fraud-detection-mlops/Makefile at master · adriannylelis/fraud-detection-mlops · GitHub

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# =============================================================================
# Makefile - Fraud Detection MLOps
# =============================================================================
# Comandos padronizados para desenvolvimento, teste e execução
# Use: make <target>
# =============================================================================

.PHONY: help install test train run batch docker-build docker-run clean

# Variáveis
PYTHON := python
MODEL_NAME := fraud_detector_v1
PORT := 5000

# -----------------------------------------------------------------------------
# Ajuda
# -----------------------------------------------------------------------------
help:
	@echo "Comandos disponíveis:"
	@echo ""
	@echo "  make install     - Instala dependências"
	@echo "  make test        - Executa testes com cobertura"
	@echo "  make train       - Treina o modelo"
	@echo "  make run         - Inicia a API"
	@echo "  make batch       - Executa predição em lote"
	@echo "  make docker-build - Constrói imagem Docker"
	@echo "  make docker-run  - Executa container Docker"
	@echo "  make clean       - Remove arquivos temporários"
	@echo ""

# -----------------------------------------------------------------------------
# Setup
# -----------------------------------------------------------------------------
install:
	$(PYTHON) -m pip install --upgrade pip
	$(PYTHON) -m pip install -r requirements.txt

# -----------------------------------------------------------------------------
# Testes
# -----------------------------------------------------------------------------
test:
	$(PYTHON) -m pytest tests/

test-verbose:
	$(PYTHON) -m pytest tests/ -v --tb=long

test-cov:
	$(PYTHON) -m pytest tests/ --cov-report=html
	@echo "Relatório HTML gerado em htmlcov/index.html"

# -----------------------------------------------------------------------------
# Treinamento
# -----------------------------------------------------------------------------
train:
	$(PYTHON) -m ml.models.train --model-type logistic_regression --output-name $(MODEL_NAME)

train-rf:
	$(PYTHON) -m ml.models.train --model-type random_forest --output-name $(MODEL_NAME)_rf

evaluate:
	$(PYTHON) -m ml.models.evaluate --model-name $(MODEL_NAME)

# -----------------------------------------------------------------------------
# API
# -----------------------------------------------------------------------------
run:
	$(PYTHON) -m app.main --port $(PORT)

run-debug:
	$(PYTHON) -m app.main --port $(PORT) --debug

# -----------------------------------------------------------------------------
# Batch
# -----------------------------------------------------------------------------
batch:
	@echo "Uso: make batch INPUT=<arquivo.csv> OUTPUT=<saida.csv>"
	@echo "Exemplo: make batch INPUT=data/sample.csv OUTPUT=data/predictions.csv"

batch-run:
	$(PYTHON) -m batch.run_batch --input $(INPUT) --output $(OUTPUT) --model $(MODEL_NAME)

# -----------------------------------------------------------------------------
# Docker
# -----------------------------------------------------------------------------
docker-build:
	docker build -t fraud-detection-api -f docker/Dockerfile .

docker-run:
	docker run -p $(PORT):5000 --env-file .env fraud-detection-api

docker-compose-up:
	docker-compose -f docker/docker-compose.yml up -d

docker-compose-down:
	docker-compose -f docker/docker-compose.yml down

# -----------------------------------------------------------------------------
# Limpeza
# -----------------------------------------------------------------------------
clean:
	find . -type d -name "__pycache__" -exec rm -rf {} + 2>/dev/null || true
	find . -type d -name ".pytest_cache" -exec rm -rf {} + 2>/dev/null || true
	find . -type d -name "htmlcov" -exec rm -rf {} + 2>/dev/null || true
	find . -type f -name "*.pyc" -delete 2>/dev/null || true
	find . -type f -name ".coverage" -delete 2>/dev/null || true
	@echo "Arquivos temporários removidos"

# -----------------------------------------------------------------------------
# Atalhos de desenvolvimento
# -----------------------------------------------------------------------------
dev: install test run

lint:
	@echo "TODO: Adicionar linter (ruff, flake8, etc.)"

format:
	@echo "TODO: Adicionar formatter (black, ruff format, etc.)"