SIENTIAPDE-1645: Remove validate.sh script, add jsonschema dependency, and improve test code readability

This commit is contained in:
Bruno Domingues
2026-08-05 11:23:22 -03:00
parent ebc7e5ce6f
commit 4133e200f7
4 changed files with 38 additions and 207 deletions

View File

@@ -7,4 +7,5 @@ git+ssh://git@github.com/Aignosi/sientia-dataops-library.git@1.12.0
git+ssh://git@github.com/Aignosi/sientia-model-library.git@0.8.3
prometheus-client==0.23.1
beautifulsoup4==4.12.3
evidently==0.6.7
evidently==0.6.7
jsonschema==4.26.0

View File

@@ -369,7 +369,10 @@ def test_prepare_data_increments_error_counter_and_still_observes_lag_on_failure
training.observe_lag_sync.assert_called_once()
training.emit_metric_sync.assert_called_once()
call_args = training.emit_metric_sync.call_args
assert call_args.kwargs['metric_object'] is mm_metrics.SIENTIA_TRAINING_DATA_PREPARATION_ERROR_COUNT_TOTAL
assert (
call_args.kwargs['metric_object']
is mm_metrics.SIENTIA_TRAINING_DATA_PREPARATION_ERROR_COUNT_TOTAL
)
def test_fit_model_observes_lag_on_success(training):
@@ -419,12 +422,16 @@ def test_fit_model_increments_error_counter_on_failure(training):
training.observe_lag_sync.assert_called_once()
training.emit_metric_sync.assert_called_once()
call_args = training.emit_metric_sync.call_args
assert call_args.kwargs['metric_object'] is mm_metrics.SIENTIA_TRAINING_MODEL_FIT_ERROR_COUNT_TOTAL
assert (
call_args.kwargs['metric_object'] is mm_metrics.SIENTIA_TRAINING_MODEL_FIT_ERROR_COUNT_TOTAL
)
@patch('model_manager.activities.training.mm_metrics')
@patch('model_manager.activities.training.mlflow')
def test_train_model_sets_quality_gauges_after_compute_metrics(mock_mlflow, mock_mm_metrics, training):
def test_train_model_sets_quality_gauges_after_compute_metrics(
mock_mlflow, mock_mm_metrics, training
):
tp = TrainModelParams.from_dict(
{**_minimal_params_dict(), 'model_metadata': {'schemas': {'components': {'schemas': {}}}}}
)
@@ -473,9 +480,15 @@ def test_train_model_sets_quality_gauges_after_compute_metrics(mock_mlflow, mock
training.train_model({'metadata': {}, 'train_params': tp.to_dict()})
mock_mm_metrics.SIENTIA_TRAINING_MODEL_QUALITY_MSE.labels.return_value.set.assert_called_once_with(0.5)
mock_mm_metrics.SIENTIA_TRAINING_MODEL_QUALITY_MAE.labels.return_value.set.assert_called_once_with(0.3)
mock_mm_metrics.SIENTIA_TRAINING_MODEL_QUALITY_R2.labels.return_value.set.assert_called_once_with(-0.1)
mock_mm_metrics.SIENTIA_TRAINING_MODEL_QUALITY_MSE.labels.return_value.set.assert_called_once_with(
0.5
)
mock_mm_metrics.SIENTIA_TRAINING_MODEL_QUALITY_MAE.labels.return_value.set.assert_called_once_with(
0.3
)
mock_mm_metrics.SIENTIA_TRAINING_MODEL_QUALITY_R2.labels.return_value.set.assert_called_once_with(
-0.1
)
@patch('model_manager.activities.training.mm_metrics')

View File

@@ -237,7 +237,10 @@ def test_sientia_training_data_preparation_error_count_total_is_counter():
from model_manager.metrics import SIENTIA_TRAINING_DATA_PREPARATION_ERROR_COUNT_TOTAL
assert isinstance(SIENTIA_TRAINING_DATA_PREPARATION_ERROR_COUNT_TOTAL, Counter)
assert 'sientia_training_data_preparation_error_count' in SIENTIA_TRAINING_DATA_PREPARATION_ERROR_COUNT_TOTAL._name
assert (
'sientia_training_data_preparation_error_count'
in SIENTIA_TRAINING_DATA_PREPARATION_ERROR_COUNT_TOTAL._name
)
_assert_training_labels(SIENTIA_TRAINING_DATA_PREPARATION_ERROR_COUNT_TOTAL)
@@ -257,7 +260,10 @@ def test_sientia_training_model_fit_error_count_total_is_counter():
from model_manager.metrics import SIENTIA_TRAINING_MODEL_FIT_ERROR_COUNT_TOTAL
assert isinstance(SIENTIA_TRAINING_MODEL_FIT_ERROR_COUNT_TOTAL, Counter)
assert 'sientia_training_model_fit_error_count' in SIENTIA_TRAINING_MODEL_FIT_ERROR_COUNT_TOTAL._name
assert (
'sientia_training_model_fit_error_count'
in SIENTIA_TRAINING_MODEL_FIT_ERROR_COUNT_TOTAL._name
)
_assert_training_labels(SIENTIA_TRAINING_MODEL_FIT_ERROR_COUNT_TOTAL)
@@ -340,9 +346,15 @@ def test_sientia_training_info_is_gauge():
assert SIENTIA_TRAINING_INFO._name == 'sientia_training_info'
expected_labels = {
'pod_id', 'model_name', 'model_type',
'dataset_train_rows', 'dataset_val_rows', 'feature_count',
'mse', 'mae', 'r2',
'pod_id',
'model_name',
'model_type',
'dataset_train_rows',
'dataset_val_rows',
'feature_count',
'mse',
'mae',
'r2',
}
assert expected_labels == set(SIENTIA_TRAINING_INFO._labelnames)

View File

@@ -1,195 +0,0 @@
#!/bin/bash
# Model Manager Code Validation Script
# This script runs all code quality checks before committing or deploying
#
# Usage:
# ./validate.sh # Run all checks including tests (default)
# ./validate.sh --no-tests # Skip unit tests
# ./validate.sh --skip-tests # Skip unit tests (alias)
# ./validate.sh --only-tests # Run only unit tests
# ./validate.sh --fix # Auto-fix formatting and linting, then run validations (no tests)
set -e # Exit on any error
# Parse command line arguments
RUN_TESTS=true
ONLY_TESTS=false
FIX_MODE=false
for arg in "$@"; do
case $arg in
--no-tests|--skip-tests)
RUN_TESTS=false
shift
;;
--only-tests)
ONLY_TESTS=true
shift
;;
--fix)
FIX_MODE=true
RUN_TESTS=false
shift
;;
--help|-h)
echo "Usage: $0 [OPTIONS]"
echo ""
echo "Options:"
echo " --no-tests, --skip-tests Skip unit tests (default: run tests)"
echo " --only-tests Run only unit tests"
echo " --fix Auto-fix formatting and linting, then run validations (no tests)"
echo " --help, -h Show this help message"
echo ""
exit 0
;;
*)
echo "Unknown option: $arg"
echo "Use --help for usage information"
exit 1
;;
esac
done
# Colors for output
RED='\033[0;31m'
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
BLUE='\033[0;34m'
NC='\033[0m' # No Color
echo -e "${BLUE}╔════════════════════════════════════════════════════════╗${NC}"
echo -e "${BLUE}║ Model Manager - Code Validation Suite ║${NC}"
echo -e "${BLUE}╚════════════════════════════════════════════════════════╝${NC}"
echo ""
# Handle --fix mode
if [ "$FIX_MODE" = true ]; then
echo -e "${BLUE}🔧 Running auto-fix mode...${NC}"
echo ""
echo -e "${BLUE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
echo -e "${BLUE}▶ Auto-fixing code formatting (Ruff)${NC}"
echo -e "${BLUE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
ruff format model_manager/ tests/
echo -e "${GREEN}✅ Code formatting applied${NC}"
echo ""
echo -e "${BLUE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
echo -e "${BLUE}▶ Auto-fixing linting issues (Ruff)${NC}"
echo -e "${BLUE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
ruff check --fix model_manager/ tests/
echo -e "${GREEN}✅ Linting fixes applied${NC}"
echo ""
echo -e "${YELLOW} Now running validations (without tests)...${NC}"
echo ""
fi
# Handle --only-tests mode
if [ "$ONLY_TESTS" = true ]; then
echo -e "${BLUE}🧪 Running only unit tests...${NC}"
echo ""
fi
if [ "$RUN_TESTS" = false ] && [ "$ONLY_TESTS" = false ]; then
echo -e "${YELLOW} Unit tests will be skipped${NC}"
echo ""
fi
# Check if virtual environment is activated
if [[ -z "${VIRTUAL_ENV}" ]] && [[ -z "${CONDA_DEFAULT_ENV}" ]]; then
echo -e "${YELLOW}⚠️ Warning: No virtual environment detected${NC}"
echo -e "${YELLOW} Consider activating your venv/conda environment${NC}"
echo ""
fi
# Function to run a validation step
run_step() {
local step_name=$1
local step_command=$2
echo -e "${BLUE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
echo -e "${BLUE}${step_name}${NC}"
echo -e "${BLUE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
if eval "$step_command"; then
echo -e "${GREEN}${step_name} - PASSED${NC}"
echo ""
return 0
else
echo -e "${RED}${step_name} - FAILED${NC}"
echo ""
return 1
fi
}
# Track failures
FAILED_STEPS=()
# Handle --only-tests mode
if [ "$ONLY_TESTS" = true ]; then
# Step 5: Unit Tests (pytest)
if ! run_step "Unit Tests (pytest)" "pytest tests/ --cov=model_manager --cov-report=term-missing --cov-report=xml --cov-report=html --cov-fail-under=80 -q"; then
FAILED_STEPS+=("Unit Tests")
fi
else
# Step 1: Code Formatting Check (Ruff)
if ! run_step "1. Code Formatting (Ruff)" "ruff format --check model_manager/ tests/"; then
FAILED_STEPS+=("Code Formatting")
fi
# Step 2: Linting (Ruff)
if ! run_step "2. Code Linting (Ruff)" "ruff check model_manager/ tests/"; then
FAILED_STEPS+=("Linting")
fi
# Step 3: Type Checking (mypy)
if ! run_step "3. Type Checking (mypy)" "mypy model_manager/"; then
FAILED_STEPS+=("Type Checking")
fi
# Step 4: Security Analysis (Bandit)
if ! run_step "4. Security Analysis (Bandit)" "bandit -r model_manager/ -ll -q"; then
FAILED_STEPS+=("Security Analysis")
fi
# Step 5: Unit Tests (pytest)
if [ "$RUN_TESTS" = true ]; then
if ! run_step "5. Unit Tests (pytest)" "pytest tests/ --cov=model_manager --cov-report=term-missing --cov-report=xml --cov-report=html --cov-fail-under=80 -q"; then
FAILED_STEPS+=("Unit Tests")
fi
else
echo -e "${BLUE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
echo -e "${BLUE}▶ 5. Unit Tests (pytest)${NC}"
echo -e "${BLUE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
echo -e "${YELLOW}⏭️ Unit Tests - SKIPPED${NC}"
echo ""
fi
fi
# Summary
echo -e "${BLUE}╔════════════════════════════════════════════════════════╗${NC}"
echo -e "${BLUE}║ Validation Summary ║${NC}"
echo -e "${BLUE}╚════════════════════════════════════════════════════════╝${NC}"
echo ""
if [ ${#FAILED_STEPS[@]} -eq 0 ]; then
echo -e "${GREEN}✅ All validation checks passed!${NC}"
echo -e "${GREEN} Your code is ready for commit/deployment.${NC}"
echo ""
exit 0
else
echo -e "${RED}❌ Validation failed for the following steps:${NC}"
for step in "${FAILED_STEPS[@]}"; do
echo -e "${RED}${step}${NC}"
done
echo ""
echo -e "${YELLOW}💡 Tips:${NC}"
echo -e "${YELLOW} • Run 'ruff format model_manager/ tests/' to auto-fix formatting${NC}"
echo -e "${YELLOW} • Run 'ruff check --fix model_manager/ tests/' to auto-fix linting issues${NC}"
echo -e "${YELLOW} • Review mypy errors and add type hints where needed${NC}"
echo -e "${YELLOW} • Check bandit warnings for security issues${NC}"
echo -e "${YELLOW} • Fix failing tests or improve test coverage${NC}"
echo ""
exit 1
fi