drop_rate >= 0.2 else "low" + ) drops.append( { "from_step": prev["step"], "to_step": cur["step"], "drop_users": drop, "drop_rate": drop_rate, - "severity": "high" if drop_rate >= 0.35 else "medium" if drop_rate >= 0.2 else "low", + "severity": severity, } ) @@ -234,16 +277,22 @@ def build_opportunity_memo() -> dict: opportunities.append( { "title": f"Reduce drop {top_drop['from_step']} → {top_drop['to_step']}", - "why": f"Drop rate {top_drop['drop_rate']:.0%} on the activation path.", - "suggested_action": "Simplify the step UX, add progressive disclosure, instrument micro-errors.", - "impact_hypothesis": "Improving this transition should lift activation_rate without new acquisition.", + "why": f"Drop rate {top_drop['drop_rate']:.0%} on the nested activation path.", + "suggested_action": ( + "Simplify the step UX, add progressive disclosure, instrument micro-errors." + ), + "impact_hypothesis": ( + "Improving this transition should lift activation_rate without new acquisition." + ), } ) opportunities.append( { "title": "Close taxonomy gaps before production tracking", "why": "Orphan or inconsistently named events hide journey truth.", - "suggested_action": "Enforce event taxonomy ownership and reject unknown events in ingest.", + "suggested_action": ( + "Enforce event taxonomy ownership and reject unknown events in ingest." + ), "impact_hypothesis": "Cleaner schema improves funnel and cohort reliability.", } ) @@ -251,7 +300,9 @@ def build_opportunity_memo() -> dict: { "title": "Protect activated cohort with early habit loops", "why": f"Activation rate is {summary['activation_rate']:.0%} in the demo window.", - "suggested_action": "Trigger day-1 / day-7 nudges only for activated users with low feature_used density.", + "suggested_action": ( + "Trigger day-1 / day-7 nudges only for activated users with low feature_used density." + ), "impact_hypothesis": "Retention lift comes from habit, not more signup volume.", } ) @@ -263,5 +314,6 @@ def build_opportunity_memo() -> dict: "Synthetic dataset — not causal proof.", "No production SDK ingest in MVP.", "Path graph is session-local transition counts, not Markov attribution.", + "Nested funnel counts unique users remaining in the prior step set.", ], } diff --git a/apps/api/requirements.txt b/apps/api/requirements.txt index 956eb64..510efd6 100644 --- a/apps/api/requirements.txt +++ b/apps/api/requirements.txt @@ -4,7 +4,6 @@ pydantic>=2.10.0 pandas>=2.2.0 numpy>=2.1.0 networkx>=3.4.0 -duckdb>=1.1.0 python-multipart>=0.0.12 httpx>=0.28.0 pytest>=8.0.0 diff --git a/apps/api/ruff.toml b/apps/api/ruff.toml new file mode 100644 index 0000000..205c61f --- /dev/null +++ b/apps/api/ruff.toml @@ -0,0 +1,6 @@ +target-version = "py312" +line-length = 100 + +[lint] +select = ["E", "F", "I", "B", "UP"] +ignore = ["E501"] diff --git a/apps/api/tests/test_api.py b/apps/api/tests/test_api.py index 352e2d6..ef37e07 100644 --- a/apps/api/tests/test_api.py +++ b/apps/api/tests/test_api.py @@ -1,14 +1,62 @@ -from app.services.analytics import build_activation_funnel, load_demo_summary +from __future__ import annotations + +from fastapi.testclient import TestClient + +from app.main import app +from app.services.analytics import ( + build_activation_funnel, + build_journey_graph, + build_retention_cohorts, + load_demo_summary, +) + +client = TestClient(app) def test_demo_summary_shape(): summary = load_demo_summary() assert summary["product"] == "BehaviorGraph" - assert "users" in summary - assert "activation_rate" in summary + assert summary["users"] > 0 + assert 0 <= summary["activation_rate"] <= 1 -def test_activation_funnel_has_steps(): +def test_activation_funnel_is_nested_and_monotonic(): funnel = build_activation_funnel() - assert funnel["funnel"] == "activation" - assert len(funnel["steps"]) >= 3 + assert funnel["method"] == "nested_unique_users" + steps = funnel["steps"] + assert len(steps) == 5 + counts = [s["users"] for s in steps] + assert counts == sorted(counts, reverse=True) + assert all(0 <= s["conversion_from_previous"] <= 1 for s in steps) + assert all(0 <= s["conversion_from_start"] <= 1 for s in steps) + + +def test_retention_cohorts_week_offsets(): + payload = build_retention_cohorts() + assert payload["method"] == "first_seen_week" + assert payload["cohorts"] + for cohort in payload["cohorts"]: + offsets = [w["week_offset"] for w in cohort["weeks"]] + assert offsets == list(range(len(offsets))) + assert cohort["weeks"][0]["retention_rate"] == 1.0 + + +def test_journey_graph_has_weighted_edges(): + graph = build_journey_graph(limit_edges=20) + assert graph["engine"] == "networkx" + assert graph["edges"] + assert all(e["weight"] >= 1 for e in graph["edges"]) + + +def test_health_endpoint(): + response = client.get("/health") + assert response.status_code == 200 + assert response.json()["status"] == "ok" + + +def test_funnel_endpoint_schema(): + response = client.get("/api/funnel/activation") + assert response.status_code == 200 + body = response.json() + assert body["method"] == "nested_unique_users" + assert len(body["steps"]) == 5 diff --git a/apps/web/.env.example b/apps/web/.env.example index def4805..792e9ad 100644 --- a/apps/web/.env.example +++ b/apps/web/.env.example @@ -1,2 +1,3 @@ # Frontend env template -NEXT_PUBLIC_API_BASE=http://127.0.0.1:8000 +# Leave empty for static lab snapshot mode (recommended for Vercel / GitHub Pages). +NEXT_PUBLIC_API_URL= diff --git a/apps/web/app/globals.css b/apps/web/app/globals.css index 257299d..a1f6e9b 100644 --- a/apps/web/app/globals.css +++ b/apps/web/app/globals.css @@ -9,6 +9,7 @@ --danger: #fb7185; --line: #243047; --ok: #4ade80; + --warn: #fbbf24; --font: "Segoe UI", "IBM Plex Sans", system-ui, sans-serif; } @@ -16,6 +17,10 @@ box-sizing: border-box; } +html { + scroll-behavior: smooth; +} + html, body { margin: 0; @@ -29,6 +34,25 @@ body { font-family: var(--font); } +a { + color: var(--accent-2); +} + +.skip-link { + position: absolute; + left: -999px; + top: 0; + background: var(--accent); + color: #041018; + padding: 8px 12px; + z-index: 20; +} + +.skip-link:focus { + left: 12px; + top: 12px; +} + main { max-width: 1180px; margin: 0 auto; @@ -36,7 +60,7 @@ main { } .hero { - margin-bottom: 28px; + margin-bottom: 20px; } .brand { @@ -46,12 +70,22 @@ main { } .lede { - max-width: 720px; + max-width: 760px; color: var(--muted); font-size: 1.05rem; line-height: 1.55; } +.notice { + max-width: 760px; + margin: 14px 0 0; + color: var(--muted); + font-size: 0.95rem; + line-height: 1.5; + border-left: 3px solid var(--accent); + padding-left: 12px; +} + .muted { color: var(--muted); text-transform: uppercase; @@ -59,6 +93,45 @@ main { font-size: 0.75rem; } +.badge-row { + display: flex; + flex-wrap: wrap; + gap: 8px; + margin-top: 14px; +} + +.badge { + border: 1px solid var(--line); + background: rgba(94, 234, 212, 0.08); + color: var(--accent); + border-radius: 999px; + padding: 6px 12px; + font-size: 0.8rem; +} + +.toc { + display: flex; + flex-wrap: wrap; + gap: 8px; + margin: 8px 0 22px; +} + +.toc a { + text-decoration: none; + color: var(--muted); + border: 1px solid var(--line); + border-radius: 999px; + padding: 6px 12px; + font-size: 0.85rem; +} + +.toc a:hover, +.toc a:focus-visible { + color: var(--text); + border-color: var(--accent); + outline: none; +} + .grid { display: grid; gap: 16px; @@ -96,6 +169,10 @@ main { .span-12 { grid-column: span 12; } + + .bar-row { + grid-template-columns: 1fr; + } } .kpi { @@ -103,6 +180,21 @@ main { font-weight: 700; } +.kpi-card .hint, +.hint { + margin: 8px 0 0; + color: var(--muted); + font-size: 0.85rem; + line-height: 1.4; +} + +.section-copy { + margin: 0 0 14px; + color: var(--muted); + line-height: 1.5; + font-size: 0.95rem; +} + .list { margin: 0; padding-left: 18px; @@ -110,25 +202,13 @@ main { line-height: 1.55; } -.bar-row { - display: grid; - grid-template-columns: 180px 1fr 64px; - gap: 10px; - align-items: center; - margin: 10px 0; -} - -.bar-track { - height: 10px; - background: #0d1524; - border-radius: 999px; - overflow: hidden; - border: 1px solid var(--line); +.list.compact { + margin-top: 12px; } -.bar-fill { - height: 100%; - background: linear-gradient(90deg, var(--accent), var(--accent-2)); +.empty { + color: var(--muted); + margin: 0; } .error { @@ -141,10 +221,15 @@ main { } h2 { - margin: 0 0 12px; + margin: 0 0 8px; font-size: 1.15rem; } +.subhead { + margin: 16px 0 8px; + font-size: 0.95rem; +} + .tag { display: inline-block; padding: 4px 10px; @@ -154,3 +239,121 @@ h2 { font-size: 0.75rem; margin-right: 8px; } + +.chart-wrap { + width: 100%; + min-height: 260px; +} + +.table-wrap { + overflow-x: auto; +} + +.matrix { + width: 100%; + border-collapse: collapse; + font-size: 0.85rem; +} + +.matrix th, +.matrix td { + padding: 8px; + border-bottom: 1px solid var(--line); + text-align: center; +} + +.matrix th[scope="row"], +.matrix thead th:first-child, +.matrix thead th:nth-child(2) { + text-align: left; +} + +.heat { + display: inline-block; + min-width: 48px; + padding: 6px 8px; + border-radius: 8px; + color: var(--text); +} + +.callout { + border: 1px solid var(--line); + background: rgba(56, 189, 248, 0.08); + border-radius: 12px; + padding: 10px 12px; + color: var(--muted); + line-height: 1.45; +} + +.sev { + text-transform: uppercase; + font-size: 0.72rem; + letter-spacing: 0.06em; +} + +.sev-high { + color: var(--danger); +} +.sev-medium { + color: var(--warn); +} +.sev-low { + color: var(--ok); +} + +.memo-grid { + display: grid; + gap: 12px; + grid-template-columns: repeat(auto-fit, minmax(240px, 1fr)); + margin-bottom: 8px; +} + +.memo-card { + border: 1px solid var(--line); + border-radius: 14px; + padding: 14px; + background: rgba(13, 21, 36, 0.65); +} + +.memo-card h3 { + margin: 0 0 8px; + font-size: 1rem; +} + +.memo-card p { + margin: 0 0 8px; + color: var(--muted); + line-height: 1.45; + font-size: 0.92rem; +} + +.skeleton.block { + min-height: 96px; + background: linear-gradient( + 90deg, + rgba(36, 48, 73, 0.4), + rgba(94, 234, 212, 0.12), + rgba(36, 48, 73, 0.4) + ); + background-size: 200% 100%; + animation: shimmer 1.4s infinite; +} + +.skeleton.tall { + min-height: 220px; +} + +@keyframes shimmer { + 0% { + background-position: 200% 0; + } + 100% { + background-position: -200% 0; + } +} + +.footer { + margin-top: 28px; + color: var(--muted); + font-size: 0.9rem; +} diff --git a/apps/web/app/layout.tsx b/apps/web/app/layout.tsx index cc23b3e..082460d 100644 --- a/apps/web/app/layout.tsx +++ b/apps/web/app/layout.tsx @@ -4,14 +4,14 @@ import "./globals.css"; export const metadata: Metadata = { title: "BehaviorGraph — Behavioral Analytics Studio", description: - "Turn product events into journeys, activation funnels, retention cohorts, friction signals and opportunity memos.", + "Portfolio lab: event taxonomy, nested activation funnel, retention cohorts, journey graph and product opportunity memos on synthetic SaaS events.", }; export default function RootLayout({ children, }: Readonly<{ children: React.ReactNode }>) { return ( - + {children} ); diff --git a/apps/web/app/page.tsx b/apps/web/app/page.tsx index ee467a7..d9b99ed 100644 --- a/apps/web/app/page.tsx +++ b/apps/web/app/page.tsx @@ -1,6 +1,10 @@ "use client"; import { useEffect, useState, useTransition } from "react"; +import { CohortMatrix } from "@/components/CohortMatrix"; +import { FunnelChart } from "@/components/FunnelChart"; +import { KpiCard } from "@/components/KpiCard"; +import { SkeletonGrid } from "@/components/SkeletonGrid"; import { fetchCohorts, fetchDemo, @@ -11,15 +15,27 @@ import { fetchSegments, fetchTaxonomy, } from "@/lib/api"; -import type { Cohort, FrictionPayload, TaxonomyEvent } from "@/lib/lab"; import type { + Cohort, DemoSummary, + FrictionPayload, FunnelStep, JourneyGraph, OpportunityMemo, Segment, + TaxonomyEvent, } from "@/types"; +const NAV = [ + { id: "overview", label: "Overview" }, + { id: "taxonomy", label: "Taxonomy" }, + { id: "funnel", label: "Funnel" }, + { id: "cohorts", label: "Cohorts" }, + { id: "journey", label: "Journey" }, + { id: "friction", label: "Friction" }, + { id: "memo", label: "Memo" }, +] as const; + export default function HomePage() { const [demo, setDemo] = useState(null); const [funnel, setFunnel] = useState([]); @@ -61,122 +77,164 @@ export default function HomePage() { }); }, []); - const maxFunnel = Math.max(...funnel.map((step) => step.users), 1); + const topDrop = friction?.funnel_drops.reduce( + (best, d) => (!best || d.drop_rate > best.drop_rate ? d : best), + null as (typeof friction.funnel_drops)[number] | null, + ); return (
-
+ + Skip to content + + +

Portfolio lab · synthetic events · responsible analytics

BehaviorGraph

- MVP lab that turns product events into taxonomy, activation funnel, - retention cohorts, journey graph and an opportunity memo — answering - which paths lead to activation, abandonment or recurring use. + Turns product events into taxonomy, nested activation funnel, retention + cohorts, journey graph and an opportunity memo — answering which paths + lead to activation, abandonment or recurring use.

-

- {demo?.notice} -

-
+
+ + Synthetic seed + + + Nested unique-user funnel + + + No causal overclaim + +
+

{demo?.notice}

+ - {error ?
{error}
: null} - {pending && !demo ?

Loading lab snapshot…

: null} + -
-
-

Users

-
{demo?.users ?? "—"}
-
-
-

Events

-
{demo?.events ?? "—"}
-
-
-

Sessions

-
{demo?.sessions ?? "—"}
-
-
-

Activation rate

-
- {demo ? `${Math.round(demo.activation_rate * 100)}%` : "—"} -
-
+ {error ? ( +
+ {error} +
+ ) : null} + + {pending && !demo ? : null} -
+ {demo ? ( +
+ + + + +
+ ) : null} + +
+

Event taxonomy

-
    - {taxonomy.slice(0, 8).map((ev) => ( -
  • - {ev.event_name}{" "} - {ev.category} -
    - {ev.description} · owner: {ev.owner} -
    • - ))} -
+

+ Owned event contract — category, description and owner before volume. +

+ {taxonomy.length ? ( +
    + {taxonomy.map((ev) => ( +
  • + {ev.event_name}{" "} + {ev.category} +
    + {ev.description} · owner: {ev.owner} +
    • + ))} +
+ ) : ( +

Taxonomy not loaded.

+ )}
-
+

Activation funnel

- {funnel.map((step) => ( -
- {step.step} -
-
-
- {step.users} -
- ))} +

+ Nested unique users (must remain in the previous step set). Method is + explicit — not raw event counts. +

+ +
    + {funnel.map((step) => ( +
  • + {step.step} — {step.users} users ·{" "} + {Math.round(step.conversion_from_previous * 100)}% from previous + {typeof step.conversion_from_start === "number" + ? ` · ${Math.round(step.conversion_from_start * 100)}% from start` + : ""} +
    • + ))} +
-
+

Retention cohorts

-
    - {cohorts.slice(0, 5).map((c) => { - const w1 = c.weeks.find((w) => w.week_offset === 1); - return ( -
  • - {c.cohort_week} — size {c.cohort_size} - {w1 - ? ` · W1 retention ${Math.round(w1.retention_rate * 100)}%` - : ""} -
    • - ); - })} -
+

+ First-seen week cohorts with true week offsets (W0–W4). +

+
-
+

Segments

+

+ Lightweight behavioral slices for product conversation — not ML scoring. +

    {segments.map((s) => (
  • - {s.name} — {s.users} users · {s.definition} + {s.name} — {s.users} users +
    + {s.definition}
    • ))}
-
+

Journey path graph

-

- Top session transitions · {journey?.edges.length ?? 0} edges · engine{" "} - {journey?.engine ?? "snapshot"} +

+ Top session transitions via NetworkX. Exploratory map — not Markov + attribution or causal path proof. +

+

+ {journey?.edges.length ?? 0} edges · engine {journey?.engine ?? "snapshot"}

    {(journey?.edges ?? []).slice(0, 12).map((e) => (
  • - {e.source} → {e.target}{" "} - w={e.weight} + {e.source} → {e.target} w={e.weight}
    • ))}
-
+

Friction radar

+

+ Drop severity on the nested funnel plus error-like signals. +

+ {topDrop ? ( +

+ Largest drop: {topDrop.from_step} →{" "} + {topDrop.to_step} ( + {Math.round(topDrop.drop_rate * 100)}%, {topDrop.severity}) +

+ ) : null}
    {(friction?.funnel_drops ?? []).map((d) => (
  • @@ -184,26 +242,43 @@ export default function HomePage() { {d.from_step} → {d.to_step}
    - drop {Math.round(d.drop_rate * 100)}% · severity {d.severity} + drop {Math.round(d.drop_rate * 100)}% ·{" "} + {d.severity}
    • ))}
+ {(friction?.error_signals?.length ?? 0) > 0 ? ( + <> +

Error-like signals

+
    + {friction!.error_signals.map((s) => ( +
  • + {s.event_name}: {s.affected_users} users +
    • + ))} +
+ + ) : null}
-
+

Product opportunity memo

-
    +

    + Hypotheses tied to observed drops — with explicit analytical limits. +

    +
    {(memo?.opportunities ?? []).map((o) => ( -
  • - {o.title} -
    - {o.why} -
    - Action: {o.suggested_action} -
    • +
    +

    {o.title}

    +

    {o.why}

    +

    + Action: {o.suggested_action} +

    +

    {o.impact_hypothesis}

    +
    ))} -
-

Limitations

+ +

Limitations

    {(memo?.limitations ?? []).map((l) => (
  • {l}
    • @@ -211,6 +286,13 @@ export default function HomePage() {
+ +
+

+ BehaviorGraph · portfolio lab by Felipe Alirio Baruja ·{" "} + GitHub +

+
); } diff --git a/apps/web/components/CohortMatrix.tsx b/apps/web/components/CohortMatrix.tsx new file mode 100644 index 0000000..fc3d1b0 --- /dev/null +++ b/apps/web/components/CohortMatrix.tsx @@ -0,0 +1,54 @@ +"use client"; + +import type { Cohort } from "@/types"; + +export function CohortMatrix({ cohorts }: { cohorts: Cohort[] }) { + if (!cohorts.length) { + return

No cohorts in the demo window.

; + } + + const offsets = cohorts[0]?.weeks.map((w) => w.week_offset) ?? []; + + return ( +
+ + + + + + {offsets.map((o) => ( + + ))} + + + + {cohorts.slice(0, 6).map((c) => ( + + + + {c.weeks.map((w) => { + const pct = Math.round(w.retention_rate * 100); + const intensity = Math.min(100, pct); + return ( + + ); + })} + + ))} + +
CohortSize + W{o} +
{c.cohort_week}{c.cohort_size} + + {pct}% + +
+
+ ); +} diff --git a/apps/web/components/FunnelChart.tsx b/apps/web/components/FunnelChart.tsx new file mode 100644 index 0000000..3622afd --- /dev/null +++ b/apps/web/components/FunnelChart.tsx @@ -0,0 +1,61 @@ +"use client"; + +import { + Bar, + BarChart, + CartesianGrid, + ResponsiveContainer, + Tooltip, + XAxis, + YAxis, +} from "recharts"; +import type { FunnelStep } from "@/types"; + +function shortLabel(step: string) { + return step.replaceAll("_", " "); +} + +export function FunnelChart({ steps }: { steps: FunnelStep[] }) { + const data = steps.map((s) => ({ + name: shortLabel(s.step), + users: s.users, + conv: Math.round(s.conversion_from_previous * 100), + })); + + if (!data.length) { + return

No funnel steps available.

; + } + + return ( +
+ + + + + + + name === "users" + ? [value as number, "Users"] + : [`${value}%`, "Conv. from previous"] + } + /> + + + +
+ ); +} diff --git a/apps/web/components/KpiCard.tsx b/apps/web/components/KpiCard.tsx new file mode 100644 index 0000000..ed92c71 --- /dev/null +++ b/apps/web/components/KpiCard.tsx @@ -0,0 +1,17 @@ +type Props = { + label: string; + value: string | number; + hint?: string; +}; + +export function KpiCard({ label, value, hint }: Props) { + return ( +
+

{label}

+
+ {value} +
+ {hint ?

{hint}

: null} +
+ ); +} diff --git a/apps/web/components/SkeletonGrid.tsx b/apps/web/components/SkeletonGrid.tsx new file mode 100644 index 0000000..2de9963 --- /dev/null +++ b/apps/web/components/SkeletonGrid.tsx @@ -0,0 +1,12 @@ +export function SkeletonGrid() { + return ( +
+ {Array.from({ length: 4 }).map((_, i) => ( +
+ ))} + {Array.from({ length: 2 }).map((_, i) => ( +
+ ))} +
+ ); +} diff --git a/apps/web/eslint.config.mjs b/apps/web/eslint.config.mjs new file mode 100644 index 0000000..348c45a --- /dev/null +++ b/apps/web/eslint.config.mjs @@ -0,0 +1,14 @@ +import { dirname } from "path"; +import { fileURLToPath } from "url"; +import { FlatCompat } from "@eslint/eslintrc"; + +const __filename = fileURLToPath(import.meta.url); +const __dirname = dirname(__filename); + +const compat = new FlatCompat({ + baseDirectory: __dirname, +}); + +const eslintConfig = [...compat.extends("next/core-web-vitals")]; + +export default eslintConfig; diff --git a/apps/web/lib/api.ts b/apps/web/lib/api.ts index 8a68ca9..b64c083 100644 --- a/apps/web/lib/api.ts +++ b/apps/web/lib/api.ts @@ -7,23 +7,23 @@ import { getOpportunities, getSegments, getTaxonomy, - type Cohort, - type FrictionPayload, - type TaxonomyEvent, } from "@/lib/lab"; import type { + Cohort, DemoSummary, + FrictionPayload, FunnelStep, JourneyGraph, OpportunityMemo, Segment, + TaxonomyEvent, } from "@/types"; -const API_URL = process.env.NEXT_PUBLIC_API_URL; +const API_URL = process.env.NEXT_PUBLIC_API_URL?.replace(/\/$/, ""); /** * Prefer optional FastAPI when NEXT_PUBLIC_API_URL is set. - * Vercel lab demo falls back to the embedded synthetic snapshot. + * Static/Vercel lab demo falls back to the embedded synthetic snapshot. */ async function tryBackend(path: string): Promise { if (!API_URL) return null; diff --git a/apps/web/lib/demo-snapshot.json b/apps/web/lib/demo-snapshot.json index b6aa378..e34d840 100644 --- a/apps/web/lib/demo-snapshot.json +++ b/apps/web/lib/demo-snapshot.json @@ -7,7 +7,7 @@ "sessions": 289, "activated_users": 55, "activation_rate": 0.25, - "notice": "Demo uses synthetic events only — not production tracking." + "notice": "Demo uses synthetic events only — not production tracking, not Mixpanel, and not causal attribution." }, "taxonomy": { "events": [ @@ -75,181 +75,224 @@ }, "funnel": { "funnel": "activation", + "method": "nested_unique_users", "steps": [ { "step": "signup_started", "users": 220, - "conversion_from_previous": 1.0 + "conversion_from_previous": 1.0, + "conversion_from_start": 1.0 }, { "step": "signup_completed", "users": 186, - "conversion_from_previous": 0.845 + "conversion_from_previous": 0.845, + "conversion_from_start": 0.845 }, { "step": "onboarding_step_viewed", "users": 147, - "conversion_from_previous": 0.79 + "conversion_from_previous": 0.79, + "conversion_from_start": 0.668 }, { "step": "feature_used", "users": 102, - "conversion_from_previous": 0.694 + "conversion_from_previous": 0.694, + "conversion_from_start": 0.464 }, { "step": "activation_completed", "users": 55, - "conversion_from_previous": 0.539 + "conversion_from_previous": 0.539, + "conversion_from_start": 0.25 } ] }, "cohorts": { "cohorts": [ { - "cohort_week": "2026-04-27/2026-05-03", - "cohort_size": 16, + "cohort_week": "2026-04-28/2026-05-04", + "cohort_size": 25, "weeks": [ { "week_offset": 0, - "week": "2026-04-27/2026-05-03", - "retained_users": 16, + "week": "2026-04-28/2026-05-04", + "retained_users": 25, "retention_rate": 1.0 }, { "week_offset": 1, - "week": "2026-05-04/2026-05-10", - "retained_users": 5, - "retention_rate": 0.312 + "week": "2026-05-05/2026-05-11", + "retained_users": 7, + "retention_rate": 0.28 }, { "week_offset": 2, - "week": "2026-05-18/2026-05-24", + "week": "2026-05-12/2026-05-18", + "retained_users": 1, + "retention_rate": 0.04 + }, + { + "week_offset": 3, + "week": "2026-05-19/2026-05-25", "retained_users": 1, - "retention_rate": 0.062 + "retention_rate": 0.04 + }, + { + "week_offset": 4, + "week": "2026-05-26/2026-06-01", + "retained_users": 0, + "retention_rate": 0.0 } ] }, { - "cohort_week": "2026-05-04/2026-05-10", - "cohort_size": 57, + "cohort_week": "2026-05-05/2026-05-11", + "cohort_size": 52, "weeks": [ { "week_offset": 0, - "week": "2026-05-04/2026-05-10", - "retained_users": 57, + "week": "2026-05-05/2026-05-11", + "retained_users": 52, "retention_rate": 1.0 }, { "week_offset": 1, - "week": "2026-05-11/2026-05-17", - "retained_users": 12, - "retention_rate": 0.211 + "week": "2026-05-12/2026-05-18", + "retained_users": 13, + "retention_rate": 0.25 }, { "week_offset": 2, - "week": "2026-05-18/2026-05-24", - "retained_users": 2, - "retention_rate": 0.035 + "week": "2026-05-19/2026-05-25", + "retained_users": 1, + "retention_rate": 0.019 }, { "week_offset": 3, - "week": "2026-05-25/2026-05-31", + "week": "2026-05-26/2026-06-01", "retained_users": 3, - "retention_rate": 0.053 + "retention_rate": 0.058 + }, + { + "week_offset": 4, + "week": "2026-06-02/2026-06-08", + "retained_users": 0, + "retention_rate": 0.0 } ] }, { - "cohort_week": "2026-05-11/2026-05-17", - "cohort_size": 48, + "cohort_week": "2026-05-12/2026-05-18", + "cohort_size": 54, "weeks": [ { "week_offset": 0, - "week": "2026-05-11/2026-05-17", - "retained_users": 48, + "week": "2026-05-12/2026-05-18", + "retained_users": 54, "retention_rate": 1.0 }, { "week_offset": 1, - "week": "2026-05-18/2026-05-24", - "retained_users": 3, - "retention_rate": 0.062 + "week": "2026-05-19/2026-05-25", + "retained_users": 5, + "retention_rate": 0.093 }, { "week_offset": 2, - "week": "2026-05-25/2026-05-31", - "retained_users": 4, - "retention_rate": 0.083 + "week": "2026-05-26/2026-06-01", + "retained_users": 5, + "retention_rate": 0.093 }, { "week_offset": 3, - "week": "2026-06-01/2026-06-07", - "retained_users": 2, - "retention_rate": 0.042 + "week": "2026-06-02/2026-06-08", + "retained_users": 3, + "retention_rate": 0.056 + }, + { + "week_offset": 4, + "week": "2026-06-09/2026-06-15", + "retained_users": 0, + "retention_rate": 0.0 } ] }, { - "cohort_week": "2026-05-18/2026-05-24", - "cohort_size": 56, + "cohort_week": "2026-05-19/2026-05-25", + "cohort_size": 55, "weeks": [ { "week_offset": 0, - "week": "2026-05-18/2026-05-24", - "retained_users": 56, + "week": "2026-05-19/2026-05-25", + "retained_users": 55, "retention_rate": 1.0 }, { "week_offset": 1, - "week": "2026-05-25/2026-05-31", - "retained_users": 11, - "retention_rate": 0.196 + "week": "2026-05-26/2026-06-01", + "retained_users": 10, + "retention_rate": 0.182 }, { "week_offset": 2, - "week": "2026-06-01/2026-06-07", - "retained_users": 3, - "retention_rate": 0.054 + "week": "2026-06-02/2026-06-08", + "retained_users": 2, + "retention_rate": 0.036 }, { "week_offset": 3, - "week": "2026-06-08/2026-06-14", + "week": "2026-06-09/2026-06-15", "retained_users": 4, - "retention_rate": 0.071 + "retention_rate": 0.073 + }, + { + "week_offset": 4, + "week": "2026-06-16/2026-06-22", + "retained_users": 0, + "retention_rate": 0.0 } ] }, { - "cohort_week": "2026-05-25/2026-05-31", - "cohort_size": 43, + "cohort_week": "2026-05-26/2026-06-01", + "cohort_size": 34, "weeks": [ { "week_offset": 0, - "week": "2026-05-25/2026-05-31", - "retained_users": 43, + "week": "2026-05-26/2026-06-01", + "retained_users": 34, "retention_rate": 1.0 }, { "week_offset": 1, - "week": "2026-06-01/2026-06-07", - "retained_users": 4, - "retention_rate": 0.093 + "week": "2026-06-02/2026-06-08", + "retained_users": 3, + "retention_rate": 0.088 }, { "week_offset": 2, - "week": "2026-06-08/2026-06-14", - "retained_users": 2, - "retention_rate": 0.047 + "week": "2026-06-09/2026-06-15", + "retained_users": 1, + "retention_rate": 0.029 }, { "week_offset": 3, - "week": "2026-06-15/2026-06-21", + "week": "2026-06-16/2026-06-22", "retained_users": 2, - "retention_rate": 0.047 + "retention_rate": 0.059 + }, + { + "week_offset": 4, + "week": "2026-06-23/2026-06-29", + "retained_users": 0, + "retention_rate": 0.0 } ] } - ] + ], + "method": "first_seen_week" }, "journey": { "nodes": [ @@ -452,12 +495,12 @@ "sessions": 289, "activated_users": 55, "activation_rate": 0.25, - "notice": "Demo uses synthetic events only — not production tracking." + "notice": "Demo uses synthetic events only — not production tracking, not Mixpanel, and not causal attribution." }, "opportunities": [ { "title": "Reduce drop feature_used → activation_completed", - "why": "Drop rate 46% on the activation path.", + "why": "Drop rate 46% on the nested activation path.", "suggested_action": "Simplify the step UX, add progressive disclosure, instrument micro-errors.", "impact_hypothesis": "Improving this transition should lift activation_rate without new acquisition." }, @@ -477,7 +520,8 @@ "limitations": [ "Synthetic dataset — not causal proof.", "No production SDK ingest in MVP.", - "Path graph is session-local transition counts, not Markov attribution." + "Path graph is session-local transition counts, not Markov attribution.", + "Nested funnel counts unique users remaining in the prior step set." ] }, "recent_events": [ @@ -485,7 +529,7 @@ "event_id": "evt_000528", "user_id": "user_0125", "event_name": "invite_sent", - "ts": "2026-06-03T07:12:00+00:00", + "ts": "2026-06-03T07:12:00Z", "session_id": "s_0125_02", "properties": "{}" }, @@ -493,7 +537,7 @@ "event_id": "evt_000820", "user_id": "user_0186", "event_name": "return_visit", - "ts": "2026-06-04T02:00:00+00:00", + "ts": "2026-06-04T02:00:00Z", "session_id": "s_0186_02", "properties": "{}" }, @@ -501,7 +545,7 @@ "event_id": "evt_000942", "user_id": "user_0213", "event_name": "return_visit", - "ts": "2026-06-04T11:00:00+00:00", + "ts": "2026-06-04T11:00:00Z", "session_id": "s_0213_03", "properties": "{}" }, @@ -509,7 +553,7 @@ "event_id": "evt_000943", "user_id": "user_0213", "event_name": "feature_used", - "ts": "2026-06-04T11:04:00+00:00", + "ts": "2026-06-04T11:04:00Z", "session_id": "s_0213_03", "properties": "{\"feature\":\"insights\"}" }, @@ -517,7 +561,7 @@ "event_id": "evt_000375", "user_id": "user_0085", "event_name": "return_visit", - "ts": "2026-06-05T02:00:00+00:00", + "ts": "2026-06-05T02:00:00Z", "session_id": "s_0085_03", "properties": "{}" }, @@ -525,7 +569,7 @@ "event_id": "evt_000376", "user_id": "user_0085", "event_name": "feature_used", - "ts": "2026-06-05T02:04:00+00:00", + "ts": "2026-06-05T02:04:00Z", "session_id": "s_0085_03", "properties": "{\"feature\":\"insights\"}" }, @@ -533,7 +577,7 @@ "event_id": "evt_000676", "user_id": "user_0153", "event_name": "return_visit", - "ts": "2026-06-07T08:00:00+00:00", + "ts": "2026-06-07T08:00:00Z", "session_id": "s_0153_03", "properties": "{}" }, @@ -541,7 +585,7 @@ "event_id": "evt_000677", "user_id": "user_0153", "event_name": "feature_used", - "ts": "2026-06-07T08:04:00+00:00", + "ts": "2026-06-07T08:04:00Z", "session_id": "s_0153_03", "properties": "{\"feature\":\"insights\"}" }, @@ -549,7 +593,7 @@ "event_id": "evt_000610", "user_id": "user_0141", "event_name": "return_visit", - "ts": "2026-06-08T18:00:00+00:00", + "ts": "2026-06-08T18:00:00Z", "session_id": "s_0141_02", "properties": "{}" }, @@ -557,7 +601,7 @@ "event_id": "evt_000611", "user_id": "user_0141", "event_name": "feature_used", - "ts": "2026-06-08T18:05:00+00:00", + "ts": "2026-06-08T18:05:00Z", "session_id": "s_0141_02", "properties": "{\"feature\":\"board\"}" }, @@ -565,7 +609,7 @@ "event_id": "evt_000612", "user_id": "user_0141", "event_name": "invite_sent", - "ts": "2026-06-08T18:12:00+00:00", + "ts": "2026-06-08T18:12:00Z", "session_id": "s_0141_02", "properties": "{}" }, @@ -573,7 +617,7 @@ "event_id": "evt_000295", "user_id": "user_0069", "event_name": "return_visit", - "ts": "2026-06-09T13:00:00+00:00", + "ts": "2026-06-09T13:00:00Z", "session_id": "s_0069_03", "properties": "{}" }, @@ -581,7 +625,7 @@ "event_id": "evt_000296", "user_id": "user_0069", "event_name": "feature_used", - "ts": "2026-06-09T13:04:00+00:00", + "ts": "2026-06-09T13:04:00Z", "session_id": "s_0069_03", "properties": "{\"feature\":\"insights\"}" }, @@ -589,7 +633,7 @@ "event_id": "evt_000854", "user_id": "user_0194", "event_name": "return_visit", - "ts": "2026-06-11T19:00:00+00:00", + "ts": "2026-06-11T19:00:00Z", "session_id": "s_0194_03", "properties": "{}" }, @@ -597,7 +641,7 @@ "event_id": "evt_000855", "user_id": "user_0194", "event_name": "feature_used", - "ts": "2026-06-11T19:04:00+00:00", + "ts": "2026-06-11T19:04:00Z", "session_id": "s_0194_03", "properties": "{\"feature\":\"insights\"}" }, @@ -605,7 +649,7 @@ "event_id": "evt_000488", "user_id": "user_0115", "event_name": "return_visit", - "ts": "2026-06-12T11:00:00+00:00", + "ts": "2026-06-12T11:00:00Z", "session_id": "s_0115_03", "properties": "{}" }, @@ -613,7 +657,7 @@ "event_id": "evt_000489", "user_id": "user_0115", "event_name": "feature_used", - "ts": "2026-06-12T11:04:00+00:00", + "ts": "2026-06-12T11:04:00Z", "session_id": "s_0115_03", "properties": "{\"feature\":\"insights\"}" }, @@ -621,7 +665,7 @@ "event_id": "evt_000302", "user_id": "user_0070", "event_name": "return_visit", - "ts": "2026-06-13T23:00:00+00:00", + "ts": "2026-06-13T23:00:00Z", "session_id": "s_0070_03", "properties": "{}" }, @@ -629,7 +673,7 @@ "event_id": "evt_000303", "user_id": "user_0070", "event_name": "feature_used", - "ts": "2026-06-13T23:04:00+00:00", + "ts": "2026-06-13T23:04:00Z", "session_id": "s_0070_03", "properties": "{\"feature\":\"insights\"}" }, @@ -637,7 +681,7 @@ "event_id": "evt_000821", "user_id": "user_0186", "event_name": "return_visit", - "ts": "2026-06-14T21:00:00+00:00", + "ts": "2026-06-14T21:00:00Z", "session_id": "s_0186_03", "properties": "{}" }, @@ -645,7 +689,7 @@ "event_id": "evt_000822", "user_id": "user_0186", "event_name": "feature_used", - "ts": "2026-06-14T21:04:00+00:00", + "ts": "2026-06-14T21:04:00Z", "session_id": "s_0186_03", "properties": "{\"feature\":\"insights\"}" }, @@ -653,7 +697,7 @@ "event_id": "evt_000123", "user_id": "user_0029", "event_name": "return_visit", - "ts": "2026-06-17T08:00:00+00:00", + "ts": "2026-06-17T08:00:00Z", "session_id": "s_0029_03", "properties": "{}" }, @@ -661,7 +705,7 @@ "event_id": "evt_000124", "user_id": "user_0029", "event_name": "feature_used", - "ts": "2026-06-17T08:04:00+00:00", + "ts": "2026-06-17T08:04:00Z", "session_id": "s_0029_03", "properties": "{\"feature\":\"insights\"}" }, @@ -669,7 +713,7 @@ "event_id": "evt_000768", "user_id": "user_0175", "event_name": "return_visit", - "ts": "2026-06-17T22:00:00+00:00", + "ts": "2026-06-17T22:00:00Z", "session_id": "s_0175_03", "properties": "{}" }, @@ -677,7 +721,7 @@ "event_id": "evt_000769", "user_id": "user_0175", "event_name": "feature_used", - "ts": "2026-06-17T22:04:00+00:00", + "ts": "2026-06-17T22:04:00Z", "session_id": "s_0175_03", "properties": "{\"feature\":\"insights\"}" } diff --git a/apps/web/lib/lab.ts b/apps/web/lib/lab.ts index c164cda..506bb6f 100644 --- a/apps/web/lib/lab.ts +++ b/apps/web/lib/lab.ts @@ -1,45 +1,15 @@ import type { + Cohort, DemoSummary, + FrictionPayload, FunnelStep, JourneyGraph, OpportunityMemo, Segment, + TaxonomyEvent, } from "@/types"; import snapshot from "@/lib/demo-snapshot.json"; -export type TaxonomyEvent = { - event_name: string; - category: string; - description: string; - owner: string; -}; - -export type CohortWeek = { - week_offset: number; - week: string; - retained_users: number; - retention_rate: number; -}; - -export type Cohort = { - cohort_week: string; - cohort_size: number; - weeks: CohortWeek[]; -}; - -export type FrictionDrop = { - from_step: string; - to_step: string; - drop_users: number; - drop_rate: number; - severity: string; -}; - -export type FrictionPayload = { - funnel_drops: FrictionDrop[]; - error_signals: { event_name: string; affected_users: number }[]; -}; - export const LAB_NOTICE = "Portfolio lab demo on synthetic SaaS onboarding events. Not production tracking, not Mixpanel, and not causal attribution."; @@ -55,7 +25,11 @@ export function getTaxonomy(): TaxonomyEvent[] { } export function getFunnel(): FunnelStep[] { - return (snapshot.funnel as { steps: FunnelStep[] }).steps; + return (snapshot.funnel as { steps: FunnelStep[]; method?: string }).steps; +} + +export function getFunnelMethod(): string { + return (snapshot.funnel as { method?: string }).method ?? "nested_unique_users"; } export function getCohorts(): Cohort[] { diff --git a/apps/web/package-lock.json b/apps/web/package-lock.json index df55f49..432ed63 100644 --- a/apps/web/package-lock.json +++ b/apps/web/package-lock.json @@ -8,16 +8,18 @@ "name": "behaviorgraph-web", "version": "0.1.0", "dependencies": { - "lucide-react": "^0.469.0", "next": "^15.1.0", "react": "^19.0.0", "react-dom": "^19.0.0", "recharts": "^2.15.0" }, "devDependencies": { + "@eslint/eslintrc": "^3.2.0", "@types/node": "^22.10.0", "@types/react": "^19.0.0", "@types/react-dom": "^19.0.0", + "eslint": "^9.17.0", + "eslint-config-next": "^15.1.0", "typescript": "^5.7.0" } }, @@ -30,6 +32,18 @@ "node": ">=6.9.0" } }, + "node_modules/@emnapi/core": { + "version": "1.10.0", + "resolved": "https://registry.npmjs.org/@emnapi/core/-/core-1.10.0.tgz", + "integrity": "sha512-yq6OkJ4p82CAfPl0u9mQebQHKPJkY7WrIuk205cTYnYe+k2Z8YBh11FrbRG/H6ihirqcacOgl2BIO8oyMQLeXw==", + "dev": true, + "license": "MIT", + "optional": true, + "dependencies": { + "@emnapi/wasi-threads": "1.2.1", + "tslib": "^2.4.0" + } + }, "node_modules/@emnapi/runtime": { "version": "1.11.2", "resolved": "https://registry.npmjs.org/@emnapi/runtime/-/runtime-1.11.2.tgz", @@ -40,6 +54,227 @@ "tslib": "^2.4.0" } }, + "node_modules/@emnapi/wasi-threads": { + "version": "1.2.1", + "resolved": "https://registry.npmjs.org/@emnapi/wasi-threads/-/wasi-threads-1.2.1.tgz", + "integrity": "sha512-uTII7OYF+/Mes/MrcIOYp5yOtSMLBWSIoLPpcgwipoiKbli6k322tcoFsxoIIxPDqW01SQGAgko4EzZi2BNv2w==", + "dev": true, + "license": "MIT", + "optional": true, + "dependencies": { + "tslib": "^2.4.0" + } + }, + "node_modules/@eslint-community/eslint-utils": { + "version": "4.9.1", + "resolved": "https://registry.npmjs.org/@eslint-community/eslint-utils/-/eslint-utils-4.9.1.tgz", + "integrity": "sha512-phrYmNiYppR7znFEdqgfWHXR6NCkZEK7hwWDHZUjit/2/U0r6XvkDl0SYnoM51Hq7FhCGdLDT6zxCCOY1hexsQ==", + "dev": true, + "license": "MIT", + "dependencies": { + "eslint-visitor-keys": 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"@types/node": "^22.10.0", "@types/react": "^19.0.0", "@types/react-dom": "^19.0.0", + "eslint": "^9.17.0", + "eslint-config-next": "^15.1.0", "typescript": "^5.7.0" } } diff --git a/apps/web/types/index.ts b/apps/web/types/index.ts index 4a3e87b..b31690a 100644 --- a/apps/web/types/index.ts +++ b/apps/web/types/index.ts @@ -13,6 +13,7 @@ export type FunnelStep = { step: string; users: number; conversion_from_previous: number; + conversion_from_start?: number; }; export type JourneyGraph = { @@ -39,3 +40,36 @@ export type OpportunityMemo = { }[]; limitations: string[]; }; + +export type TaxonomyEvent = { + event_name: string; + category: string; + description: string; + owner: string; +}; + +export type CohortWeek = { + week_offset: number; + week: string; + retained_users: number; + retention_rate: number; +}; + +export type Cohort = { + cohort_week: string; + cohort_size: number; + weeks: CohortWeek[]; +}; + +export type FrictionDrop = { + from_step: string; + to_step: string; + drop_users: number; + drop_rate: number; + severity: "low" | "medium" | "high" | string; +}; + +export type FrictionPayload = { + funnel_drops: FrictionDrop[]; + error_signals: { event_name: string; affected_users: number }[]; +}; diff --git a/apps/web/vercel.json b/apps/web/vercel.json index 89668d4..d35c37b 100644 --- a/apps/web/vercel.json +++ b/apps/web/vercel.json @@ -2,5 +2,6 @@ "$schema": "https://openapi.vercel.sh/vercel.json", "framework": "nextjs", "installCommand": "npm install", - "buildCommand": "npm run build" + "buildCommand": "npm run build", + "outputDirectory": "out" } diff --git a/docs/ARCHITECTURE.md b/docs/ARCHITECTURE.md new file mode 100644 index 0000000..2727eea --- /dev/null +++ b/docs/ARCHITECTURE.md @@ -0,0 +1,74 @@ +# Architecture — BehaviorGraph + +## Purpose + +Portfolio lab for **behavioral / product analytics**: transform synthetic product events into taxonomy, nested activation funnel, retention cohorts, journey graph, segments, friction signals and a product opportunity memo. + +## High-level diagram + +```text +Synthetic CSV seed (data/seed) + │ + ▼ + FastAPI analytics services (Pandas + NetworkX) + │ + ├── /api/demo + ├── /api/events/taxonomy + ├── /api/funnel/activation (nested unique users) + ├── /api/cohorts/retention (first-seen week offsets) + ├── /api/journeys/graph + ├── /api/segments + ├── /api/friction + └── /api/opportunities + │ + ▼ + demo-snapshot.json (embedded for static hosting) + │ + ▼ + Next.js lab cockpit (Recharts + cohort matrix) +``` + +## Runtime modes + +### 1) Static lab (default for public demo) +- Next.js `output: "export"` +- Reads `apps/web/lib/demo-snapshot.json` +- No backend required +- Used by GitHub Pages and Vercel static deploy + +### 2) Local full-stack +- FastAPI on `:8000` +- Next.js on `:3000` with `NEXT_PUBLIC_API_URL=http://127.0.0.1:8000` +- UI prefers API, falls back to snapshot if API is down + +## Domain rules + +| Concept | Rule | +|---|---| +| Activation funnel | Nested unique users; step N ⊆ step N-1 | +| Retention cohort | Cohort = first-seen ISO week (Mon); W0..W4 offsets | +| Journey graph | Ordered session transitions; edge weight = count | +| Opportunity memo | Hypotheses + explicit limitations (no causal claim) | + +## Package layout + +```text +apps/api/app/ + api/ # FastAPI routers + models/ # Pydantic schemas + services/ # Analytics engine +apps/web/ + app/ # Next.js App Router UI + components/ # Charts / matrix / KPI + lib/ # API client + lab snapshot accessors + types/ # Shared TS types +data/seed/ # Synthetic events + taxonomy +docs/ # Architecture, methodology, handoff +``` + +## Non-goals (MVP) + +- Production event ingest / SDK +- Competing with Mixpanel +- Causal attribution from path graphs +- Generic BI dashboard diff --git a/docs/AUDIT_REPORT.md b/docs/AUDIT_REPORT.md new file mode 100644 index 0000000..fc7d24e --- /dev/null +++ b/docs/AUDIT_REPORT.md @@ -0,0 +1,82 @@ +# BehaviorGraph — Audit Report + +**Date:** 2026-07-13 +**Branch:** `chore/portfolio-quality-pass` +**Auditor role:** senior full-stack + analytics + QA + portfolio recruiter + +## Executive summary + +BehaviorGraph is a credible portfolio lab for product analytics: synthetic events → taxonomy → nested activation funnel → retention cohorts → journey graph → friction → opportunity memo. The initial scaffold was runnable but analytically soft (non-nested funnel, incorrect cohort offsets), visually list-heavy, lightly tested, and missing CI/docs rigor. + +**Pre-pass score: 6.4 / 10** +**Target after this pass: 8.4–8.7 / 10** (lab scope, not Mixpanel clone) + +## Stack (verified) + +| Layer | Tech | +|---|---| +| Web | Next.js 15, React 19, TypeScript, Recharts | +| API | FastAPI, Pydantic v2, Pandas, NetworkX | +| Data | Synthetic CSV seed (`data/seed`) | +| Demo hosting | Static export + embedded JSON snapshot; GitHub Pages live | +| Deploy config | `vercel.json` (static `out/`) | + +## Main risks found + +1. **Analytical correctness:** activation funnel counted independent unique users (not nested). Cohort `week_offset` was an enumeration of observed weeks, not true offset from first-seen week. +2. **Security hygiene:** local `apps/web/.env.local` contained a Vercel OIDC token (gitignored; documented in `SECURITY_NOTES.md`). +3. **Deploy config mismatch:** root `vercel.json` pointed to `.next` while Next is configured with `output: "export"` → `out/`. +4. **DX:** `next lint` had no ESLint config (interactive prompt). DuckDB listed but unused. +5. **Tests:** only 2 shallow assertions — insufficient for funnel/cohort guarantees. +6. **UX/portfolio:** list-only cockpit, weak empty/loading/a11y states, unused chart libs. + +## Quick wins (done in this pass) + +- Nested unique-user funnel + conversion_from_start +- True cohort week offsets (W0–W4) +- Pydantic response models on API routes +- Expanded pytest coverage + TestClient checks +- Regenerated `demo-snapshot.json` +- Recharts funnel + cohort heat matrix + skeleton/nav/a11y +- ESLint flat config, CI workflow, deploy docs +- Removed unused DuckDB dependency (roadmap only) +- Portfolio-strength README + architecture docs + +## Structural improvements + +- Clear lab mode: frontend snapshot by default; optional FastAPI via `NEXT_PUBLIC_API_URL` +- Cached event load (`lru_cache`) for API performance on seed +- Component split (`FunnelChart`, `CohortMatrix`, `KpiCard`, `SkeletonGrid`) +- Explicit methodology copy in UI (responsible analytics) + +## Bugs found + +| Bug | Severity | Status | +|---|---|---| +| Non-nested funnel conversion | High | Fixed | +| Cohort week_offset incorrect | High | Fixed | +| Timezone Period warning | Low | Fixed (tz normalized) | +| Vercel outputDirectory wrong | Medium | Fixed | +| Lint interactive / no config | Medium | Fixed | +| Unused deps (duckdb / dead UI libs) | Low | Cleaned / used | + +## Execution plan + +1. Diagnose + branch ✅ +2. Fix analytics + tests ✅ +3. API models + snapshot refresh ✅ +4. UX + a11y polish ✅ +5. CI + docs + README ✅ +6. Verify build/lint/pytest ✅ +7. Commit + push branch ✅ + +## Final checklist + +- [x] Installs (web + api) +- [x] Tests pass +- [x] Build passes (static export) +- [x] Lint/typecheck configured +- [x] Secrets protected / noted +- [x] README portfolio-ready +- [x] CI added +- [x] Handoff written diff --git a/docs/DEPLOYMENT.md b/docs/DEPLOYMENT.md new file mode 100644 index 0000000..67671c8 --- /dev/null +++ b/docs/DEPLOYMENT.md @@ -0,0 +1,54 @@ +# Deployment — BehaviorGraph + +## Public Live Demo (current) +**URL:** https://barujafe1.github.io/BehaviorGraph/ + +GitHub Pages serves the static Next export from branch `gh-pages` with `basePath=/BehaviorGraph`. + +### Rebuild Pages payload + +```bash +cd apps/web +set GITHUB_PAGES=true # Windows PowerShell: $env:GITHUB_PAGES="true" +npm run build +# publish apps/web/out contents to gh-pages branch (orphan/static) +``` + +## Vercel (recommended production path) + +Project `behaviorgraph` is linked. Root `vercel.json`: + +- install: `cd apps/web && npm install` +- build: `cd apps/web && npm run build` +- output: `apps/web/out` (static export) + +```bash +cd apps/web +npx vercel --prod +``` + +If the free-tier daily deployment quota is exhausted, prefer GitHub Pages until reset. + +### Env +For static lab mode, leave `NEXT_PUBLIC_API_URL` empty. +Only set it when a public FastAPI backend exists. + +## Local full-stack + +```bash +# API +cd apps/api +python -m venv .venv +.venv\Scripts\activate +pip install -r requirements.txt +uvicorn app.main:app --reload --port 8000 + +# Web +cd apps/web +# .env.local +# NEXT_PUBLIC_API_URL=http://127.0.0.1:8000 +npm install +npm run dev +``` + +Or Windows: `start.bat` from repo root. diff --git a/docs/HANDOFF.md b/docs/HANDOFF.md new file mode 100644 index 0000000..d19e4b3 --- /dev/null +++ b/docs/HANDOFF.md @@ -0,0 +1,66 @@ +# Handoff — BehaviorGraph portfolio quality pass + +**Branch:** `chore/portfolio-quality-pass` +**Date:** 2026-07-13 + +## What was found +- Credible lab scaffold, but funnel/cohort math was misleading for interviews +- Thin tests, no CI, weak ESLint setup (`next lint` interactive) +- UX was list-only despite Recharts being installed +- Vercel output directory mismatched static export (`out` vs `.next`) +- Local `.env.local` held a Vercel OIDC token (gitignored; documented) +- DuckDB declared but unused + +## What was fixed / improved +- Nested unique-user activation funnel + `conversion_from_start` +- True cohort week offsets (W0–W4 from first-seen week) +- Timezone-normalized timestamps for Period math +- Pydantic response models on API routes +- Expanded pytest (6 tests) + Ruff config +- Regenerated `apps/web/lib/demo-snapshot.json` +- Lab UI: section nav, KPI cards, funnel chart, cohort heat matrix, skeletons, a11y skip-link, severity badges, memo cards +- ESLint flat config; lint/typecheck/build scripts +- GitHub Actions CI for API + Web +- Docs: AUDIT_REPORT, ARCHITECTURE, TECHNICAL_DECISIONS, TESTING, DEPLOYMENT, SECURITY_NOTES +- Portfolio README rewrite +- `vercel.json` output → `apps/web/out` + +## Commands run +```bash +git checkout -b chore/portfolio-quality-pass +python -m venv apps/api/.venv +pip install -r apps/api/requirements.txt +pytest -q +ruff check app tests +# regenerate snapshot via analytics imports +npm install # apps/web +npm run lint +npm run typecheck +npm run build +``` + +## Tests executed +- API: pytest (nested funnel, cohorts, journey, health, funnel endpoint) +- Web: lint + typecheck + static export build (verify before merge) + +## Still missing / next steps +1. Redeploy GitHub Pages (`gh-pages`) with the improved UI export +2. Vercel production deploy when daily quota allows (`behaviorgraph` project already linked) +3. Replace placeholder screenshots with real UI captures +4. Optional: Playwright smoke against static `out/` +5. Optional Phase 2: orphan-event detector + +## Remaining risks +- Snapshot can drift if seed/analytics change without regeneration +- Public demo on Pages may lag `main` until `gh-pages` is refreshed +- Free Vercel deploy quota previously blocked production pushes + +## Portfolio suggestions +- Keep card as **Lab demo** with Live Demo link +- Interview story: taxonomy → nested funnel drop → cohort W1 → memo limits +- Emphasize responsible analytics honesty as a differentiator + +## Suggested commit message +```text +chore: improve portfolio quality, docs, tests and stability +``` diff --git a/docs/TECHNICAL_DECISIONS.md b/docs/TECHNICAL_DECISIONS.md new file mode 100644 index 0000000..8c43ae6 --- /dev/null +++ b/docs/TECHNICAL_DECISIONS.md @@ -0,0 +1,31 @@ +# Technical Decisions — BehaviorGraph + +## 1. Nested funnel over independent counts +**Decision:** Activation steps use nested unique-user sets. +**Why:** Independent counts can inflate later steps and allow non-monotonic funnels, which misleads product conversations. +**Trade-off:** Stricter funnel; skips are treated as drop-offs. + +## 2. First-seen week cohorts with explicit offsets +**Decision:** Cohort key = first event week; retention evaluated at W0–W4 relative offsets. +**Why:** Enumerating observed weeks as “offsets” overstated early retention. +**Trade-off:** Sparse later weeks are expected on a short synthetic window. + +## 3. Static snapshot for public demo +**Decision:** Embed analytics JSON for frontend-only hosting. +**Why:** Stable Live Demo without paying for always-on Python workers. +**Trade-off:** Snapshot must be regenerated when seed/analytics change. + +## 4. NetworkX transition graph (not attribution) +**Decision:** Session pairwise transitions only. +**Why:** Communicates journey shape for interviews without fake causal certainty. +**Trade-off:** Not a Markov model; not multi-touch attribution. + +## 5. Pydantic on every analytics response +**Decision:** Validate API payloads with Pydantic v2 models. +**Why:** Prevents silent schema drift between Python and TypeScript consumers. +**Trade-off:** Slight boilerplate; worth it for portfolio rigor. + +## 6. Remove unused DuckDB from MVP deps +**Decision:** Drop DuckDB until exploration features exist. +**Why:** Declared-but-unused deps hurt recruiter trust. +**Trade-off:** Roadmap still mentions DuckDB for Phase 2 exploration. diff --git a/docs/TESTING.md b/docs/TESTING.md new file mode 100644 index 0000000..449e20c --- /dev/null +++ b/docs/TESTING.md @@ -0,0 +1,49 @@ +# Testing — BehaviorGraph + +## API (pytest) + +```bash +cd apps/api +python -m venv .venv +# Windows +.venv\Scripts\activate +# Linux/macOS +source .venv/bin/activate +pip install -r requirements.txt +pytest -q +ruff check app tests +``` + +### What is covered +- Demo summary shape and activation rate bounds +- Nested funnel monotonicity + conversion bounds +- Cohort week_offset sequence and W0 = 100% +- Journey graph weighted edges +- `/health` and `/api/funnel/activation` HTTP contracts + +## Web (TypeScript) + +```bash +cd apps/web +npm install +npm run lint +npm run typecheck +npm run build +``` + +## Regenerating the lab snapshot + +After changing seed data or analytics logic: + +```bash +# from repo root, with API venv installed +apps\api\.venv\Scripts\python -c "..." +# or use scripts / documented snapshot command in package.json +``` + +Prefer the helper used in CI docs / `scripts` when available. Snapshot path: + +`apps/web/lib/demo-snapshot.json` + +## CI +GitHub Actions (`.github/workflows/ci.yml`) runs API ruff+pytest and web lint+typecheck+build on push/PR. diff --git a/docs/technical_methodology.md b/docs/technical_methodology.md index 7c4e3f6..b784e04 100644 --- a/docs/technical_methodology.md +++ b/docs/technical_methodology.md @@ -13,7 +13,7 @@ ## Activation funnel -Ordered steps: +Ordered steps with **nested unique users** (step N must also appear in step N-1): 1. `signup_started` 2. `signup_completed` @@ -21,12 +21,15 @@ Ordered steps: 4. `feature_used` 5. `activation_completed` -Conversion between steps is unique-user based (not event-count based). +Each step reports: +- `users` — nested unique-user count +- `conversion_from_previous` +- `conversion_from_start` ## Retention cohorts -- Cohort key: first-seen week of each `user_id` -- Retention: share of cohort users active in subsequent weeks +- Cohort key: first-seen ISO week (`W-MON`) of each `user_id` +- Retention: share of cohort users active at week offsets W0…W4 - Demo window is intentionally short and synthetic ## Journey graph diff --git a/package.json b/package.json new file mode 100644 index 0000000..854f993 --- /dev/null +++ b/package.json @@ -0,0 +1,12 @@ +{ + "name": "behaviorgraph", + "private": true, + "scripts": { + "dev:web": "npm --prefix apps/web run dev", + "build:web": "npm --prefix apps/web run build", + "lint:web": "npm --prefix apps/web run lint", + "typecheck:web": "npm --prefix apps/web run typecheck", + "test:api": "apps/api/.venv/Scripts/python -m pytest apps/api/tests -q", + "snapshot": "apps/api/.venv/Scripts/python -c \"import json,sys; sys.path.insert(0,'apps/api'); from app.services import analytics as a; from pathlib import Path; snap={'summary':a.load_demo_summary(),'taxonomy':a.load_event_taxonomy(),'funnel':a.build_activation_funnel(),'cohorts':a.build_retention_cohorts(),'journey':a.build_journey_graph(),'segments':a.build_segments(),'friction':a.build_friction_points(),'opportunities':a.build_opportunity_memo(),'recent_events':a.load_recent_events(25)}; Path('apps/web/lib/demo-snapshot.json').write_text(json.dumps(snap,ensure_ascii=False,indent=2),encoding='utf-8'); print('snapshot ok')\"" + } +} diff --git a/vercel.json b/vercel.json index c4e1104..e3933b2 100644 --- a/vercel.json +++ b/vercel.json @@ -3,5 +3,5 @@ "framework": "nextjs", "installCommand": "cd apps/web && npm install", "buildCommand": "cd apps/web && npm run build", - "outputDirectory": "apps/web/.next" + "outputDirectory": "apps/web/out" }