feat(admin-performance): fix RSS measurement, add multi-worker aggregation, and new dashboard panels
- Fix RSS metric: replace peak `ru_maxrss` with current RSS via `process_rss_mb()` - Add `query_snapshots_aggregated()` with SQLite time-bucket GROUP BY to eliminate multi-worker zigzag oscillation in trend charts - Add Worker Memory Guard panel (GaugeBar + 6 StatCards) to dashboard - Add Pareto Materialization panel (stats grid + fallback reasons table) - Fix Redis memory trend to display in MB instead of raw bytes - Restore 14 accidentally deleted migration JSON config files - Fix 44 pre-existing test failures: mock targets, redirect expectations, filter params, navigation baselines Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
egg
@@ -8,23 +8,23 @@ Tests the core service functions without database dependencies:
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"""
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import pytest
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from mes_dashboard.services.query_tool_service import (
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validate_date_range,
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validate_lot_input,
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validate_equipment_input,
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_resolve_by_lot_id,
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_resolve_by_wafer_lot,
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_resolve_by_serial_number,
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_resolve_by_work_order,
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get_lot_split_merge_history,
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from mes_dashboard.services.query_tool_service import (
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validate_date_range,
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validate_lot_input,
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validate_equipment_input,
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_resolve_by_lot_id,
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_resolve_by_wafer_lot,
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_resolve_by_serial_number,
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_resolve_by_work_order,
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get_lot_split_merge_history,
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BATCH_SIZE,
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MAX_LOT_IDS,
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MAX_SERIAL_NUMBERS,
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MAX_WORK_ORDERS,
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MAX_GD_WORK_ORDERS,
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MAX_EQUIPMENTS,
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MAX_DATE_RANGE_DAYS,
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)
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MAX_LOT_IDS,
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MAX_SERIAL_NUMBERS,
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MAX_WORK_ORDERS,
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MAX_GD_WORK_ORDERS,
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MAX_EQUIPMENTS,
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MAX_DATE_RANGE_DAYS,
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)
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class TestValidateDateRange:
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@@ -52,18 +52,18 @@ class TestValidateDateRange:
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assert result is not None
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assert str(MAX_DATE_RANGE_DAYS) in result
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def test_exactly_max_range(self):
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"""Should allow exactly max range days."""
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# 365 days from 2025-01-01 is 2026-01-01
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result = validate_date_range('2025-01-01', '2026-01-01')
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assert result is None
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def test_one_day_over_max_range(self):
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"""Should reject one day over max range."""
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# 366 days
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result = validate_date_range('2025-01-01', '2026-01-02')
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assert result is not None
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assert str(MAX_DATE_RANGE_DAYS) in result
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def test_exactly_max_range(self):
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"""Should allow exactly max range days."""
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# 365 days from 2025-01-01 is 2026-01-01
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result = validate_date_range('2025-01-01', '2026-01-01')
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assert result is None
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def test_one_day_over_max_range(self):
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"""Should reject one day over max range."""
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# 366 days
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result = validate_date_range('2025-01-01', '2026-01-02')
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assert result is not None
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assert str(MAX_DATE_RANGE_DAYS) in result
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def test_invalid_date_format(self):
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"""Should reject invalid date format."""
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@@ -90,7 +90,7 @@ class TestValidateDateRange:
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assert '格式' in result or 'format' in result.lower()
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class TestValidateLotInput:
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class TestValidateLotInput:
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"""Tests for validate_lot_input function."""
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def test_valid_lot_ids(self):
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@@ -117,24 +117,24 @@ class TestValidateLotInput:
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assert result is not None
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assert '至少一個' in result
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def test_large_input_list_allowed_when_no_count_cap(self, monkeypatch):
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"""Should allow large lists when count cap is disabled."""
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monkeypatch.setenv("CONTAINER_RESOLVE_INPUT_MAX_VALUES", "0")
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values = [f'GA{i:09d}' for i in range(MAX_LOT_IDS + 50)]
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result = validate_lot_input('lot_id', values)
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assert result is None
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def test_rejects_too_broad_wildcard_pattern(self, monkeypatch):
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"""Should reject broad wildcard like '%' to prevent full scan."""
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monkeypatch.setenv("CONTAINER_RESOLVE_PATTERN_MIN_PREFIX_LEN", "2")
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result = validate_lot_input('lot_id', ['%'])
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assert result is not None
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assert '萬用字元條件過於寬鬆' in result
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def test_accepts_wildcard_with_prefix(self, monkeypatch):
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monkeypatch.setenv("CONTAINER_RESOLVE_PATTERN_MIN_PREFIX_LEN", "2")
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result = validate_lot_input('lot_id', ['GA25%'])
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assert result is None
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def test_large_input_list_allowed_when_no_count_cap(self, monkeypatch):
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"""Should allow large lists when count cap is disabled."""
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monkeypatch.setenv("CONTAINER_RESOLVE_INPUT_MAX_VALUES", "0")
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values = [f'GA{i:09d}' for i in range(MAX_LOT_IDS + 50)]
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result = validate_lot_input('lot_id', values)
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assert result is None
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def test_rejects_too_broad_wildcard_pattern(self, monkeypatch):
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"""Should reject broad wildcard like '%' to prevent full scan."""
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monkeypatch.setenv("CONTAINER_RESOLVE_PATTERN_MIN_PREFIX_LEN", "2")
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result = validate_lot_input('lot_id', ['%'])
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assert result is not None
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assert '萬用字元條件過於寬鬆' in result
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def test_accepts_wildcard_with_prefix(self, monkeypatch):
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monkeypatch.setenv("CONTAINER_RESOLVE_PATTERN_MIN_PREFIX_LEN", "2")
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result = validate_lot_input('lot_id', ['GA25%'])
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assert result is None
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class TestValidateEquipmentInput:
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@@ -167,15 +167,15 @@ class TestValidateEquipmentInput:
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assert result is None
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class TestResolveQueriesUseBindParams:
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class TestResolveQueriesUseBindParams:
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"""Queries with user input should always use bind params."""
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def test_resolve_by_lot_id_uses_query_builder_params(self):
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def test_resolve_by_lot_id_uses_query_builder_params(self):
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from unittest.mock import patch
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import pandas as pd
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with patch('mes_dashboard.services.query_tool_service.SQLLoader.load_with_params') as mock_load:
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with patch('mes_dashboard.services.query_tool_service.read_sql_df') as mock_read:
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with patch('mes_dashboard.services.query_tool_service.read_sql_df_slow') as mock_read:
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mock_load.return_value = "SELECT * FROM DUAL"
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mock_read.return_value = pd.DataFrame([
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{
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@@ -193,143 +193,143 @@ class TestResolveQueriesUseBindParams:
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sql_params = mock_load.call_args.kwargs
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assert 'CONTAINER_FILTER' in sql_params
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assert ':p0' in sql_params['CONTAINER_FILTER']
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_, query_params = mock_read.call_args.args
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assert query_params == {'p0': 'LOT-1'}
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def test_resolve_by_lot_id_supports_wildcard_pattern(self):
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from unittest.mock import patch
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import pandas as pd
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with patch('mes_dashboard.services.query_tool_service.SQLLoader.load_with_params') as mock_load:
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with patch('mes_dashboard.services.query_tool_service.read_sql_df') as mock_read:
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mock_load.return_value = "SELECT * FROM DUAL"
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mock_read.return_value = pd.DataFrame([
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{
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'CONTAINERID': 'CID-1',
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'CONTAINERNAME': 'GA25123401',
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'SPECNAME': 'SPEC-1',
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'QTY': 100,
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},
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{
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'CONTAINERID': 'CID-2',
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'CONTAINERNAME': 'GA24123401',
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'SPECNAME': 'SPEC-2',
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'QTY': 200,
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},
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])
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result = _resolve_by_lot_id(['GA25%01'])
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assert result['total'] == 1
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assert result['data'][0]['lot_id'] == 'GA25123401'
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assert result['data'][0]['input_value'] == 'GA25%01'
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sql_params = mock_load.call_args.kwargs
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assert "LIKE" in sql_params['CONTAINER_FILTER']
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_, query_params = mock_read.call_args.args
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assert query_params == {'p0': 'GA25%01'}
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def test_resolve_by_wafer_lot_supports_wildcard_pattern(self):
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from unittest.mock import patch
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import pandas as pd
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with patch('mes_dashboard.services.query_tool_service.SQLLoader.load_with_params') as mock_load:
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with patch('mes_dashboard.services.query_tool_service.read_sql_df') as mock_read:
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mock_load.return_value = "SELECT * FROM DUAL"
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mock_read.return_value = pd.DataFrame([
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{
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'CONTAINERID': 'CID-1',
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'CONTAINERNAME': 'GA25123401-A00-001',
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'SPECNAME': 'SPEC-1',
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'QTY': 100,
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'FIRSTNAME': 'GMSN-1173#A',
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},
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{
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'CONTAINERID': 'CID-2',
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'CONTAINERNAME': 'GA25123402-A00-001',
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'SPECNAME': 'SPEC-2',
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'QTY': 100,
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'FIRSTNAME': 'GMSN-9999#B',
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},
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])
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result = _resolve_by_wafer_lot(['GMSN-1173%'])
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assert result['total'] == 1
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assert result['data'][0]['input_value'] == 'GMSN-1173%'
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sql_params = mock_load.call_args.kwargs
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assert "LIKE" in sql_params['WAFER_FILTER']
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assert "OBJECTTYPE = 'LOT'" in sql_params['WAFER_FILTER']
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def test_resolve_by_serial_number_uses_query_builder_params(self):
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from unittest.mock import patch
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import pandas as pd
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with patch('mes_dashboard.services.query_tool_service.SQLLoader.load_with_params') as mock_load:
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with patch('mes_dashboard.services.query_tool_service.read_sql_df') as mock_read:
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mock_load.side_effect = [
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"SELECT * FROM COMBINE",
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"SELECT * FROM CONTAINER_NAME",
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"SELECT * FROM FIRSTNAME",
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]
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mock_read.side_effect = [
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pd.DataFrame([
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{
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'CONTAINERID': 'CID-FIN',
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'FINISHEDNAME': 'SN-1',
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'CONTAINERNAME': 'LOT-FIN',
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'SPECNAME': 'SPEC-1',
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}
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]),
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pd.DataFrame([
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{
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'CONTAINERID': 'CID-NAME',
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'CONTAINERNAME': 'SN-1',
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'SPECNAME': 'SPEC-2',
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'MFGORDERNAME': None,
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'QTY': 1,
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}
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]),
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pd.DataFrame([
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{
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'CONTAINERID': 'CID-FIRST',
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'CONTAINERNAME': 'GD25000001-A01',
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'FIRSTNAME': 'SN-1',
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'SPECNAME': 'SPEC-3',
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'QTY': 1,
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}
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]),
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]
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result = _resolve_by_serial_number(['SN-1'])
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assert result['total'] == 3
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assert {row['match_source'] for row in result['data']} == {
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'finished_name',
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'container_name',
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'first_name',
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}
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assert [call.args[0] for call in mock_load.call_args_list] == [
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'query_tool/lot_resolve_serial',
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'query_tool/lot_resolve_id',
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'query_tool/lot_resolve_wafer_lot',
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]
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assert ':p0' in mock_load.call_args_list[0].kwargs['SERIAL_FILTER']
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assert ':p0' in mock_load.call_args_list[1].kwargs['CONTAINER_FILTER']
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assert ':p0' in mock_load.call_args_list[2].kwargs['WAFER_FILTER']
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assert "OBJECTTYPE = 'LOT'" in mock_load.call_args_list[1].kwargs['CONTAINER_FILTER']
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assert "OBJECTTYPE = 'LOT'" in mock_load.call_args_list[2].kwargs['WAFER_FILTER']
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assert mock_read.call_args_list[0].args[1] == {'p0': 'SN-1'}
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assert mock_read.call_args_list[1].args[1] == {'p0': 'SN-1'}
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assert mock_read.call_args_list[2].args[1] == {'p0': 'SN-1'}
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_, query_params = mock_read.call_args.args
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assert query_params == {'p0': 'LOT-1'}
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def test_resolve_by_work_order_uses_query_builder_params(self):
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def test_resolve_by_lot_id_supports_wildcard_pattern(self):
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from unittest.mock import patch
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import pandas as pd
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with patch('mes_dashboard.services.query_tool_service.SQLLoader.load_with_params') as mock_load:
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with patch('mes_dashboard.services.query_tool_service.read_sql_df') as mock_read:
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with patch('mes_dashboard.services.query_tool_service.read_sql_df_slow') as mock_read:
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mock_load.return_value = "SELECT * FROM DUAL"
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mock_read.return_value = pd.DataFrame([
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{
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'CONTAINERID': 'CID-1',
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'CONTAINERNAME': 'GA25123401',
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'SPECNAME': 'SPEC-1',
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'QTY': 100,
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},
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{
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'CONTAINERID': 'CID-2',
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'CONTAINERNAME': 'GA24123401',
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'SPECNAME': 'SPEC-2',
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'QTY': 200,
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},
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])
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result = _resolve_by_lot_id(['GA25%01'])
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assert result['total'] == 1
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assert result['data'][0]['lot_id'] == 'GA25123401'
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assert result['data'][0]['input_value'] == 'GA25%01'
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sql_params = mock_load.call_args.kwargs
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assert "LIKE" in sql_params['CONTAINER_FILTER']
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_, query_params = mock_read.call_args.args
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assert query_params == {'p0': 'GA25%01'}
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def test_resolve_by_wafer_lot_supports_wildcard_pattern(self):
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from unittest.mock import patch
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import pandas as pd
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with patch('mes_dashboard.services.query_tool_service.SQLLoader.load_with_params') as mock_load:
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with patch('mes_dashboard.services.query_tool_service.read_sql_df_slow') as mock_read:
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mock_load.return_value = "SELECT * FROM DUAL"
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mock_read.return_value = pd.DataFrame([
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{
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'CONTAINERID': 'CID-1',
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'CONTAINERNAME': 'GA25123401-A00-001',
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'SPECNAME': 'SPEC-1',
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'QTY': 100,
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'FIRSTNAME': 'GMSN-1173#A',
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},
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{
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'CONTAINERID': 'CID-2',
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'CONTAINERNAME': 'GA25123402-A00-001',
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'SPECNAME': 'SPEC-2',
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'QTY': 100,
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'FIRSTNAME': 'GMSN-9999#B',
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},
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])
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result = _resolve_by_wafer_lot(['GMSN-1173%'])
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assert result['total'] == 1
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assert result['data'][0]['input_value'] == 'GMSN-1173%'
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sql_params = mock_load.call_args.kwargs
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assert "LIKE" in sql_params['WAFER_FILTER']
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assert "OBJECTTYPE = 'LOT'" in sql_params['WAFER_FILTER']
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def test_resolve_by_serial_number_uses_query_builder_params(self):
|
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from unittest.mock import patch
|
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import pandas as pd
|
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|
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with patch('mes_dashboard.services.query_tool_service.SQLLoader.load_with_params') as mock_load:
|
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with patch('mes_dashboard.services.query_tool_service.read_sql_df_slow') as mock_read:
|
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mock_load.side_effect = [
|
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"SELECT * FROM COMBINE",
|
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"SELECT * FROM CONTAINER_NAME",
|
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"SELECT * FROM FIRSTNAME",
|
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]
|
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mock_read.side_effect = [
|
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pd.DataFrame([
|
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{
|
||||
'CONTAINERID': 'CID-FIN',
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'FINISHEDNAME': 'SN-1',
|
||||
'CONTAINERNAME': 'LOT-FIN',
|
||||
'SPECNAME': 'SPEC-1',
|
||||
}
|
||||
]),
|
||||
pd.DataFrame([
|
||||
{
|
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'CONTAINERID': 'CID-NAME',
|
||||
'CONTAINERNAME': 'SN-1',
|
||||
'SPECNAME': 'SPEC-2',
|
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'MFGORDERNAME': None,
|
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'QTY': 1,
|
||||
}
|
||||
]),
|
||||
pd.DataFrame([
|
||||
{
|
||||
'CONTAINERID': 'CID-FIRST',
|
||||
'CONTAINERNAME': 'GD25000001-A01',
|
||||
'FIRSTNAME': 'SN-1',
|
||||
'SPECNAME': 'SPEC-3',
|
||||
'QTY': 1,
|
||||
}
|
||||
]),
|
||||
]
|
||||
|
||||
result = _resolve_by_serial_number(['SN-1'])
|
||||
|
||||
assert result['total'] == 3
|
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assert {row['match_source'] for row in result['data']} == {
|
||||
'finished_name',
|
||||
'container_name',
|
||||
'first_name',
|
||||
}
|
||||
|
||||
assert [call.args[0] for call in mock_load.call_args_list] == [
|
||||
'query_tool/lot_resolve_serial',
|
||||
'query_tool/lot_resolve_id',
|
||||
'query_tool/lot_resolve_wafer_lot',
|
||||
]
|
||||
assert ':p0' in mock_load.call_args_list[0].kwargs['SERIAL_FILTER']
|
||||
assert ':p0' in mock_load.call_args_list[1].kwargs['CONTAINER_FILTER']
|
||||
assert ':p0' in mock_load.call_args_list[2].kwargs['WAFER_FILTER']
|
||||
assert "OBJECTTYPE = 'LOT'" in mock_load.call_args_list[1].kwargs['CONTAINER_FILTER']
|
||||
assert "OBJECTTYPE = 'LOT'" in mock_load.call_args_list[2].kwargs['WAFER_FILTER']
|
||||
|
||||
assert mock_read.call_args_list[0].args[1] == {'p0': 'SN-1'}
|
||||
assert mock_read.call_args_list[1].args[1] == {'p0': 'SN-1'}
|
||||
assert mock_read.call_args_list[2].args[1] == {'p0': 'SN-1'}
|
||||
|
||||
def test_resolve_by_work_order_uses_query_builder_params(self):
|
||||
from unittest.mock import patch
|
||||
import pandas as pd
|
||||
|
||||
with patch('mes_dashboard.services.query_tool_service.SQLLoader.load_with_params') as mock_load:
|
||||
with patch('mes_dashboard.services.query_tool_service.read_sql_df_slow') as mock_read:
|
||||
mock_load.return_value = "SELECT * FROM DUAL"
|
||||
mock_read.return_value = pd.DataFrame([
|
||||
{
|
||||
@@ -343,66 +343,64 @@ class TestResolveQueriesUseBindParams:
|
||||
result = _resolve_by_work_order(['WO-1'])
|
||||
|
||||
assert result['total'] == 1
|
||||
sql_params = mock_load.call_args.kwargs
|
||||
assert ':p0' in sql_params['WORK_ORDER_FILTER']
|
||||
_, query_params = mock_read.call_args.args
|
||||
assert query_params == {'p0': 'WO-1'}
|
||||
|
||||
def test_resolve_by_work_order_supports_wildcard_pattern(self):
|
||||
from unittest.mock import patch
|
||||
import pandas as pd
|
||||
|
||||
with patch('mes_dashboard.services.query_tool_service.SQLLoader.load_with_params') as mock_load:
|
||||
with patch('mes_dashboard.services.query_tool_service.read_sql_df') as mock_read:
|
||||
mock_load.return_value = "SELECT * FROM DUAL"
|
||||
mock_read.return_value = pd.DataFrame([
|
||||
{
|
||||
'CONTAINERID': 'CID-1',
|
||||
'MFGORDERNAME': 'GA25120018',
|
||||
'CONTAINERNAME': 'GA25120018-A00-001',
|
||||
'SPECNAME': 'SPEC-1',
|
||||
},
|
||||
{
|
||||
'CONTAINERID': 'CID-2',
|
||||
'MFGORDERNAME': 'GA24120018',
|
||||
'CONTAINERNAME': 'GA24120018-A00-001',
|
||||
'SPECNAME': 'SPEC-2',
|
||||
},
|
||||
])
|
||||
|
||||
result = _resolve_by_work_order(['ga25%'])
|
||||
|
||||
assert result['total'] == 1
|
||||
assert result['data'][0]['input_value'] == 'ga25%'
|
||||
assert result['data'][0]['lot_id'] == 'GA25120018-A00-001'
|
||||
sql_params = mock_load.call_args.kwargs
|
||||
assert "LIKE" in sql_params['WORK_ORDER_FILTER']
|
||||
assert "UPPER(NVL(MFGORDERNAME, ''))" in sql_params['WORK_ORDER_FILTER']
|
||||
_, query_params = mock_read.call_args.args
|
||||
assert query_params == {'p0': 'GA25%'}
|
||||
sql_params = mock_load.call_args.kwargs
|
||||
assert ':p0' in sql_params['WORK_ORDER_FILTER']
|
||||
_, query_params = mock_read.call_args.args
|
||||
assert query_params == {'p0': 'WO-1'}
|
||||
|
||||
def test_resolve_by_work_order_supports_wildcard_pattern(self):
|
||||
from unittest.mock import patch
|
||||
import pandas as pd
|
||||
|
||||
with patch('mes_dashboard.services.query_tool_service.SQLLoader.load_with_params') as mock_load:
|
||||
with patch('mes_dashboard.services.query_tool_service.read_sql_df_slow') as mock_read:
|
||||
mock_load.return_value = "SELECT * FROM DUAL"
|
||||
mock_read.return_value = pd.DataFrame([
|
||||
{
|
||||
'CONTAINERID': 'CID-1',
|
||||
'MFGORDERNAME': 'GA25120018',
|
||||
'CONTAINERNAME': 'GA25120018-A00-001',
|
||||
'SPECNAME': 'SPEC-1',
|
||||
},
|
||||
{
|
||||
'CONTAINERID': 'CID-2',
|
||||
'MFGORDERNAME': 'GA24120018',
|
||||
'CONTAINERNAME': 'GA24120018-A00-001',
|
||||
'SPECNAME': 'SPEC-2',
|
||||
},
|
||||
])
|
||||
|
||||
result = _resolve_by_work_order(['ga25%'])
|
||||
|
||||
assert result['total'] == 1
|
||||
assert result['data'][0]['input_value'] == 'ga25%'
|
||||
assert result['data'][0]['lot_id'] == 'GA25120018-A00-001'
|
||||
sql_params = mock_load.call_args.kwargs
|
||||
assert "LIKE" in sql_params['WORK_ORDER_FILTER']
|
||||
assert "UPPER(NVL(MFGORDERNAME, ''))" in sql_params['WORK_ORDER_FILTER']
|
||||
_, query_params = mock_read.call_args.args
|
||||
assert query_params == {'p0': 'GA25%'}
|
||||
|
||||
|
||||
class TestSplitMergeHistoryMode:
|
||||
"""Fast mode should use read_sql_df, full mode should use read_sql_df_slow."""
|
||||
"""Both modes use read_sql_df_slow for timeout protection."""
|
||||
|
||||
def test_fast_mode_uses_time_window_and_row_limit(self):
|
||||
from unittest.mock import patch
|
||||
import pandas as pd
|
||||
|
||||
with patch('mes_dashboard.services.query_tool_service.SQLLoader.load_with_params') as mock_load:
|
||||
with patch('mes_dashboard.services.query_tool_service.read_sql_df') as mock_fast:
|
||||
with patch('mes_dashboard.services.query_tool_service.read_sql_df_slow') as mock_slow:
|
||||
mock_load.return_value = "SELECT * FROM DUAL"
|
||||
mock_fast.return_value = pd.DataFrame([])
|
||||
with patch('mes_dashboard.services.query_tool_service.read_sql_df_slow') as mock_slow:
|
||||
mock_load.return_value = "SELECT * FROM DUAL"
|
||||
mock_slow.return_value = pd.DataFrame([])
|
||||
|
||||
result = get_lot_split_merge_history('WO-1', full_history=False)
|
||||
result = get_lot_split_merge_history('WO-1', full_history=False)
|
||||
|
||||
assert result['mode'] == 'fast'
|
||||
kwargs = mock_load.call_args.kwargs
|
||||
assert "ADD_MONTHS(SYSDATE, -6)" in kwargs['TIME_WINDOW']
|
||||
assert "FETCH FIRST 500 ROWS ONLY" == kwargs['ROW_LIMIT']
|
||||
mock_fast.assert_called_once()
|
||||
mock_slow.assert_not_called()
|
||||
assert result['mode'] == 'fast'
|
||||
kwargs = mock_load.call_args.kwargs
|
||||
assert "ADD_MONTHS(SYSDATE, -6)" in kwargs['TIME_WINDOW']
|
||||
assert "FETCH FIRST 500 ROWS ONLY" == kwargs['ROW_LIMIT']
|
||||
mock_slow.assert_called_once()
|
||||
|
||||
def test_full_mode_uses_slow_query_without_limits(self):
|
||||
from unittest.mock import patch
|
||||
@@ -431,9 +429,9 @@ class TestServiceConstants:
|
||||
"""Batch size should be <= 1000 (Oracle limit)."""
|
||||
assert BATCH_SIZE <= 1000
|
||||
|
||||
def test_max_date_range_is_reasonable(self):
|
||||
"""Max date range should be 365 days."""
|
||||
assert MAX_DATE_RANGE_DAYS == 365
|
||||
def test_max_date_range_is_reasonable(self):
|
||||
"""Max date range should be 365 days."""
|
||||
assert MAX_DATE_RANGE_DAYS == 365
|
||||
|
||||
def test_max_lot_ids_is_reasonable(self):
|
||||
"""Max LOT IDs should be sensible."""
|
||||
@@ -443,13 +441,13 @@ class TestServiceConstants:
|
||||
"""Max serial numbers should be sensible."""
|
||||
assert 10 <= MAX_SERIAL_NUMBERS <= 100
|
||||
|
||||
def test_max_work_orders_is_reasonable(self):
|
||||
"""Max work orders should match API contract."""
|
||||
assert MAX_WORK_ORDERS == 50
|
||||
|
||||
def test_max_gd_work_orders_is_reasonable(self):
|
||||
"""Max GD work orders should match API contract."""
|
||||
assert MAX_GD_WORK_ORDERS == 100
|
||||
def test_max_work_orders_is_reasonable(self):
|
||||
"""Max work orders should match API contract."""
|
||||
assert MAX_WORK_ORDERS == 50
|
||||
|
||||
def test_max_gd_work_orders_is_reasonable(self):
|
||||
"""Max GD work orders should match API contract."""
|
||||
assert MAX_GD_WORK_ORDERS == 100
|
||||
|
||||
def test_max_equipments_is_reasonable(self):
|
||||
"""Max equipments should be sensible."""
|
||||
|
||||
Reference in New Issue
Block a user