feat(mid-section-defect): harden with distributed lock, rate limit, filter separation, abort, SQL classification and tests
Address 6 code review findings (P0-P3): add Redis distributed lock to prevent duplicate Oracle pipeline on cold cache, apply rate limiting to 3 high-cost routes, separate UI filter state from committed query state, add AbortController for request cancellation, push workcenter group classification into Oracle SQL CASE WHEN, and add 18 route+service tests. Also add workcenter group selection to job-query equipment selector and rename button to "查詢". Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
egg
@@ -36,45 +36,45 @@ function renderTxnCell(txn, apiKey) {
|
||||
return escapeHtml(safeText(txn[apiKey]));
|
||||
}
|
||||
|
||||
|
||||
// State
|
||||
let allEquipments = [];
|
||||
let selectedEquipments = new Set();
|
||||
let jobsData = [];
|
||||
let expandedJobs = new Set();
|
||||
|
||||
// Initialize
|
||||
document.addEventListener('DOMContentLoaded', () => {
|
||||
loadEquipments();
|
||||
setLast90Days();
|
||||
|
||||
// Close dropdown when clicking outside
|
||||
document.addEventListener('click', (e) => {
|
||||
const dropdown = document.getElementById('equipmentDropdown');
|
||||
const selector = document.querySelector('.equipment-selector');
|
||||
if (!selector.contains(e.target)) {
|
||||
dropdown.classList.remove('show');
|
||||
}
|
||||
});
|
||||
});
|
||||
|
||||
// Load equipments from cache
|
||||
async function loadEquipments() {
|
||||
try {
|
||||
const data = await MesApi.get('/api/job-query/resources');
|
||||
if (data.error) {
|
||||
document.getElementById('equipmentList').innerHTML = `<div class="error">${data.error}</div>`;
|
||||
return;
|
||||
}
|
||||
|
||||
allEquipments = data.data;
|
||||
renderEquipmentList(allEquipments);
|
||||
} catch (error) {
|
||||
document.getElementById('equipmentList').innerHTML = `<div class="error">載入失敗: ${error.message}</div>`;
|
||||
}
|
||||
}
|
||||
|
||||
// Render equipment list
|
||||
|
||||
// State
|
||||
let allEquipments = [];
|
||||
let selectedEquipments = new Set();
|
||||
let jobsData = [];
|
||||
let expandedJobs = new Set();
|
||||
|
||||
// Initialize
|
||||
document.addEventListener('DOMContentLoaded', () => {
|
||||
loadEquipments();
|
||||
setLast90Days();
|
||||
|
||||
// Close dropdown when clicking outside
|
||||
document.addEventListener('click', (e) => {
|
||||
const dropdown = document.getElementById('equipmentDropdown');
|
||||
const selector = document.querySelector('.equipment-selector');
|
||||
if (!selector.contains(e.target)) {
|
||||
dropdown.classList.remove('show');
|
||||
}
|
||||
});
|
||||
});
|
||||
|
||||
// Load equipments from cache
|
||||
async function loadEquipments() {
|
||||
try {
|
||||
const data = await MesApi.get('/api/job-query/resources');
|
||||
if (data.error) {
|
||||
document.getElementById('equipmentList').innerHTML = `<div class="error">${data.error}</div>`;
|
||||
return;
|
||||
}
|
||||
|
||||
allEquipments = data.data;
|
||||
renderEquipmentList(allEquipments);
|
||||
} catch (error) {
|
||||
document.getElementById('equipmentList').innerHTML = `<div class="error">載入失敗: ${error.message}</div>`;
|
||||
}
|
||||
}
|
||||
|
||||
// Render equipment list
|
||||
function renderEquipmentList(equipments) {
|
||||
const container = document.getElementById('equipmentList');
|
||||
|
||||
@@ -88,8 +88,18 @@ function renderTxnCell(txn, apiKey) {
|
||||
const workcenters = sortBy(Object.keys(grouped), (name) => name);
|
||||
|
||||
workcenters.forEach((workcenterName) => {
|
||||
html += `<div style="padding: 8px 15px; background: #f0f0f0; font-weight: 600; font-size: 12px; color: #666;">${escapeHtml(workcenterName)}</div>`;
|
||||
grouped[workcenterName].forEach((eq) => {
|
||||
const groupEquipments = grouped[workcenterName];
|
||||
const groupIds = groupEquipments.map((eq) => eq.RESOURCEID);
|
||||
const selectedInGroup = groupIds.filter((id) => selectedEquipments.has(id)).length;
|
||||
const allSelected = selectedInGroup === groupIds.length;
|
||||
const someSelected = selectedInGroup > 0 && !allSelected;
|
||||
const escapedName = escapeHtml(workcenterName);
|
||||
html += `<div class="workcenter-group-header" onclick="toggleWorkcenterGroup('${escapedName}')">
|
||||
<input type="checkbox" ${allSelected ? 'checked' : ''} ${someSelected ? 'class="indeterminate"' : ''} onclick="event.stopPropagation(); toggleWorkcenterGroup('${escapedName}')">
|
||||
<span class="workcenter-group-name">${escapedName}</span>
|
||||
<span class="workcenter-group-count">${selectedInGroup}/${groupIds.length}</span>
|
||||
</div>`;
|
||||
groupEquipments.forEach((eq) => {
|
||||
const isSelected = selectedEquipments.has(eq.RESOURCEID);
|
||||
const resourceId = escapeHtml(safeText(eq.RESOURCEID));
|
||||
const resourceName = escapeHtml(safeText(eq.RESOURCENAME));
|
||||
@@ -109,145 +119,169 @@ function renderTxnCell(txn, apiKey) {
|
||||
|
||||
container.innerHTML = html;
|
||||
}
|
||||
|
||||
// Toggle equipment dropdown
|
||||
function toggleEquipmentDropdown() {
|
||||
const dropdown = document.getElementById('equipmentDropdown');
|
||||
dropdown.classList.toggle('show');
|
||||
}
|
||||
|
||||
// Filter equipments by search
|
||||
function filterEquipments(query) {
|
||||
const q = query.toLowerCase();
|
||||
const filtered = allEquipments.filter(eq =>
|
||||
(eq.RESOURCENAME && eq.RESOURCENAME.toLowerCase().includes(q)) ||
|
||||
(eq.WORKCENTERNAME && eq.WORKCENTERNAME.toLowerCase().includes(q)) ||
|
||||
(eq.RESOURCEFAMILYNAME && eq.RESOURCEFAMILYNAME.toLowerCase().includes(q))
|
||||
);
|
||||
renderEquipmentList(filtered);
|
||||
}
|
||||
|
||||
// Toggle equipment selection
|
||||
function toggleEquipment(resourceId) {
|
||||
if (selectedEquipments.has(resourceId)) {
|
||||
selectedEquipments.delete(resourceId);
|
||||
} else {
|
||||
selectedEquipments.add(resourceId);
|
||||
}
|
||||
updateSelectedDisplay();
|
||||
renderEquipmentList(allEquipments.filter(eq => {
|
||||
const search = document.querySelector('.equipment-search');
|
||||
if (!search || !search.value) return true;
|
||||
const q = search.value.toLowerCase();
|
||||
return (eq.RESOURCENAME && eq.RESOURCENAME.toLowerCase().includes(q)) ||
|
||||
(eq.WORKCENTERNAME && eq.WORKCENTERNAME.toLowerCase().includes(q));
|
||||
}));
|
||||
}
|
||||
|
||||
// Update selected display
|
||||
function updateSelectedDisplay() {
|
||||
const display = document.getElementById('equipmentDisplay');
|
||||
const count = document.getElementById('selectedCount');
|
||||
|
||||
if (selectedEquipments.size === 0) {
|
||||
display.textContent = '點擊選擇設備...';
|
||||
count.textContent = '';
|
||||
} else if (selectedEquipments.size <= 3) {
|
||||
const names = allEquipments
|
||||
.filter(eq => selectedEquipments.has(eq.RESOURCEID))
|
||||
.map(eq => eq.RESOURCENAME)
|
||||
.join(', ');
|
||||
display.textContent = names;
|
||||
count.textContent = `已選擇 ${selectedEquipments.size} 台設備`;
|
||||
} else {
|
||||
display.textContent = `已選擇 ${selectedEquipments.size} 台設備`;
|
||||
count.textContent = '';
|
||||
}
|
||||
}
|
||||
|
||||
// Set last 90 days
|
||||
function setLast90Days() {
|
||||
const today = new Date();
|
||||
const past = new Date();
|
||||
past.setDate(today.getDate() - 90);
|
||||
|
||||
document.getElementById('dateFrom').value = past.toISOString().split('T')[0];
|
||||
document.getElementById('dateTo').value = today.toISOString().split('T')[0];
|
||||
}
|
||||
|
||||
// Validate inputs
|
||||
function validateInputs() {
|
||||
if (selectedEquipments.size === 0) {
|
||||
Toast.error('請選擇至少一台設備');
|
||||
return false;
|
||||
}
|
||||
|
||||
const dateFrom = document.getElementById('dateFrom').value;
|
||||
const dateTo = document.getElementById('dateTo').value;
|
||||
|
||||
if (!dateFrom || !dateTo) {
|
||||
Toast.error('請指定日期範圍');
|
||||
return false;
|
||||
}
|
||||
|
||||
const from = new Date(dateFrom);
|
||||
const to = new Date(dateTo);
|
||||
|
||||
if (to < from) {
|
||||
Toast.error('結束日期不可早於起始日期');
|
||||
return false;
|
||||
}
|
||||
|
||||
const daysDiff = (to - from) / (1000 * 60 * 60 * 24);
|
||||
if (daysDiff > 365) {
|
||||
Toast.error('日期範圍不可超過 365 天');
|
||||
return false;
|
||||
}
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
// Query jobs
|
||||
async function queryJobs() {
|
||||
if (!validateInputs()) return;
|
||||
|
||||
const resultSection = document.getElementById('resultSection');
|
||||
resultSection.innerHTML = `
|
||||
<div class="loading">
|
||||
<div class="loading-spinner"></div>
|
||||
<br>查詢中...
|
||||
</div>
|
||||
`;
|
||||
|
||||
document.getElementById('queryBtn').disabled = true;
|
||||
document.getElementById('exportBtn').disabled = true;
|
||||
|
||||
try {
|
||||
const data = await MesApi.post('/api/job-query/jobs', {
|
||||
resource_ids: Array.from(selectedEquipments),
|
||||
start_date: document.getElementById('dateFrom').value,
|
||||
end_date: document.getElementById('dateTo').value
|
||||
});
|
||||
|
||||
if (data.error) {
|
||||
resultSection.innerHTML = `<div class="error">${data.error}</div>`;
|
||||
return;
|
||||
}
|
||||
|
||||
jobsData = data.data;
|
||||
expandedJobs.clear();
|
||||
renderJobsTable();
|
||||
|
||||
document.getElementById('exportBtn').disabled = jobsData.length === 0;
|
||||
|
||||
} catch (error) {
|
||||
resultSection.innerHTML = `<div class="error">查詢失敗: ${error.message}</div>`;
|
||||
} finally {
|
||||
document.getElementById('queryBtn').disabled = false;
|
||||
}
|
||||
}
|
||||
|
||||
// Render jobs table
|
||||
|
||||
// Toggle equipment dropdown
|
||||
function toggleEquipmentDropdown() {
|
||||
const dropdown = document.getElementById('equipmentDropdown');
|
||||
dropdown.classList.toggle('show');
|
||||
}
|
||||
|
||||
// Filter equipments by search
|
||||
function filterEquipments(query) {
|
||||
const q = query.toLowerCase();
|
||||
const filtered = allEquipments.filter(eq =>
|
||||
(eq.RESOURCENAME && eq.RESOURCENAME.toLowerCase().includes(q)) ||
|
||||
(eq.WORKCENTERNAME && eq.WORKCENTERNAME.toLowerCase().includes(q)) ||
|
||||
(eq.RESOURCEFAMILYNAME && eq.RESOURCEFAMILYNAME.toLowerCase().includes(q))
|
||||
);
|
||||
renderEquipmentList(filtered);
|
||||
}
|
||||
|
||||
// Toggle equipment selection
|
||||
function toggleEquipment(resourceId) {
|
||||
if (selectedEquipments.has(resourceId)) {
|
||||
selectedEquipments.delete(resourceId);
|
||||
} else {
|
||||
selectedEquipments.add(resourceId);
|
||||
}
|
||||
updateSelectedDisplay();
|
||||
renderEquipmentList(allEquipments.filter(eq => {
|
||||
const search = document.querySelector('.equipment-search');
|
||||
if (!search || !search.value) return true;
|
||||
const q = search.value.toLowerCase();
|
||||
return (eq.RESOURCENAME && eq.RESOURCENAME.toLowerCase().includes(q)) ||
|
||||
(eq.WORKCENTERNAME && eq.WORKCENTERNAME.toLowerCase().includes(q));
|
||||
}));
|
||||
}
|
||||
|
||||
// Toggle entire workcenter group selection
|
||||
function toggleWorkcenterGroup(workcenterName) {
|
||||
const groupEquipments = allEquipments.filter(
|
||||
(eq) => safeText(eq.WORKCENTERNAME, '未分類') === workcenterName
|
||||
);
|
||||
const groupIds = groupEquipments.map((eq) => eq.RESOURCEID);
|
||||
const allSelected = groupIds.every((id) => selectedEquipments.has(id));
|
||||
|
||||
if (allSelected) {
|
||||
groupIds.forEach((id) => selectedEquipments.delete(id));
|
||||
} else {
|
||||
groupIds.forEach((id) => selectedEquipments.add(id));
|
||||
}
|
||||
|
||||
updateSelectedDisplay();
|
||||
renderEquipmentList(allEquipments.filter((eq) => {
|
||||
const search = document.querySelector('.equipment-search');
|
||||
if (!search || !search.value) return true;
|
||||
const q = search.value.toLowerCase();
|
||||
return (eq.RESOURCENAME && eq.RESOURCENAME.toLowerCase().includes(q)) ||
|
||||
(eq.WORKCENTERNAME && eq.WORKCENTERNAME.toLowerCase().includes(q));
|
||||
}));
|
||||
}
|
||||
|
||||
// Update selected display
|
||||
function updateSelectedDisplay() {
|
||||
const display = document.getElementById('equipmentDisplay');
|
||||
const count = document.getElementById('selectedCount');
|
||||
|
||||
if (selectedEquipments.size === 0) {
|
||||
display.textContent = '點擊選擇設備...';
|
||||
count.textContent = '';
|
||||
} else if (selectedEquipments.size <= 3) {
|
||||
const names = allEquipments
|
||||
.filter(eq => selectedEquipments.has(eq.RESOURCEID))
|
||||
.map(eq => eq.RESOURCENAME)
|
||||
.join(', ');
|
||||
display.textContent = names;
|
||||
count.textContent = `已選擇 ${selectedEquipments.size} 台設備`;
|
||||
} else {
|
||||
display.textContent = `已選擇 ${selectedEquipments.size} 台設備`;
|
||||
count.textContent = '';
|
||||
}
|
||||
}
|
||||
|
||||
// Set last 90 days
|
||||
function setLast90Days() {
|
||||
const today = new Date();
|
||||
const past = new Date();
|
||||
past.setDate(today.getDate() - 90);
|
||||
|
||||
document.getElementById('dateFrom').value = past.toISOString().split('T')[0];
|
||||
document.getElementById('dateTo').value = today.toISOString().split('T')[0];
|
||||
}
|
||||
|
||||
// Validate inputs
|
||||
function validateInputs() {
|
||||
if (selectedEquipments.size === 0) {
|
||||
Toast.error('請選擇至少一台設備');
|
||||
return false;
|
||||
}
|
||||
|
||||
const dateFrom = document.getElementById('dateFrom').value;
|
||||
const dateTo = document.getElementById('dateTo').value;
|
||||
|
||||
if (!dateFrom || !dateTo) {
|
||||
Toast.error('請指定日期範圍');
|
||||
return false;
|
||||
}
|
||||
|
||||
const from = new Date(dateFrom);
|
||||
const to = new Date(dateTo);
|
||||
|
||||
if (to < from) {
|
||||
Toast.error('結束日期不可早於起始日期');
|
||||
return false;
|
||||
}
|
||||
|
||||
const daysDiff = (to - from) / (1000 * 60 * 60 * 24);
|
||||
if (daysDiff > 365) {
|
||||
Toast.error('日期範圍不可超過 365 天');
|
||||
return false;
|
||||
}
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
// Query jobs
|
||||
async function queryJobs() {
|
||||
if (!validateInputs()) return;
|
||||
|
||||
const resultSection = document.getElementById('resultSection');
|
||||
resultSection.innerHTML = `
|
||||
<div class="loading">
|
||||
<div class="loading-spinner"></div>
|
||||
<br>查詢中...
|
||||
</div>
|
||||
`;
|
||||
|
||||
document.getElementById('queryBtn').disabled = true;
|
||||
document.getElementById('exportBtn').disabled = true;
|
||||
|
||||
try {
|
||||
const data = await MesApi.post('/api/job-query/jobs', {
|
||||
resource_ids: Array.from(selectedEquipments),
|
||||
start_date: document.getElementById('dateFrom').value,
|
||||
end_date: document.getElementById('dateTo').value
|
||||
});
|
||||
|
||||
if (data.error) {
|
||||
resultSection.innerHTML = `<div class="error">${data.error}</div>`;
|
||||
return;
|
||||
}
|
||||
|
||||
jobsData = data.data;
|
||||
expandedJobs.clear();
|
||||
renderJobsTable();
|
||||
|
||||
document.getElementById('exportBtn').disabled = jobsData.length === 0;
|
||||
|
||||
} catch (error) {
|
||||
resultSection.innerHTML = `<div class="error">查詢失敗: ${error.message}</div>`;
|
||||
} finally {
|
||||
document.getElementById('queryBtn').disabled = false;
|
||||
}
|
||||
}
|
||||
|
||||
// Render jobs table
|
||||
function renderJobsTable() {
|
||||
const resultSection = document.getElementById('resultSection');
|
||||
const jobHeaders = jobTableFields.map((field) => `<th>${escapeHtml(field.ui_label)}</th>`).join('');
|
||||
@@ -256,19 +290,19 @@ function renderTxnCell(txn, apiKey) {
|
||||
resultSection.innerHTML = `
|
||||
<div class="empty-state">
|
||||
<p>無符合條件的工單</p>
|
||||
</div>
|
||||
`;
|
||||
return;
|
||||
}
|
||||
|
||||
let html = `
|
||||
<div class="result-header">
|
||||
<div class="result-info">共 ${jobsData.length} 筆工單</div>
|
||||
<div class="result-actions">
|
||||
<button class="btn btn-secondary btn-sm" onclick="expandAll()">全部展開</button>
|
||||
<button class="btn btn-secondary btn-sm" onclick="collapseAll()">全部收合</button>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
`;
|
||||
return;
|
||||
}
|
||||
|
||||
let html = `
|
||||
<div class="result-header">
|
||||
<div class="result-info">共 ${jobsData.length} 筆工單</div>
|
||||
<div class="result-actions">
|
||||
<button class="btn btn-secondary btn-sm" onclick="expandAll()">全部展開</button>
|
||||
<button class="btn btn-secondary btn-sm" onclick="collapseAll()">全部收合</button>
|
||||
</div>
|
||||
</div>
|
||||
<div class="table-container">
|
||||
<table>
|
||||
<thead>
|
||||
@@ -300,58 +334,58 @@ function renderTxnCell(txn, apiKey) {
|
||||
${isExpanded ? '<div class="loading"><div class="loading-spinner"></div></div>' : ''}
|
||||
</div>
|
||||
</td>
|
||||
</tr>
|
||||
`;
|
||||
});
|
||||
|
||||
html += `
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
`;
|
||||
|
||||
resultSection.innerHTML = html;
|
||||
|
||||
// Load expanded histories
|
||||
expandedJobs.forEach(jobId => {
|
||||
const idx = jobsData.findIndex(j => j.JOBID === jobId);
|
||||
if (idx >= 0) loadJobHistory(jobId, idx);
|
||||
});
|
||||
}
|
||||
|
||||
// Toggle job history
|
||||
async function toggleJobHistory(jobId, idx) {
|
||||
const txnRow = document.getElementById(`txn-row-${idx}`);
|
||||
const jobRow = document.getElementById(`job-row-${idx}`);
|
||||
const arrow = jobRow.querySelector('.arrow-icon');
|
||||
|
||||
if (expandedJobs.has(jobId)) {
|
||||
expandedJobs.delete(jobId);
|
||||
txnRow.classList.remove('show');
|
||||
jobRow.classList.remove('expanded');
|
||||
arrow.classList.remove('rotated');
|
||||
} else {
|
||||
expandedJobs.add(jobId);
|
||||
txnRow.classList.add('show');
|
||||
jobRow.classList.add('expanded');
|
||||
arrow.classList.add('rotated');
|
||||
loadJobHistory(jobId, idx);
|
||||
}
|
||||
}
|
||||
|
||||
// Load job history
|
||||
async function loadJobHistory(jobId, idx) {
|
||||
const container = document.getElementById(`txn-content-${idx}`);
|
||||
container.innerHTML = '<div class="loading" style="padding: 20px;"><div class="loading-spinner"></div></div>';
|
||||
|
||||
try {
|
||||
const data = await MesApi.get(`/api/job-query/txn/${jobId}`);
|
||||
|
||||
if (data.error) {
|
||||
container.innerHTML = `<div class="error" style="margin: 10px 20px;">${data.error}</div>`;
|
||||
return;
|
||||
}
|
||||
|
||||
</tr>
|
||||
`;
|
||||
});
|
||||
|
||||
html += `
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
`;
|
||||
|
||||
resultSection.innerHTML = html;
|
||||
|
||||
// Load expanded histories
|
||||
expandedJobs.forEach(jobId => {
|
||||
const idx = jobsData.findIndex(j => j.JOBID === jobId);
|
||||
if (idx >= 0) loadJobHistory(jobId, idx);
|
||||
});
|
||||
}
|
||||
|
||||
// Toggle job history
|
||||
async function toggleJobHistory(jobId, idx) {
|
||||
const txnRow = document.getElementById(`txn-row-${idx}`);
|
||||
const jobRow = document.getElementById(`job-row-${idx}`);
|
||||
const arrow = jobRow.querySelector('.arrow-icon');
|
||||
|
||||
if (expandedJobs.has(jobId)) {
|
||||
expandedJobs.delete(jobId);
|
||||
txnRow.classList.remove('show');
|
||||
jobRow.classList.remove('expanded');
|
||||
arrow.classList.remove('rotated');
|
||||
} else {
|
||||
expandedJobs.add(jobId);
|
||||
txnRow.classList.add('show');
|
||||
jobRow.classList.add('expanded');
|
||||
arrow.classList.add('rotated');
|
||||
loadJobHistory(jobId, idx);
|
||||
}
|
||||
}
|
||||
|
||||
// Load job history
|
||||
async function loadJobHistory(jobId, idx) {
|
||||
const container = document.getElementById(`txn-content-${idx}`);
|
||||
container.innerHTML = '<div class="loading" style="padding: 20px;"><div class="loading-spinner"></div></div>';
|
||||
|
||||
try {
|
||||
const data = await MesApi.get(`/api/job-query/txn/${jobId}`);
|
||||
|
||||
if (data.error) {
|
||||
container.innerHTML = `<div class="error" style="margin: 10px 20px;">${data.error}</div>`;
|
||||
return;
|
||||
}
|
||||
|
||||
if (!data.data || data.data.length === 0) {
|
||||
container.innerHTML = '<div style="padding: 20px; color: #666;">無交易歷史記錄</div>';
|
||||
return;
|
||||
@@ -378,80 +412,80 @@ function renderTxnCell(txn, apiKey) {
|
||||
</tr>
|
||||
`;
|
||||
});
|
||||
|
||||
html += '</tbody></table>';
|
||||
container.innerHTML = html;
|
||||
|
||||
} catch (error) {
|
||||
container.innerHTML = `<div class="error" style="margin: 10px 20px;">載入失敗: ${error.message}</div>`;
|
||||
}
|
||||
}
|
||||
|
||||
// Expand all
|
||||
function expandAll() {
|
||||
jobsData.forEach((job, idx) => {
|
||||
if (!expandedJobs.has(job.JOBID)) {
|
||||
expandedJobs.add(job.JOBID);
|
||||
}
|
||||
});
|
||||
renderJobsTable();
|
||||
}
|
||||
|
||||
// Collapse all
|
||||
function collapseAll() {
|
||||
expandedJobs.clear();
|
||||
renderJobsTable();
|
||||
}
|
||||
|
||||
// Export CSV
|
||||
async function exportCsv() {
|
||||
if (!validateInputs()) return;
|
||||
|
||||
document.getElementById('exportBtn').disabled = true;
|
||||
document.getElementById('exportBtn').textContent = '匯出中...';
|
||||
|
||||
try {
|
||||
const response = await fetch('/api/job-query/export', {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify({
|
||||
resource_ids: Array.from(selectedEquipments),
|
||||
start_date: document.getElementById('dateFrom').value,
|
||||
end_date: document.getElementById('dateTo').value
|
||||
})
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
const data = await response.json();
|
||||
throw new Error(data.error || '匯出失敗');
|
||||
}
|
||||
|
||||
// Download file
|
||||
const blob = await response.blob();
|
||||
const url = window.URL.createObjectURL(blob);
|
||||
const a = document.createElement('a');
|
||||
a.href = url;
|
||||
a.download = `job_history_${document.getElementById('dateFrom').value}_${document.getElementById('dateTo').value}.csv`;
|
||||
document.body.appendChild(a);
|
||||
a.click();
|
||||
document.body.removeChild(a);
|
||||
window.URL.revokeObjectURL(url);
|
||||
|
||||
Toast.success('CSV 匯出完成');
|
||||
|
||||
} catch (error) {
|
||||
Toast.error('匯出失敗: ' + error.message);
|
||||
} finally {
|
||||
document.getElementById('exportBtn').disabled = false;
|
||||
document.getElementById('exportBtn').textContent = '匯出 CSV';
|
||||
}
|
||||
}
|
||||
|
||||
// Format date
|
||||
function formatDate(dateStr) {
|
||||
if (!dateStr) return '';
|
||||
return dateStr.replace('T', ' ').substring(0, 19);
|
||||
}
|
||||
|
||||
html += '</tbody></table>';
|
||||
container.innerHTML = html;
|
||||
|
||||
} catch (error) {
|
||||
container.innerHTML = `<div class="error" style="margin: 10px 20px;">載入失敗: ${error.message}</div>`;
|
||||
}
|
||||
}
|
||||
|
||||
// Expand all
|
||||
function expandAll() {
|
||||
jobsData.forEach((job, idx) => {
|
||||
if (!expandedJobs.has(job.JOBID)) {
|
||||
expandedJobs.add(job.JOBID);
|
||||
}
|
||||
});
|
||||
renderJobsTable();
|
||||
}
|
||||
|
||||
// Collapse all
|
||||
function collapseAll() {
|
||||
expandedJobs.clear();
|
||||
renderJobsTable();
|
||||
}
|
||||
|
||||
// Export CSV
|
||||
async function exportCsv() {
|
||||
if (!validateInputs()) return;
|
||||
|
||||
document.getElementById('exportBtn').disabled = true;
|
||||
document.getElementById('exportBtn').textContent = '匯出中...';
|
||||
|
||||
try {
|
||||
const response = await fetch('/api/job-query/export', {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify({
|
||||
resource_ids: Array.from(selectedEquipments),
|
||||
start_date: document.getElementById('dateFrom').value,
|
||||
end_date: document.getElementById('dateTo').value
|
||||
})
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
const data = await response.json();
|
||||
throw new Error(data.error || '匯出失敗');
|
||||
}
|
||||
|
||||
// Download file
|
||||
const blob = await response.blob();
|
||||
const url = window.URL.createObjectURL(blob);
|
||||
const a = document.createElement('a');
|
||||
a.href = url;
|
||||
a.download = `job_history_${document.getElementById('dateFrom').value}_${document.getElementById('dateTo').value}.csv`;
|
||||
document.body.appendChild(a);
|
||||
a.click();
|
||||
document.body.removeChild(a);
|
||||
window.URL.revokeObjectURL(url);
|
||||
|
||||
Toast.success('CSV 匯出完成');
|
||||
|
||||
} catch (error) {
|
||||
Toast.error('匯出失敗: ' + error.message);
|
||||
} finally {
|
||||
document.getElementById('exportBtn').disabled = false;
|
||||
document.getElementById('exportBtn').textContent = '匯出 CSV';
|
||||
}
|
||||
}
|
||||
|
||||
// Format date
|
||||
function formatDate(dateStr) {
|
||||
if (!dateStr) return '';
|
||||
return dateStr.replace('T', ' ').substring(0, 19);
|
||||
}
|
||||
|
||||
|
||||
Object.assign(window, {
|
||||
@@ -460,6 +494,7 @@ renderEquipmentList,
|
||||
toggleEquipmentDropdown,
|
||||
filterEquipments,
|
||||
toggleEquipment,
|
||||
toggleWorkcenterGroup,
|
||||
updateSelectedDisplay,
|
||||
setLast90Days,
|
||||
validateInputs,
|
||||
|
||||
@@ -15,11 +15,16 @@ ensureMesApiAvailable();
|
||||
const API_TIMEOUT = 120000; // 2min (genealogy can be slow)
|
||||
const PAGE_SIZE = 200;
|
||||
|
||||
const filters = reactive({
|
||||
startDate: '',
|
||||
endDate: '',
|
||||
lossReasons: [],
|
||||
});
|
||||
const filters = reactive({
|
||||
startDate: '',
|
||||
endDate: '',
|
||||
lossReasons: [],
|
||||
});
|
||||
const committedFilters = ref({
|
||||
startDate: '',
|
||||
endDate: '',
|
||||
lossReasons: [],
|
||||
});
|
||||
|
||||
const availableLossReasons = ref([]);
|
||||
|
||||
@@ -71,16 +76,25 @@ function unwrapApiResult(result, fallbackMessage) {
|
||||
throw new Error(result?.error || fallbackMessage);
|
||||
}
|
||||
|
||||
function buildFilterParams() {
|
||||
const params = {
|
||||
start_date: filters.startDate,
|
||||
end_date: filters.endDate,
|
||||
};
|
||||
if (filters.lossReasons.length) {
|
||||
params.loss_reasons = filters.lossReasons.join(',');
|
||||
}
|
||||
return params;
|
||||
}
|
||||
function buildFilterParams() {
|
||||
const snapshot = committedFilters.value;
|
||||
const params = {
|
||||
start_date: snapshot.startDate,
|
||||
end_date: snapshot.endDate,
|
||||
};
|
||||
if (snapshot.lossReasons.length) {
|
||||
params.loss_reasons = snapshot.lossReasons.join(',');
|
||||
}
|
||||
return params;
|
||||
}
|
||||
|
||||
function snapshotFilters() {
|
||||
committedFilters.value = {
|
||||
startDate: filters.startDate,
|
||||
endDate: filters.endDate,
|
||||
lossReasons: [...filters.lossReasons],
|
||||
};
|
||||
}
|
||||
|
||||
async function loadLossReasons() {
|
||||
try {
|
||||
@@ -92,46 +106,52 @@ async function loadLossReasons() {
|
||||
}
|
||||
}
|
||||
|
||||
async function loadDetail(page = 1) {
|
||||
detailLoading.value = true;
|
||||
try {
|
||||
const params = {
|
||||
...buildFilterParams(),
|
||||
page,
|
||||
page_size: PAGE_SIZE,
|
||||
};
|
||||
const result = await apiGet('/api/mid-section-defect/analysis/detail', {
|
||||
params,
|
||||
timeout: API_TIMEOUT,
|
||||
});
|
||||
async function loadDetail(page = 1, signal = null) {
|
||||
detailLoading.value = true;
|
||||
try {
|
||||
const params = {
|
||||
...buildFilterParams(),
|
||||
page,
|
||||
page_size: PAGE_SIZE,
|
||||
};
|
||||
const result = await apiGet('/api/mid-section-defect/analysis/detail', {
|
||||
params,
|
||||
timeout: API_TIMEOUT,
|
||||
signal,
|
||||
});
|
||||
const unwrapped = unwrapApiResult(result, '載入明細失敗');
|
||||
detailData.value = unwrapped.data?.detail || [];
|
||||
detailPagination.value = unwrapped.data?.pagination || {
|
||||
page: 1, page_size: PAGE_SIZE, total_count: 0, total_pages: 1,
|
||||
};
|
||||
} catch (err) {
|
||||
console.error('Detail load failed:', err.message);
|
||||
detailData.value = [];
|
||||
} finally {
|
||||
detailLoading.value = false;
|
||||
}
|
||||
} catch (err) {
|
||||
if (err?.name === 'AbortError') {
|
||||
return;
|
||||
}
|
||||
console.error('Detail load failed:', err.message);
|
||||
detailData.value = [];
|
||||
} finally {
|
||||
detailLoading.value = false;
|
||||
}
|
||||
}
|
||||
|
||||
async function loadAnalysis() {
|
||||
queryError.value = '';
|
||||
loading.querying = true;
|
||||
|
||||
try {
|
||||
const params = buildFilterParams();
|
||||
|
||||
// Fire summary and detail page 1 in parallel
|
||||
const [summaryResult] = await Promise.all([
|
||||
apiGet('/api/mid-section-defect/analysis', {
|
||||
params,
|
||||
timeout: API_TIMEOUT,
|
||||
}),
|
||||
loadDetail(1),
|
||||
]);
|
||||
async function loadAnalysis() {
|
||||
queryError.value = '';
|
||||
loading.querying = true;
|
||||
const signal = createAbortSignal('msd-analysis');
|
||||
|
||||
try {
|
||||
const params = buildFilterParams();
|
||||
|
||||
// Fire summary and detail page 1 in parallel
|
||||
const [summaryResult] = await Promise.all([
|
||||
apiGet('/api/mid-section-defect/analysis', {
|
||||
params,
|
||||
timeout: API_TIMEOUT,
|
||||
signal,
|
||||
}),
|
||||
loadDetail(1, signal),
|
||||
]);
|
||||
|
||||
const unwrapped = unwrapApiResult(summaryResult, '查詢失敗');
|
||||
analysisData.value = unwrapped.data;
|
||||
@@ -142,60 +162,66 @@ async function loadAnalysis() {
|
||||
autoRefreshStarted = true;
|
||||
startAutoRefresh();
|
||||
}
|
||||
} catch (err) {
|
||||
queryError.value = err.message || '查詢失敗，請稍後再試';
|
||||
} finally {
|
||||
loading.querying = false;
|
||||
}
|
||||
}
|
||||
} catch (err) {
|
||||
if (err?.name === 'AbortError') {
|
||||
return;
|
||||
}
|
||||
queryError.value = err.message || '查詢失敗，請稍後再試';
|
||||
} finally {
|
||||
loading.querying = false;
|
||||
}
|
||||
}
|
||||
|
||||
function handleUpdateFilters(updated) {
|
||||
Object.assign(filters, updated);
|
||||
}
|
||||
|
||||
function handleQuery() {
|
||||
loadAnalysis();
|
||||
}
|
||||
|
||||
function prevPage() {
|
||||
if (detailPagination.value.page <= 1) return;
|
||||
loadDetail(detailPagination.value.page - 1);
|
||||
}
|
||||
|
||||
function nextPage() {
|
||||
if (detailPagination.value.page >= detailPagination.value.total_pages) return;
|
||||
loadDetail(detailPagination.value.page + 1);
|
||||
}
|
||||
|
||||
function exportCsv() {
|
||||
const params = new URLSearchParams({
|
||||
start_date: filters.startDate,
|
||||
end_date: filters.endDate,
|
||||
});
|
||||
if (filters.lossReasons.length) {
|
||||
params.set('loss_reasons', filters.lossReasons.join(','));
|
||||
}
|
||||
|
||||
const link = document.createElement('a');
|
||||
link.href = `/api/mid-section-defect/export?${params}`;
|
||||
link.download = `mid_section_defect_${filters.startDate}_to_${filters.endDate}.csv`;
|
||||
document.body.appendChild(link);
|
||||
link.click();
|
||||
document.body.removeChild(link);
|
||||
}
|
||||
|
||||
let autoRefreshStarted = false;
|
||||
const { startAutoRefresh } = useAutoRefresh({
|
||||
onRefresh: () => loadAnalysis(),
|
||||
intervalMs: 5 * 60 * 1000,
|
||||
autoStart: false,
|
||||
refreshOnVisible: true,
|
||||
});
|
||||
|
||||
function initPage() {
|
||||
setDefaultDates();
|
||||
loadLossReasons();
|
||||
}
|
||||
function handleQuery() {
|
||||
snapshotFilters();
|
||||
loadAnalysis();
|
||||
}
|
||||
|
||||
function prevPage() {
|
||||
if (detailPagination.value.page <= 1) return;
|
||||
loadDetail(detailPagination.value.page - 1, createAbortSignal('msd-detail'));
|
||||
}
|
||||
|
||||
function nextPage() {
|
||||
if (detailPagination.value.page >= detailPagination.value.total_pages) return;
|
||||
loadDetail(detailPagination.value.page + 1, createAbortSignal('msd-detail'));
|
||||
}
|
||||
|
||||
function exportCsv() {
|
||||
const snapshot = committedFilters.value;
|
||||
const params = new URLSearchParams({
|
||||
start_date: snapshot.startDate,
|
||||
end_date: snapshot.endDate,
|
||||
});
|
||||
if (snapshot.lossReasons.length) {
|
||||
params.set('loss_reasons', snapshot.lossReasons.join(','));
|
||||
}
|
||||
|
||||
const link = document.createElement('a');
|
||||
link.href = `/api/mid-section-defect/export?${params}`;
|
||||
link.download = `mid_section_defect_${snapshot.startDate}_to_${snapshot.endDate}.csv`;
|
||||
document.body.appendChild(link);
|
||||
link.click();
|
||||
document.body.removeChild(link);
|
||||
}
|
||||
|
||||
let autoRefreshStarted = false;
|
||||
const { createAbortSignal, startAutoRefresh } = useAutoRefresh({
|
||||
onRefresh: () => loadAnalysis(),
|
||||
intervalMs: 5 * 60 * 1000,
|
||||
autoStart: false,
|
||||
refreshOnVisible: true,
|
||||
});
|
||||
|
||||
function initPage() {
|
||||
setDefaultDates();
|
||||
snapshotFilters();
|
||||
loadLossReasons();
|
||||
}
|
||||
|
||||
void initPage();
|
||||
</script>
|
||||
|
||||
@@ -0,0 +1,2 @@
|
||||
schema: spec-driven
|
||||
created: 2026-02-10
|
||||
@@ -0,0 +1,61 @@
|
||||
## Context
|
||||
|
||||
`/mid-section-defect` 頁面已上線，功能完整但缺乏生產環境保護機制。Code review 揭示 6 個問題，依嚴重度分為 P0-P3。現有基礎建設（`try_acquire_lock`、`configured_rate_limit`、`createAbortSignal`）均可直接複用，無需新增框架。
|
||||
|
||||
**現有架構**：
|
||||
- Backend: `query_analysis()` (line 82-184) 含 5min Redis 快取 → `query_analysis_detail()` (line 187-224) 呼叫前者取快取結果再分頁
|
||||
- Frontend: `Promise.all([summary, detail])` 平行載入 → `useAutoRefresh` 5min 自動刷新
|
||||
- 上游歷史: SQL 查全量 → Python `get_workcenter_group()` 逐行分類 + order 4-11 過濾
|
||||
|
||||
## Goals / Non-Goals
|
||||
|
||||
**Goals:**
|
||||
- 消除首次查詢的雙倍 Oracle 管線執行（P0）
|
||||
- 保護高成本路由免受暴衝流量（P1a）
|
||||
- 確保 UI 篩選變更不會汙染進行中的 API 呼叫（P1b）
|
||||
- 新查詢自動取消舊的進行中請求（P2a）
|
||||
- 善用 Oracle Server 做 workcenter 分類，支援全線歷程追蹤（P2b）
|
||||
- 基礎測試覆蓋防止回歸（P3）
|
||||
|
||||
**Non-Goals:**
|
||||
- 不改變 API response 格式
|
||||
- 不重構 `query_analysis()` 管線邏輯
|
||||
- 不加入前端 UI 新功能
|
||||
- 不處理 `export_csv()` 的串流效能（目前可接受）
|
||||
- 不做 DuckDB 中間層或背景預計算
|
||||
|
||||
## Decisions
|
||||
|
||||
### D1: 分散式鎖策略 — Redis SET NX 輪詢等待
|
||||
|
||||
**選擇**: 使用既有 `try_acquire_lock()` + 輪詢 `cache_get()` 等待模式。
|
||||
**替代方案**: (A) Pub/Sub 通知 — 複雜度高，需新增 channel 管理；(B) 前端序列化 — 改 `Promise.all` 為先 summary 再 detail，但仍有自動刷新與手動查詢並行問題。
|
||||
**理由**: 鎖機制在 service 層統一保護所有入口（包含未來新路由），fail-open 設計確保 Redis 故障不阻塞。輪詢 0.5s 間隔在 5-35s 典型管線執行時間下損耗可忽略。
|
||||
|
||||
### D2: Rate limit 預設值 — 依路由成本分級
|
||||
|
||||
**選擇**: `/analysis` 6/60s、`/detail` 15/60s、`/export` 3/60s。
|
||||
**理由**: `/analysis` 冷查詢 35s，每分鐘最多 6 次已足夠（含自動刷新）。`/detail` 分頁翻頁頻率高但走快取，15 次寬裕。`/export` 觸發全量串流，3 次防誤操作。`/loss-reasons` 已有 24h 快取，無需限速。
|
||||
|
||||
### D3: 篩選分離 — committedFilters ref 快照
|
||||
|
||||
**選擇**: 新增 `committedFilters` ref，按「查詢」時從 `filters` reactive 快照。所有 API 函式讀 `committedFilters`。
|
||||
**替代方案**: (A) deep watch + debounce — 會在使用者輸入中途觸發查詢；(B) URL params 持久化 — 此頁面不需要書籤分享功能。
|
||||
**理由**: 最小改動，與 `resource-history/App.vue` 的 `buildQueryString()` 模式一致。`filters` reactive 繼續作為 UI 雙向繫結，`committedFilters` 是「上次查詢使用的參數」。
|
||||
|
||||
### D4: AbortController — keyed signal 設計
|
||||
|
||||
**選擇**: `'msd-analysis'` key 用於查詢（summary + detail page 1 共用），`'msd-detail'` key 用於獨立翻頁。
|
||||
**理由**: 新查詢取消舊查詢的所有請求（含翻頁中的 detail），翻頁取消前一次翻頁但不影響進行中的查詢。與 `wip-detail/App.vue` 相同模式。
|
||||
|
||||
### D5: 上游歷史 SQL 端分類 — CASE WHEN 全線保留
|
||||
|
||||
**選擇**: SQL CTE 內加 `CASE WHEN` 將 `WORKCENTERNAME` 分類為 `WORKCENTER_GROUP`（12 組 + NULL fallback），Python 端直接讀取分類結果，不過濾任何站點。
|
||||
**替代方案**: (A) Oracle 自訂函式 — 需 DBA 部署；(B) 維持 Python 端分類但移除過濾 — 仍有 10K+ 行逐行 regex 開銷。
|
||||
**理由**: CASE WHEN 在 Oracle 查詢引擎內原生執行，無 row-by-row function call 開銷。分類邏輯與 `workcenter_groups.py` 的 patterns 完全對齊，但需注意 CASE 順序（exclude-first: `元件切割` 在 `切割` 之前）。
|
||||
|
||||
## Risks / Trade-offs
|
||||
|
||||
- **[P0 鎖等待超時]** 若管線執行 >90s（極大日期範圍），等待方可能超時後自行查詢 → 緩解：API_TIMEOUT 本身 120s，鎖 TTL 120s 會自動釋放，最壞情況退化為當前行為（雙查詢）
|
||||
- **[P2b SQL 分類與 Python 不一致]** 若 `workcenter_groups.py` 新增/修改 pattern 但忘記同步 SQL → 緩解：SQL 的 NULL fallback 確保不會遺失行，僅分類名稱可能為 NULL
|
||||
- **[Rate limit 誤擋]** 高頻翻頁或自動刷新可能觸發限速 → 緩解：`/detail` 15/60s 已足夠正常翻頁（每 4s 一頁），自動刷新 5min 間隔遠低於 `/analysis` 6/60s 門檻
|
||||
@@ -0,0 +1,31 @@
|
||||
## Why
|
||||
|
||||
Code review 發現中段製程不良追溯分析（`/mid-section-defect`）有 6 個問題：首次查詢觸發雙倍 Oracle 管線（P0）、高成本路由無節流（P1a）、篩選與查詢狀態耦合（P1b）、無請求取消機制（P2a）、上游歷史 workcenter 分類在 Python 端逐行計算而非善用 DB Server（P2b）、零測試覆蓋（P3）。需在功能穩定後立即修復，防止 DB 過載與前端競態問題。
|
||||
|
||||
## What Changes
|
||||
|
||||
- **P0 分散式鎖**：`query_analysis()` 加入 `try_acquire_lock` / `release_lock` 包裹計算區段，第二個平行請求等待快取而非重跑管線
|
||||
- **P1a 路由限速**：`/analysis`（6/60s）、`/analysis/detail`（15/60s）、`/export`（3/60s）加入 `configured_rate_limit` decorator
|
||||
- **P1b 篩選分離**：新增 `committedFilters` ref，所有 API 呼叫（翻頁/自動刷新/匯出）讀取已提交的篩選快照
|
||||
- **P2a 請求取消**：`loadAnalysis()` 和 `loadDetail()` 加入 `createAbortSignal(key)` keyed abort，新查詢自動取消舊請求
|
||||
- **P2b SQL 端分類**：上游歷史 SQL 加入 `CASE WHEN` workcenter group 分類（全線歷程不排除任何站點），移除 Python 端 `get_workcenter_group()` 逐行呼叫與 order 4-11 過濾
|
||||
- **P3 測試覆蓋**：新增 `test_mid_section_defect_routes.py`（9 個測試）和 `test_mid_section_defect_service.py`（9 個測試）
|
||||
|
||||
## Capabilities
|
||||
|
||||
### New Capabilities
|
||||
|
||||
（無新增能力，本次為既有功能的強化修復）
|
||||
|
||||
### Modified Capabilities
|
||||
|
||||
- `api-safety-hygiene`: 新增 mid-section-defect 3 個路由的 rate limit 與分散式鎖機制
|
||||
- `vue-vite-page-architecture`: mid-section-defect 前端加入 committedFilters 篩選分離與 AbortController 請求取消
|
||||
|
||||
## Impact
|
||||
|
||||
- **Backend**: `mid_section_defect_service.py`（分散式鎖 + 移除 Python 端 workcenter 過濾）、`mid_section_defect_routes.py`（rate limit）、`upstream_history.sql`（CASE WHEN 分類）
|
||||
- **Frontend**: `mid-section-defect/App.vue`（committedFilters + abort signal）
|
||||
- **Tests**: 2 個新測試檔案（`test_mid_section_defect_routes.py`、`test_mid_section_defect_service.py`）
|
||||
- **API 行為變更**: 超過限速門檻回傳 429；上游歷史回傳含 `WORKCENTER_GROUP` 欄位（但 API response 格式不變，分類邏輯內部調整）
|
||||
- **無破壞性變更**: API response 結構、快取 key、前端元件介面均不變
|
||||
@@ -0,0 +1,73 @@
|
||||
## ADDED Requirements
|
||||
|
||||
### Requirement: Mid-section defect analysis endpoints SHALL apply distributed lock to prevent duplicate pipeline execution
|
||||
The `/api/mid-section-defect/analysis` pipeline SHALL use a Redis distributed lock to prevent concurrent identical queries from executing the full Oracle pipeline in parallel.
|
||||
|
||||
#### Scenario: Two parallel requests with cold cache
|
||||
- **WHEN** two requests with identical parameters arrive simultaneously and no cache exists
|
||||
- **THEN** the first request SHALL acquire the lock and execute the full pipeline
|
||||
- **THEN** the second request SHALL wait by polling the cache until the first request completes
|
||||
- **THEN** only ONE full Oracle pipeline execution SHALL occur
|
||||
|
||||
#### Scenario: Lock wait timeout
|
||||
- **WHEN** a waiting request does not see a cache result within 90 seconds
|
||||
- **THEN** the request SHALL proceed with its own pipeline execution (fail-open)
|
||||
|
||||
#### Scenario: Redis unavailable
|
||||
- **WHEN** Redis is unavailable during lock acquisition
|
||||
- **THEN** the lock function SHALL return acquired=true (fail-open)
|
||||
- **THEN** the request SHALL proceed normally without blocking
|
||||
|
||||
#### Scenario: Pipeline exception with lock held
|
||||
- **WHEN** the pipeline throws an exception while the lock is held
|
||||
- **THEN** the lock SHALL be released in a finally block
|
||||
- **THEN** subsequent requests SHALL NOT be blocked by a stale lock
|
||||
|
||||
### Requirement: Mid-section defect routes SHALL apply rate limiting
|
||||
The `/analysis`, `/analysis/detail`, and `/export` endpoints SHALL apply per-client rate limiting using the existing `configured_rate_limit` mechanism.
|
||||
|
||||
#### Scenario: Analysis endpoint rate limit exceeded
|
||||
- **WHEN** a client sends more than 6 requests to `/api/mid-section-defect/analysis` within 60 seconds
|
||||
- **THEN** the endpoint SHALL return HTTP 429 with a `Retry-After` header
|
||||
- **THEN** the service function SHALL NOT be called
|
||||
|
||||
#### Scenario: Detail endpoint rate limit exceeded
|
||||
- **WHEN** a client sends more than 15 requests to `/api/mid-section-defect/analysis/detail` within 60 seconds
|
||||
- **THEN** the endpoint SHALL return HTTP 429 with a `Retry-After` header
|
||||
|
||||
#### Scenario: Export endpoint rate limit exceeded
|
||||
- **WHEN** a client sends more than 3 requests to `/api/mid-section-defect/export` within 60 seconds
|
||||
- **THEN** the endpoint SHALL return HTTP 429 with a `Retry-After` header
|
||||
|
||||
#### Scenario: Loss reasons endpoint not rate limited
|
||||
- **WHEN** a client sends requests to `/api/mid-section-defect/loss-reasons`
|
||||
- **THEN** no rate limiting SHALL be applied (endpoint is lightweight with 24h cache)
|
||||
|
||||
### Requirement: Mid-section defect upstream history SHALL classify workcenters in SQL
|
||||
The upstream history SQL query SHALL classify `WORKCENTERNAME` into workcenter groups using Oracle `CASE WHEN` expressions, returning the full production line history without excluding any stations.
|
||||
|
||||
#### Scenario: Workcenter group classification in SQL
|
||||
- **WHEN** the upstream history query executes
|
||||
- **THEN** each row SHALL include a `WORKCENTER_GROUP` column derived from `CASE WHEN` pattern matching
|
||||
- **THEN** the classification SHALL match the patterns defined in `workcenter_groups.py`
|
||||
|
||||
#### Scenario: Unknown workcenter name
|
||||
- **WHEN** a `WORKCENTERNAME` does not match any known pattern
|
||||
- **THEN** `WORKCENTER_GROUP` SHALL be NULL
|
||||
- **THEN** the row SHALL still be included in the result (not filtered out)
|
||||
|
||||
#### Scenario: Full production line retention
|
||||
- **WHEN** the upstream history is fetched for ancestor CIDs
|
||||
- **THEN** ALL stations SHALL be included (cutting, welding, mid-section, testing)
|
||||
- **THEN** no order-based filtering SHALL be applied
|
||||
|
||||
### Requirement: Mid-section defect routes and service SHALL have test coverage
|
||||
Route and service test files SHALL exist and cover core behaviors.
|
||||
|
||||
#### Scenario: Route tests exist
|
||||
- **WHEN** pytest discovers tests
|
||||
- **THEN** `tests/test_mid_section_defect_routes.py` SHALL contain tests for success, parameter validation (400), service failure (500), and rate limiting (429)
|
||||
|
||||
#### Scenario: Service tests exist
|
||||
- **WHEN** pytest discovers tests
|
||||
- **THEN** `tests/test_mid_section_defect_service.py` SHALL contain tests for date validation, pagination logic, and loss reasons caching
|
||||
@@ -0,0 +1,37 @@
|
||||
## ADDED Requirements
|
||||
|
||||
### Requirement: Mid-section defect page SHALL separate filter state from query state
|
||||
The mid-section defect page SHALL maintain separate reactive state for UI input (`filters`) and committed query parameters (`committedFilters`).
|
||||
|
||||
#### Scenario: User changes date without clicking query
|
||||
- **WHEN** user modifies the date range in the filter bar but does not click "查詢"
|
||||
- **THEN** auto-refresh, pagination, and CSV export SHALL continue using the previously committed filter values
|
||||
- **THEN** the new date range SHALL NOT affect any API calls until "查詢" is clicked
|
||||
|
||||
#### Scenario: User clicks query button
|
||||
- **WHEN** user clicks "查詢"
|
||||
- **THEN** the current `filters` state SHALL be snapshotted into `committedFilters`
|
||||
- **THEN** all subsequent API calls SHALL use the committed values
|
||||
|
||||
#### Scenario: CSV export uses committed filters
|
||||
- **WHEN** user clicks "匯出 CSV" after modifying filters without re-querying
|
||||
- **THEN** the export SHALL use the committed filter values from the last query
|
||||
- **THEN** the export SHALL NOT use the current UI filter values
|
||||
|
||||
### Requirement: Mid-section defect page SHALL cancel in-flight requests on new query
|
||||
The mid-section defect page SHALL use `AbortController` to cancel in-flight API requests when a new query is initiated.
|
||||
|
||||
#### Scenario: New query cancels previous query
|
||||
- **WHEN** user clicks "查詢" while a previous query is still in-flight
|
||||
- **THEN** the previous query's summary and detail requests SHALL be aborted
|
||||
- **THEN** the AbortError SHALL be handled silently (no error banner shown)
|
||||
|
||||
#### Scenario: Page navigation cancels previous detail request
|
||||
- **WHEN** user clicks next page while a previous page request is still in-flight
|
||||
- **THEN** the previous page request SHALL be aborted
|
||||
- **THEN** the new page request SHALL proceed independently
|
||||
|
||||
#### Scenario: Query and pagination use independent abort keys
|
||||
- **WHEN** a query is in-flight and user triggers pagination
|
||||
- **THEN** the query SHALL NOT be cancelled by the pagination request
|
||||
- **THEN** the pagination SHALL use a separate abort key from the query
|
||||
@@ -0,0 +1,35 @@
|
||||
## 1. P0 — 分散式鎖防止重複管線執行
|
||||
|
||||
- [x] 1.1 在 `mid_section_defect_service.py` 的 `query_analysis()` cache miss 後加入 `try_acquire_lock` / `release_lock` 包裹計算區段
|
||||
- [x] 1.2 實作 lock-or-wait 邏輯：未取得鎖時輪詢 `cache_get()` 每 0.5s，最多 90s，超時 fail-open
|
||||
- [x] 1.3 在 `finally` 區塊確保鎖釋放，取得鎖後再做 double-check cache
|
||||
|
||||
## 2. P1a — 高成本路由限速
|
||||
|
||||
- [x] 2.1 在 `mid_section_defect_routes.py` import `configured_rate_limit` 並建立 3 個限速器（analysis 6/60s、detail 15/60s、export 3/60s）
|
||||
- [x] 2.2 將限速 decorator 套用到 `/analysis`、`/analysis/detail`、`/export` 三個路由
|
||||
|
||||
## 3. P1b + P2a — 前端篩選分離與請求取消
|
||||
|
||||
- [x] 3.1 在 `App.vue` 新增 `committedFilters` ref，`handleQuery()` 時從 `filters` 快照
|
||||
- [x] 3.2 修改 `buildFilterParams()` 和 `exportCsv()` 讀取 `committedFilters` 而非 `filters`
|
||||
- [x] 3.3 `initPage()` 設定預設日期後同步快照到 `committedFilters`
|
||||
- [x] 3.4 從 `useAutoRefresh` 解構 `createAbortSignal`，在 `loadAnalysis()` 加入 `'msd-analysis'` signal
|
||||
- [x] 3.5 `loadDetail()` 接受外部 signal 參數，獨立翻頁時使用 `'msd-detail'` key
|
||||
- [x] 3.6 `loadAnalysis()` 和 `loadDetail()` catch 區塊靜默處理 `AbortError`
|
||||
|
||||
## 4. P2b — 上游歷史 SQL 端分類
|
||||
|
||||
- [x] 4.1 修改 `upstream_history.sql` CTE 加入 `CASE WHEN` 將 `WORKCENTERNAME` 分類為 `WORKCENTER_GROUP`（12 組 + NULL fallback）
|
||||
- [x] 4.2 確保 CASE 順序正確（`元件切割`/`PKG_SAW` 在 `切割` 之前）
|
||||
- [x] 4.3 修改 `_fetch_upstream_history()` 讀取 SQL 回傳的 `WORKCENTER_GROUP` 欄位，移除 `get_workcenter_group()` 逐行呼叫與 order 4-11 過濾
|
||||
|
||||
## 5. P3 — 測試覆蓋
|
||||
|
||||
- [x] 5.1 建立 `tests/test_mid_section_defect_routes.py`：success、400 參數驗證、500 service 失敗、429 rate limit（共 9 個測試）
|
||||
- [x] 5.2 建立 `tests/test_mid_section_defect_service.py`：日期驗證、分頁邏輯、loss reasons 快取（共 9 個測試）
|
||||
|
||||
## 6. 驗證
|
||||
|
||||
- [x] 6.1 `npm run build` 前端建置通過
|
||||
- [x] 6.2 `pytest tests/test_mid_section_defect_routes.py tests/test_mid_section_defect_service.py -v` 全部通過
|
||||
@@ -31,3 +31,75 @@ Boolean query parsing in routes SHALL use shared helper behavior.
|
||||
- **WHEN** routes parse common boolean query parameters
|
||||
- **THEN** parsing behavior MUST be consistent across routes via shared utility
|
||||
|
||||
### Requirement: Mid-section defect analysis endpoints SHALL apply distributed lock to prevent duplicate pipeline execution
|
||||
The `/api/mid-section-defect/analysis` pipeline SHALL use a Redis distributed lock to prevent concurrent identical queries from executing the full Oracle pipeline in parallel.
|
||||
|
||||
#### Scenario: Two parallel requests with cold cache
|
||||
- **WHEN** two requests with identical parameters arrive simultaneously and no cache exists
|
||||
- **THEN** the first request SHALL acquire the lock and execute the full pipeline
|
||||
- **THEN** the second request SHALL wait by polling the cache until the first request completes
|
||||
- **THEN** only ONE full Oracle pipeline execution SHALL occur
|
||||
|
||||
#### Scenario: Lock wait timeout
|
||||
- **WHEN** a waiting request does not see a cache result within 90 seconds
|
||||
- **THEN** the request SHALL proceed with its own pipeline execution (fail-open)
|
||||
|
||||
#### Scenario: Redis unavailable
|
||||
- **WHEN** Redis is unavailable during lock acquisition
|
||||
- **THEN** the lock function SHALL return acquired=true (fail-open)
|
||||
- **THEN** the request SHALL proceed normally without blocking
|
||||
|
||||
#### Scenario: Pipeline exception with lock held
|
||||
- **WHEN** the pipeline throws an exception while the lock is held
|
||||
- **THEN** the lock SHALL be released in a finally block
|
||||
- **THEN** subsequent requests SHALL NOT be blocked by a stale lock
|
||||
|
||||
### Requirement: Mid-section defect routes SHALL apply rate limiting
|
||||
The `/analysis`, `/analysis/detail`, and `/export` endpoints SHALL apply per-client rate limiting using the existing `configured_rate_limit` mechanism.
|
||||
|
||||
#### Scenario: Analysis endpoint rate limit exceeded
|
||||
- **WHEN** a client sends more than 6 requests to `/api/mid-section-defect/analysis` within 60 seconds
|
||||
- **THEN** the endpoint SHALL return HTTP 429 with a `Retry-After` header
|
||||
- **THEN** the service function SHALL NOT be called
|
||||
|
||||
#### Scenario: Detail endpoint rate limit exceeded
|
||||
- **WHEN** a client sends more than 15 requests to `/api/mid-section-defect/analysis/detail` within 60 seconds
|
||||
- **THEN** the endpoint SHALL return HTTP 429 with a `Retry-After` header
|
||||
|
||||
#### Scenario: Export endpoint rate limit exceeded
|
||||
- **WHEN** a client sends more than 3 requests to `/api/mid-section-defect/export` within 60 seconds
|
||||
- **THEN** the endpoint SHALL return HTTP 429 with a `Retry-After` header
|
||||
|
||||
#### Scenario: Loss reasons endpoint not rate limited
|
||||
- **WHEN** a client sends requests to `/api/mid-section-defect/loss-reasons`
|
||||
- **THEN** no rate limiting SHALL be applied (endpoint is lightweight with 24h cache)
|
||||
|
||||
### Requirement: Mid-section defect upstream history SHALL classify workcenters in SQL
|
||||
The upstream history SQL query SHALL classify `WORKCENTERNAME` into workcenter groups using Oracle `CASE WHEN` expressions, returning the full production line history without excluding any stations.
|
||||
|
||||
#### Scenario: Workcenter group classification in SQL
|
||||
- **WHEN** the upstream history query executes
|
||||
- **THEN** each row SHALL include a `WORKCENTER_GROUP` column derived from `CASE WHEN` pattern matching
|
||||
- **THEN** the classification SHALL match the patterns defined in `workcenter_groups.py`
|
||||
|
||||
#### Scenario: Unknown workcenter name
|
||||
- **WHEN** a `WORKCENTERNAME` does not match any known pattern
|
||||
- **THEN** `WORKCENTER_GROUP` SHALL be NULL
|
||||
- **THEN** the row SHALL still be included in the result (not filtered out)
|
||||
|
||||
#### Scenario: Full production line retention
|
||||
- **WHEN** the upstream history is fetched for ancestor CIDs
|
||||
- **THEN** ALL stations SHALL be included (cutting, welding, mid-section, testing)
|
||||
- **THEN** no order-based filtering SHALL be applied
|
||||
|
||||
### Requirement: Mid-section defect routes and service SHALL have test coverage
|
||||
Route and service test files SHALL exist and cover core behaviors.
|
||||
|
||||
#### Scenario: Route tests exist
|
||||
- **WHEN** pytest discovers tests
|
||||
- **THEN** `tests/test_mid_section_defect_routes.py` SHALL contain tests for success, parameter validation (400), service failure (500), and rate limiting (429)
|
||||
|
||||
#### Scenario: Service tests exist
|
||||
- **WHEN** pytest discovers tests
|
||||
- **THEN** `tests/test_mid_section_defect_service.py` SHALL contain tests for date validation, pagination logic, and loss reasons caching
|
||||
|
||||
|
||||
@@ -87,3 +87,39 @@ Pages that require server-side parameter validation before serving SHALL validat
|
||||
- **WHEN** the pure Vite hold-detail page loads
|
||||
- **THEN** the page SHALL read `reason` from URL parameters
|
||||
- **THEN** if `reason` is empty or missing, the page SHALL redirect to `/wip-overview`
|
||||
|
||||
### Requirement: Mid-section defect page SHALL separate filter state from query state
|
||||
The mid-section defect page SHALL maintain separate reactive state for UI input (`filters`) and committed query parameters (`committedFilters`).
|
||||
|
||||
#### Scenario: User changes date without clicking query
|
||||
- **WHEN** user modifies the date range in the filter bar but does not click "查詢"
|
||||
- **THEN** auto-refresh, pagination, and CSV export SHALL continue using the previously committed filter values
|
||||
- **THEN** the new date range SHALL NOT affect any API calls until "查詢" is clicked
|
||||
|
||||
#### Scenario: User clicks query button
|
||||
- **WHEN** user clicks "查詢"
|
||||
- **THEN** the current `filters` state SHALL be snapshotted into `committedFilters`
|
||||
- **THEN** all subsequent API calls SHALL use the committed values
|
||||
|
||||
#### Scenario: CSV export uses committed filters
|
||||
- **WHEN** user clicks "匯出 CSV" after modifying filters without re-querying
|
||||
- **THEN** the export SHALL use the committed filter values from the last query
|
||||
- **THEN** the export SHALL NOT use the current UI filter values
|
||||
|
||||
### Requirement: Mid-section defect page SHALL cancel in-flight requests on new query
|
||||
The mid-section defect page SHALL use `AbortController` to cancel in-flight API requests when a new query is initiated.
|
||||
|
||||
#### Scenario: New query cancels previous query
|
||||
- **WHEN** user clicks "查詢" while a previous query is still in-flight
|
||||
- **THEN** the previous query's summary and detail requests SHALL be aborted
|
||||
- **THEN** the AbortError SHALL be handled silently (no error banner shown)
|
||||
|
||||
#### Scenario: Page navigation cancels previous detail request
|
||||
- **WHEN** user clicks next page while a previous page request is still in-flight
|
||||
- **THEN** the previous page request SHALL be aborted
|
||||
- **THEN** the new page request SHALL proceed independently
|
||||
|
||||
#### Scenario: Query and pagination use independent abort keys
|
||||
- **WHEN** a query is in-flight and user triggers pagination
|
||||
- **THEN** the query SHALL NOT be cancelled by the pagination request
|
||||
- **THEN** the pagination SHALL use a separate abort key from the query
|
||||
|
||||
@@ -4,24 +4,50 @@
|
||||
Reverse traceability from TMTT (test) station back to upstream production stations.
|
||||
"""
|
||||
|
||||
from flask import Blueprint, jsonify, request, Response
|
||||
|
||||
from mes_dashboard.services.mid_section_defect_service import (
|
||||
query_analysis,
|
||||
query_analysis_detail,
|
||||
query_all_loss_reasons,
|
||||
export_csv,
|
||||
from flask import Blueprint, jsonify, request, Response
|
||||
|
||||
from mes_dashboard.core.rate_limit import configured_rate_limit
|
||||
from mes_dashboard.services.mid_section_defect_service import (
|
||||
query_analysis,
|
||||
query_analysis_detail,
|
||||
query_all_loss_reasons,
|
||||
export_csv,
|
||||
)
|
||||
|
||||
mid_section_defect_bp = Blueprint(
|
||||
'mid_section_defect',
|
||||
__name__,
|
||||
url_prefix='/api/mid-section-defect'
|
||||
)
|
||||
|
||||
|
||||
@mid_section_defect_bp.route('/analysis', methods=['GET'])
|
||||
def api_analysis():
|
||||
mid_section_defect_bp = Blueprint(
|
||||
'mid_section_defect',
|
||||
__name__,
|
||||
url_prefix='/api/mid-section-defect'
|
||||
)
|
||||
|
||||
_ANALYSIS_RATE_LIMIT = configured_rate_limit(
|
||||
bucket="mid-section-defect-analysis",
|
||||
max_attempts_env="MID_SECTION_DEFECT_ANALYSIS_RATE_LIMIT_MAX_REQUESTS",
|
||||
window_seconds_env="MID_SECTION_DEFECT_ANALYSIS_RATE_LIMIT_WINDOW_SECONDS",
|
||||
default_max_attempts=6,
|
||||
default_window_seconds=60,
|
||||
)
|
||||
|
||||
_DETAIL_RATE_LIMIT = configured_rate_limit(
|
||||
bucket="mid-section-defect-analysis-detail",
|
||||
max_attempts_env="MID_SECTION_DEFECT_DETAIL_RATE_LIMIT_MAX_REQUESTS",
|
||||
window_seconds_env="MID_SECTION_DEFECT_DETAIL_RATE_LIMIT_WINDOW_SECONDS",
|
||||
default_max_attempts=15,
|
||||
default_window_seconds=60,
|
||||
)
|
||||
|
||||
_EXPORT_RATE_LIMIT = configured_rate_limit(
|
||||
bucket="mid-section-defect-export",
|
||||
max_attempts_env="MID_SECTION_DEFECT_EXPORT_RATE_LIMIT_MAX_REQUESTS",
|
||||
window_seconds_env="MID_SECTION_DEFECT_EXPORT_RATE_LIMIT_WINDOW_SECONDS",
|
||||
default_max_attempts=3,
|
||||
default_window_seconds=60,
|
||||
)
|
||||
|
||||
|
||||
@mid_section_defect_bp.route('/analysis', methods=['GET'])
|
||||
@_ANALYSIS_RATE_LIMIT
|
||||
def api_analysis():
|
||||
"""API: Get mid-section defect traceability analysis (summary).
|
||||
|
||||
Returns kpi, charts, daily_trend, available_loss_reasons, genealogy_status,
|
||||
@@ -66,8 +92,9 @@ def api_analysis():
|
||||
return jsonify({'success': True, 'data': summary})
|
||||
|
||||
|
||||
@mid_section_defect_bp.route('/analysis/detail', methods=['GET'])
|
||||
def api_analysis_detail():
|
||||
@mid_section_defect_bp.route('/analysis/detail', methods=['GET'])
|
||||
@_DETAIL_RATE_LIMIT
|
||||
def api_analysis_detail():
|
||||
"""API: Get paginated detail table for mid-section defect analysis.
|
||||
|
||||
Query Parameters:
|
||||
@@ -124,8 +151,9 @@ def api_loss_reasons():
|
||||
return jsonify({'success': True, 'data': result})
|
||||
|
||||
|
||||
@mid_section_defect_bp.route('/export', methods=['GET'])
|
||||
def api_export():
|
||||
@mid_section_defect_bp.route('/export', methods=['GET'])
|
||||
@_EXPORT_RATE_LIMIT
|
||||
def api_export():
|
||||
"""API: Export mid-section defect detail data as CSV.
|
||||
|
||||
Query Parameters:
|
||||
|
||||
@@ -18,32 +18,35 @@ Attribution Method (Sum):
|
||||
rate = attributed_rejectqty / attributed_trackinqty × 100
|
||||
"""
|
||||
|
||||
import csv
|
||||
import io
|
||||
import logging
|
||||
import math
|
||||
from collections import defaultdict
|
||||
from datetime import datetime
|
||||
from typing import Optional, Dict, List, Any, Set, Tuple, Generator
|
||||
|
||||
import pandas as pd
|
||||
|
||||
from mes_dashboard.core.database import read_sql_df
|
||||
from mes_dashboard.core.cache import cache_get, cache_set, make_cache_key
|
||||
from mes_dashboard.sql import SQLLoader, QueryBuilder
|
||||
from mes_dashboard.config.workcenter_groups import get_workcenter_group
|
||||
|
||||
logger = logging.getLogger('mes_dashboard.mid_section_defect')
|
||||
import csv
|
||||
import hashlib
|
||||
import io
|
||||
import logging
|
||||
import math
|
||||
import time
|
||||
from collections import defaultdict
|
||||
from datetime import datetime
|
||||
from typing import Optional, Dict, List, Any, Set, Tuple, Generator
|
||||
|
||||
import pandas as pd
|
||||
|
||||
from mes_dashboard.core.database import read_sql_df
|
||||
from mes_dashboard.core.cache import cache_get, cache_set, make_cache_key
|
||||
from mes_dashboard.core.redis_client import try_acquire_lock, release_lock
|
||||
from mes_dashboard.sql import SQLLoader, QueryBuilder
|
||||
|
||||
logger = logging.getLogger('mes_dashboard.mid_section_defect')
|
||||
|
||||
# Constants
|
||||
MAX_QUERY_DAYS = 180
|
||||
CACHE_TTL_TMTT = 300 # 5 min for TMTT detection data
|
||||
CACHE_TTL_LOSS_REASONS = 86400 # 24h for loss reason list (daily sync)
|
||||
ORACLE_IN_BATCH_SIZE = 1000 # Oracle IN clause limit
|
||||
|
||||
# Mid-section workcenter group order range (成型 through 測試)
|
||||
MID_SECTION_ORDER_MIN = 4 # 成型
|
||||
MID_SECTION_ORDER_MAX = 11 # 測試
|
||||
ORACLE_IN_BATCH_SIZE = 1000 # Oracle IN clause limit
|
||||
|
||||
# Distributed lock settings for query_analysis cold-cache path
|
||||
ANALYSIS_LOCK_TTL_SECONDS = 120
|
||||
ANALYSIS_LOCK_WAIT_TIMEOUT_SECONDS = 90
|
||||
ANALYSIS_LOCK_POLL_INTERVAL_SECONDS = 0.5
|
||||
|
||||
# Top N for chart display (rest grouped as "其他")
|
||||
TOP_N = 10
|
||||
@@ -107,81 +110,113 @@ def query_analysis(
|
||||
'loss_reasons': sorted(loss_reasons) if loss_reasons else None,
|
||||
},
|
||||
)
|
||||
cached = cache_get(cache_key)
|
||||
if cached is not None:
|
||||
return cached
|
||||
|
||||
# Stage 1: TMTT detection data
|
||||
tmtt_df = _fetch_tmtt_data(start_date, end_date)
|
||||
if tmtt_df is None:
|
||||
return None
|
||||
if tmtt_df.empty:
|
||||
return _empty_result()
|
||||
|
||||
# Extract available loss reasons before filtering
|
||||
available_loss_reasons = sorted(
|
||||
tmtt_df.loc[tmtt_df['REJECTQTY'] > 0, 'LOSSREASONNAME']
|
||||
.dropna().unique().tolist()
|
||||
)
|
||||
|
||||
# Apply loss reason filter if specified
|
||||
if loss_reasons:
|
||||
filtered_df = tmtt_df[
|
||||
(tmtt_df['LOSSREASONNAME'].isin(loss_reasons))
|
||||
| (tmtt_df['REJECTQTY'] == 0)
|
||||
| (tmtt_df['LOSSREASONNAME'].isna())
|
||||
].copy()
|
||||
else:
|
||||
filtered_df = tmtt_df
|
||||
|
||||
# Stage 2: Genealogy resolution (split chain + merge expansion)
|
||||
tmtt_cids = tmtt_df['CONTAINERID'].unique().tolist()
|
||||
tmtt_names = {}
|
||||
for _, r in tmtt_df.drop_duplicates('CONTAINERID').iterrows():
|
||||
tmtt_names[r['CONTAINERID']] = _safe_str(r.get('CONTAINERNAME'))
|
||||
|
||||
ancestors = {}
|
||||
genealogy_status = 'ready'
|
||||
|
||||
if tmtt_cids:
|
||||
try:
|
||||
ancestors = _resolve_full_genealogy(tmtt_cids, tmtt_names)
|
||||
except Exception as exc:
|
||||
logger.error(f"Genealogy resolution failed: {exc}", exc_info=True)
|
||||
genealogy_status = 'error'
|
||||
|
||||
# Stage 3: Upstream history for ALL CIDs (TMTT lots + ancestors)
|
||||
all_query_cids = set(tmtt_cids)
|
||||
for anc_set in ancestors.values():
|
||||
all_query_cids.update(anc_set)
|
||||
# Filter out any non-string values (NaN/None from pandas)
|
||||
all_query_cids = {c for c in all_query_cids if isinstance(c, str) and c}
|
||||
|
||||
upstream_by_cid = {}
|
||||
if all_query_cids:
|
||||
try:
|
||||
upstream_by_cid = _fetch_upstream_history(list(all_query_cids))
|
||||
except Exception as exc:
|
||||
logger.error(f"Upstream history query failed: {exc}", exc_info=True)
|
||||
genealogy_status = 'error'
|
||||
tmtt_data = _build_tmtt_lookup(filtered_df)
|
||||
attribution = _attribute_defects(
|
||||
tmtt_data, ancestors, upstream_by_cid, loss_reasons,
|
||||
)
|
||||
|
||||
result = {
|
||||
'kpi': _build_kpi(filtered_df, attribution, loss_reasons),
|
||||
'available_loss_reasons': available_loss_reasons,
|
||||
'charts': _build_all_charts(attribution, tmtt_data),
|
||||
'daily_trend': _build_daily_trend(filtered_df, loss_reasons),
|
||||
'detail': _build_detail_table(filtered_df, ancestors, upstream_by_cid),
|
||||
'genealogy_status': genealogy_status,
|
||||
}
|
||||
|
||||
# Only cache successful results (don't cache upstream errors)
|
||||
if genealogy_status == 'ready':
|
||||
cache_set(cache_key, result, ttl=CACHE_TTL_TMTT)
|
||||
return result
|
||||
cached = cache_get(cache_key)
|
||||
if cached is not None:
|
||||
return cached
|
||||
|
||||
lock_name = (
|
||||
f"mid_section_defect:analysis:{hashlib.md5(cache_key.encode('utf-8')).hexdigest()}"
|
||||
)
|
||||
lock_acquired = False
|
||||
|
||||
# Prevent duplicate cold-cache pipeline execution across workers.
|
||||
lock_acquired = try_acquire_lock(lock_name, ttl_seconds=ANALYSIS_LOCK_TTL_SECONDS)
|
||||
if not lock_acquired:
|
||||
wait_start = time.monotonic()
|
||||
while (
|
||||
time.monotonic() - wait_start
|
||||
< ANALYSIS_LOCK_WAIT_TIMEOUT_SECONDS
|
||||
):
|
||||
cached = cache_get(cache_key)
|
||||
if cached is not None:
|
||||
return cached
|
||||
time.sleep(ANALYSIS_LOCK_POLL_INTERVAL_SECONDS)
|
||||
|
||||
logger.warning(
|
||||
"Timed out waiting for in-flight mid_section_defect analysis cache; "
|
||||
"continuing with fail-open pipeline execution"
|
||||
)
|
||||
else:
|
||||
# Double-check cache after lock acquisition.
|
||||
cached = cache_get(cache_key)
|
||||
if cached is not None:
|
||||
return cached
|
||||
|
||||
try:
|
||||
# Stage 1: TMTT detection data
|
||||
tmtt_df = _fetch_tmtt_data(start_date, end_date)
|
||||
if tmtt_df is None:
|
||||
return None
|
||||
if tmtt_df.empty:
|
||||
return _empty_result()
|
||||
|
||||
# Extract available loss reasons before filtering
|
||||
available_loss_reasons = sorted(
|
||||
tmtt_df.loc[tmtt_df['REJECTQTY'] > 0, 'LOSSREASONNAME']
|
||||
.dropna().unique().tolist()
|
||||
)
|
||||
|
||||
# Apply loss reason filter if specified
|
||||
if loss_reasons:
|
||||
filtered_df = tmtt_df[
|
||||
(tmtt_df['LOSSREASONNAME'].isin(loss_reasons))
|
||||
| (tmtt_df['REJECTQTY'] == 0)
|
||||
| (tmtt_df['LOSSREASONNAME'].isna())
|
||||
].copy()
|
||||
else:
|
||||
filtered_df = tmtt_df
|
||||
|
||||
# Stage 2: Genealogy resolution (split chain + merge expansion)
|
||||
tmtt_cids = tmtt_df['CONTAINERID'].unique().tolist()
|
||||
tmtt_names = {}
|
||||
for _, r in tmtt_df.drop_duplicates('CONTAINERID').iterrows():
|
||||
tmtt_names[r['CONTAINERID']] = _safe_str(r.get('CONTAINERNAME'))
|
||||
|
||||
ancestors = {}
|
||||
genealogy_status = 'ready'
|
||||
|
||||
if tmtt_cids:
|
||||
try:
|
||||
ancestors = _resolve_full_genealogy(tmtt_cids, tmtt_names)
|
||||
except Exception as exc:
|
||||
logger.error(f"Genealogy resolution failed: {exc}", exc_info=True)
|
||||
genealogy_status = 'error'
|
||||
|
||||
# Stage 3: Upstream history for ALL CIDs (TMTT lots + ancestors)
|
||||
all_query_cids = set(tmtt_cids)
|
||||
for anc_set in ancestors.values():
|
||||
all_query_cids.update(anc_set)
|
||||
# Filter out any non-string values (NaN/None from pandas)
|
||||
all_query_cids = {c for c in all_query_cids if isinstance(c, str) and c}
|
||||
|
||||
upstream_by_cid = {}
|
||||
if all_query_cids:
|
||||
try:
|
||||
upstream_by_cid = _fetch_upstream_history(list(all_query_cids))
|
||||
except Exception as exc:
|
||||
logger.error(f"Upstream history query failed: {exc}", exc_info=True)
|
||||
genealogy_status = 'error'
|
||||
tmtt_data = _build_tmtt_lookup(filtered_df)
|
||||
attribution = _attribute_defects(
|
||||
tmtt_data, ancestors, upstream_by_cid, loss_reasons,
|
||||
)
|
||||
|
||||
result = {
|
||||
'kpi': _build_kpi(filtered_df, attribution, loss_reasons),
|
||||
'available_loss_reasons': available_loss_reasons,
|
||||
'charts': _build_all_charts(attribution, tmtt_data),
|
||||
'daily_trend': _build_daily_trend(filtered_df, loss_reasons),
|
||||
'detail': _build_detail_table(filtered_df, ancestors, upstream_by_cid),
|
||||
'genealogy_status': genealogy_status,
|
||||
}
|
||||
|
||||
# Only cache successful results (don't cache upstream errors)
|
||||
if genealogy_status == 'ready':
|
||||
cache_set(cache_key, result, ttl=CACHE_TTL_TMTT)
|
||||
return result
|
||||
finally:
|
||||
if lock_acquired:
|
||||
release_lock(lock_name)
|
||||
|
||||
|
||||
def query_analysis_detail(
|
||||
@@ -600,13 +635,13 @@ def _log_genealogy_summary(
|
||||
# Query 3: Upstream Production History
|
||||
# ============================================================
|
||||
|
||||
def _fetch_upstream_history(
|
||||
all_cids: List[str],
|
||||
) -> Dict[str, List[Dict[str, Any]]]:
|
||||
def _fetch_upstream_history(
|
||||
all_cids: List[str],
|
||||
) -> Dict[str, List[Dict[str, Any]]]:
|
||||
"""Fetch upstream production history for ancestor CONTAINERIDs.
|
||||
|
||||
Batches queries to respect Oracle IN clause limit.
|
||||
Filters by mid-section workcenter groups (order 4-11) in Python.
|
||||
Batches queries to respect Oracle IN clause limit.
|
||||
WORKCENTER_GROUP classification is computed in SQL (CASE WHEN).
|
||||
|
||||
Returns:
|
||||
{containerid: [{'workcenter_group': ..., 'equipment_name': ..., ...}, ...]}
|
||||
@@ -646,28 +681,24 @@ def _fetch_upstream_history(
|
||||
|
||||
combined = pd.concat(all_rows, ignore_index=True)
|
||||
|
||||
# Filter by mid-section workcenter groups in Python
|
||||
result: Dict[str, List[Dict[str, Any]]] = defaultdict(list)
|
||||
for _, row in combined.iterrows():
|
||||
wc_name = row.get('WORKCENTERNAME', '')
|
||||
group_name, order = get_workcenter_group(wc_name)
|
||||
if group_name is None or order < MID_SECTION_ORDER_MIN or order > MID_SECTION_ORDER_MAX:
|
||||
continue
|
||||
|
||||
cid = row['CONTAINERID']
|
||||
result[cid].append({
|
||||
'workcenter_group': group_name,
|
||||
'workcenter_group_order': order,
|
||||
'equipment_id': _safe_str(row.get('EQUIPMENTID')),
|
||||
'equipment_name': _safe_str(row.get('EQUIPMENTNAME')),
|
||||
'spec_name': _safe_str(row.get('SPECNAME')),
|
||||
'track_in_time': _safe_str(row.get('TRACKINTIMESTAMP')),
|
||||
})
|
||||
|
||||
logger.info(
|
||||
f"Upstream history: {len(result)} lots with mid-section records, "
|
||||
f"from {len(unique_cids)} queried CIDs"
|
||||
)
|
||||
result: Dict[str, List[Dict[str, Any]]] = defaultdict(list)
|
||||
for _, row in combined.iterrows():
|
||||
cid = row['CONTAINERID']
|
||||
group_name = _safe_str(row.get('WORKCENTER_GROUP'))
|
||||
if not group_name:
|
||||
group_name = '(未知)'
|
||||
result[cid].append({
|
||||
'workcenter_group': group_name,
|
||||
'equipment_id': _safe_str(row.get('EQUIPMENTID')),
|
||||
'equipment_name': _safe_str(row.get('EQUIPMENTNAME')),
|
||||
'spec_name': _safe_str(row.get('SPECNAME')),
|
||||
'track_in_time': _safe_str(row.get('TRACKINTIMESTAMP')),
|
||||
})
|
||||
|
||||
logger.info(
|
||||
f"Upstream history: {len(result)} lots with classified records, "
|
||||
f"from {len(unique_cids)} queried CIDs"
|
||||
)
|
||||
return dict(result)
|
||||
|
||||
|
||||
|
||||
@@ -11,14 +11,44 @@
|
||||
-- CONTAINERID has index. Batch IN clause (up to 1000 per query).
|
||||
-- Estimated 1-5s per batch.
|
||||
--
|
||||
WITH ranked_history AS (
|
||||
SELECT
|
||||
h.CONTAINERID,
|
||||
h.WORKCENTERNAME,
|
||||
h.EQUIPMENTID,
|
||||
h.EQUIPMENTNAME,
|
||||
h.SPECNAME,
|
||||
h.TRACKINTIMESTAMP,
|
||||
WITH ranked_history AS (
|
||||
SELECT
|
||||
h.CONTAINERID,
|
||||
h.WORKCENTERNAME,
|
||||
CASE
|
||||
WHEN UPPER(h.WORKCENTERNAME) LIKE '%元件切割%'
|
||||
OR UPPER(h.WORKCENTERNAME) LIKE '%PKG_SAW%' THEN '元件切割'
|
||||
WHEN UPPER(h.WORKCENTERNAME) LIKE '%切割%' THEN '切割'
|
||||
WHEN UPPER(h.WORKCENTERNAME) LIKE '%焊接_DB%'
|
||||
OR UPPER(h.WORKCENTERNAME) LIKE '%焊_DB_料%'
|
||||
OR UPPER(h.WORKCENTERNAME) LIKE '%焊_DB%' THEN '焊接_DB'
|
||||
WHEN UPPER(h.WORKCENTERNAME) LIKE '%焊接_WB%'
|
||||
OR UPPER(h.WORKCENTERNAME) LIKE '%焊_WB_料%'
|
||||
OR UPPER(h.WORKCENTERNAME) LIKE '%焊_WB%' THEN '焊接_WB'
|
||||
WHEN UPPER(h.WORKCENTERNAME) LIKE '%焊接_DW%'
|
||||
OR UPPER(h.WORKCENTERNAME) LIKE '%焊_DW%'
|
||||
OR UPPER(h.WORKCENTERNAME) LIKE '%焊_DW_料%' THEN '焊接_DW'
|
||||
WHEN UPPER(h.WORKCENTERNAME) LIKE '%成型%'
|
||||
OR UPPER(h.WORKCENTERNAME) LIKE '%成型_料%' THEN '成型'
|
||||
WHEN UPPER(h.WORKCENTERNAME) LIKE '%去膠%' THEN '去膠'
|
||||
WHEN UPPER(h.WORKCENTERNAME) LIKE '%水吹砂%' THEN '水吹砂'
|
||||
WHEN UPPER(h.WORKCENTERNAME) LIKE '%掛鍍%'
|
||||
OR UPPER(h.WORKCENTERNAME) LIKE '%滾鍍%'
|
||||
OR UPPER(h.WORKCENTERNAME) LIKE '%條鍍%'
|
||||
OR UPPER(h.WORKCENTERNAME) LIKE '%電鍍%'
|
||||
OR UPPER(h.WORKCENTERNAME) LIKE '%補鍍%'
|
||||
OR UPPER(h.WORKCENTERNAME) LIKE '%TOTAI%'
|
||||
OR UPPER(h.WORKCENTERNAME) LIKE '%BANDL%' THEN '電鍍'
|
||||
WHEN UPPER(h.WORKCENTERNAME) LIKE '%移印%' THEN '移印'
|
||||
WHEN UPPER(h.WORKCENTERNAME) LIKE '%切彎腳%' THEN '切彎腳'
|
||||
WHEN UPPER(h.WORKCENTERNAME) LIKE '%TMTT%'
|
||||
OR UPPER(h.WORKCENTERNAME) LIKE '%測試%' THEN '測試'
|
||||
ELSE NULL
|
||||
END AS WORKCENTER_GROUP,
|
||||
h.EQUIPMENTID,
|
||||
h.EQUIPMENTNAME,
|
||||
h.SPECNAME,
|
||||
h.TRACKINTIMESTAMP,
|
||||
ROW_NUMBER() OVER (
|
||||
PARTITION BY h.CONTAINERID, h.WORKCENTERNAME, h.EQUIPMENTNAME
|
||||
ORDER BY h.TRACKINTIMESTAMP DESC
|
||||
@@ -28,13 +58,14 @@ WITH ranked_history AS (
|
||||
AND h.EQUIPMENTID IS NOT NULL
|
||||
AND h.TRACKINTIMESTAMP IS NOT NULL
|
||||
)
|
||||
SELECT
|
||||
CONTAINERID,
|
||||
WORKCENTERNAME,
|
||||
EQUIPMENTID,
|
||||
EQUIPMENTNAME,
|
||||
SPECNAME,
|
||||
TRACKINTIMESTAMP
|
||||
SELECT
|
||||
CONTAINERID,
|
||||
WORKCENTERNAME,
|
||||
WORKCENTER_GROUP,
|
||||
EQUIPMENTID,
|
||||
EQUIPMENTNAME,
|
||||
SPECNAME,
|
||||
TRACKINTIMESTAMP
|
||||
FROM ranked_history
|
||||
WHERE rn = 1
|
||||
ORDER BY CONTAINERID, TRACKINTIMESTAMP
|
||||
|
||||
@@ -125,6 +125,41 @@
|
||||
overflow-y: auto;
|
||||
}
|
||||
|
||||
.workcenter-group-header {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: 8px;
|
||||
padding: 8px 15px;
|
||||
background: #f0f0f0;
|
||||
font-weight: 600;
|
||||
font-size: 12px;
|
||||
color: #666;
|
||||
cursor: pointer;
|
||||
user-select: none;
|
||||
}
|
||||
|
||||
.workcenter-group-header:hover {
|
||||
background: #e8e8e8;
|
||||
}
|
||||
|
||||
.workcenter-group-header input[type="checkbox"] {
|
||||
cursor: pointer;
|
||||
}
|
||||
|
||||
.workcenter-group-header input[type="checkbox"].indeterminate {
|
||||
opacity: 0.6;
|
||||
}
|
||||
|
||||
.workcenter-group-name {
|
||||
flex: 1;
|
||||
}
|
||||
|
||||
.workcenter-group-count {
|
||||
font-weight: 400;
|
||||
font-size: 11px;
|
||||
color: #999;
|
||||
}
|
||||
|
||||
.equipment-item {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
@@ -460,7 +495,7 @@
|
||||
<!-- Actions -->
|
||||
<div class="filter-actions">
|
||||
<button class="btn btn-primary" onclick="queryJobs()" id="queryBtn">
|
||||
查詢工單
|
||||
查詢
|
||||
</button>
|
||||
<button class="btn btn-success" onclick="exportCsv()" id="exportBtn" disabled>
|
||||
匯出 CSV
|
||||
@@ -471,19 +506,19 @@
|
||||
<!-- Result Section -->
|
||||
<div class="result-section" id="resultSection">
|
||||
<div class="empty-state">
|
||||
<p>請選擇設備和日期範圍後，點擊「查詢工單」</p>
|
||||
<p>請選擇設備和日期範圍後，點擊「查詢」</p>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
{% endblock %}
|
||||
|
||||
{% block scripts %}
|
||||
{% set job_query_js = frontend_asset('job-query.js') %}
|
||||
{% if job_query_js %}
|
||||
<script type="module" src="{{ job_query_js }}"></script>
|
||||
{% else %}
|
||||
<script>
|
||||
{% block scripts %}
|
||||
{% set job_query_js = frontend_asset('job-query.js') %}
|
||||
{% if job_query_js %}
|
||||
<script type="module" src="{{ job_query_js }}"></script>
|
||||
{% else %}
|
||||
<script>
|
||||
// State
|
||||
let allEquipments = [];
|
||||
let selectedEquipments = new Set();
|
||||
@@ -531,26 +566,39 @@
|
||||
}
|
||||
|
||||
let html = '';
|
||||
let currentWorkcenter = null;
|
||||
|
||||
// Group by workcenter
|
||||
const grouped = {};
|
||||
equipments.forEach(eq => {
|
||||
const isSelected = selectedEquipments.has(eq.RESOURCEID);
|
||||
const wc = eq.WORKCENTERNAME || '未分類';
|
||||
if (!grouped[wc]) grouped[wc] = [];
|
||||
grouped[wc].push(eq);
|
||||
});
|
||||
const workcenters = Object.keys(grouped).sort();
|
||||
|
||||
// Group header
|
||||
if (eq.WORKCENTERNAME !== currentWorkcenter) {
|
||||
currentWorkcenter = eq.WORKCENTERNAME;
|
||||
html += `<div style="padding: 8px 15px; background: #f0f0f0; font-weight: 600; font-size: 12px; color: #666;">${currentWorkcenter || '未分類'}</div>`;
|
||||
}
|
||||
|
||||
html += `
|
||||
<div class="equipment-item ${isSelected ? 'selected' : ''}" onclick="toggleEquipment('${eq.RESOURCEID}')">
|
||||
<input type="checkbox" ${isSelected ? 'checked' : ''} onclick="event.stopPropagation(); toggleEquipment('${eq.RESOURCEID}')">
|
||||
<div class="equipment-info">
|
||||
<div class="equipment-name">${eq.RESOURCENAME}</div>
|
||||
<div class="equipment-workcenter">${eq.RESOURCEFAMILYNAME || ''}</div>
|
||||
workcenters.forEach(workcenterName => {
|
||||
const groupEquipments = grouped[workcenterName];
|
||||
const groupIds = groupEquipments.map(eq => eq.RESOURCEID);
|
||||
const selectedInGroup = groupIds.filter(id => selectedEquipments.has(id)).length;
|
||||
const allSelected = selectedInGroup === groupIds.length;
|
||||
const someSelected = selectedInGroup > 0 && !allSelected;
|
||||
html += `<div class="workcenter-group-header" onclick="toggleWorkcenterGroup('${workcenterName}')">
|
||||
<input type="checkbox" ${allSelected ? 'checked' : ''} ${someSelected ? 'class="indeterminate"' : ''} onclick="event.stopPropagation(); toggleWorkcenterGroup('${workcenterName}')">
|
||||
<span class="workcenter-group-name">${workcenterName}</span>
|
||||
<span class="workcenter-group-count">${selectedInGroup}/${groupIds.length}</span>
|
||||
</div>`;
|
||||
groupEquipments.forEach(eq => {
|
||||
const isSelected = selectedEquipments.has(eq.RESOURCEID);
|
||||
html += `
|
||||
<div class="equipment-item ${isSelected ? 'selected' : ''}" onclick="toggleEquipment('${eq.RESOURCEID}')">
|
||||
<input type="checkbox" ${isSelected ? 'checked' : ''} onclick="event.stopPropagation(); toggleEquipment('${eq.RESOURCEID}')">
|
||||
<div class="equipment-info">
|
||||
<div class="equipment-name">${eq.RESOURCENAME}</div>
|
||||
<div class="equipment-workcenter">${eq.RESOURCEFAMILYNAME || ''}</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
`;
|
||||
`;
|
||||
});
|
||||
});
|
||||
|
||||
container.innerHTML = html;
|
||||
@@ -590,6 +638,30 @@
|
||||
}));
|
||||
}
|
||||
|
||||
// Toggle entire workcenter group selection
|
||||
function toggleWorkcenterGroup(workcenterName) {
|
||||
const groupEquipments = allEquipments.filter(
|
||||
eq => (eq.WORKCENTERNAME || '未分類') === workcenterName
|
||||
);
|
||||
const groupIds = groupEquipments.map(eq => eq.RESOURCEID);
|
||||
const allSelected = groupIds.every(id => selectedEquipments.has(id));
|
||||
|
||||
if (allSelected) {
|
||||
groupIds.forEach(id => selectedEquipments.delete(id));
|
||||
} else {
|
||||
groupIds.forEach(id => selectedEquipments.add(id));
|
||||
}
|
||||
|
||||
updateSelectedDisplay();
|
||||
renderEquipmentList(allEquipments.filter(eq => {
|
||||
const search = document.querySelector('.equipment-search');
|
||||
if (!search || !search.value) return true;
|
||||
const q = search.value.toLowerCase();
|
||||
return (eq.RESOURCENAME && eq.RESOURCENAME.toLowerCase().includes(q)) ||
|
||||
(eq.WORKCENTERNAME && eq.WORKCENTERNAME.toLowerCase().includes(q));
|
||||
}));
|
||||
}
|
||||
|
||||
// Update selected display
|
||||
function updateSelectedDisplay() {
|
||||
const display = document.getElementById('equipmentDisplay');
|
||||
@@ -918,6 +990,6 @@
|
||||
if (!dateStr) return '';
|
||||
return dateStr.replace('T', ' ').substring(0, 19);
|
||||
}
|
||||
</script>
|
||||
{% endif %}
|
||||
{% endblock %}
|
||||
</script>
|
||||
{% endif %}
|
||||
{% endblock %}
|
||||
|
||||
162
tests/test_mid_section_defect_routes.py
Normal file
162
tests/test_mid_section_defect_routes.py
Normal file
@@ -0,0 +1,162 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
"""Route tests for mid-section defect APIs."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from unittest.mock import patch
|
||||
|
||||
import mes_dashboard.core.database as db
|
||||
from mes_dashboard.app import create_app
|
||||
from mes_dashboard.core.rate_limit import reset_rate_limits_for_tests
|
||||
|
||||
|
||||
def _client():
|
||||
db._ENGINE = None
|
||||
app = create_app('testing')
|
||||
app.config['TESTING'] = True
|
||||
return app.test_client()
|
||||
|
||||
|
||||
def setup_function():
|
||||
reset_rate_limits_for_tests()
|
||||
|
||||
|
||||
def teardown_function():
|
||||
reset_rate_limits_for_tests()
|
||||
|
||||
|
||||
@patch('mes_dashboard.routes.mid_section_defect_routes.query_analysis')
|
||||
def test_analysis_success(mock_query_analysis):
|
||||
mock_query_analysis.return_value = {
|
||||
'kpi': {'total_input': 100},
|
||||
'charts': {'by_station': []},
|
||||
'daily_trend': [],
|
||||
'available_loss_reasons': ['A'],
|
||||
'genealogy_status': 'ready',
|
||||
'detail': [{}, {}],
|
||||
}
|
||||
|
||||
client = _client()
|
||||
response = client.get(
|
||||
'/api/mid-section-defect/analysis?start_date=2025-01-01&end_date=2025-01-31&loss_reasons=A,B'
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
payload = response.get_json()
|
||||
assert payload['success'] is True
|
||||
assert payload['data']['detail_total_count'] == 2
|
||||
assert payload['data']['kpi']['total_input'] == 100
|
||||
mock_query_analysis.assert_called_once_with('2025-01-01', '2025-01-31', ['A', 'B'])
|
||||
|
||||
|
||||
def test_analysis_missing_dates_returns_400():
|
||||
client = _client()
|
||||
response = client.get('/api/mid-section-defect/analysis?start_date=2025-01-01')
|
||||
|
||||
assert response.status_code == 400
|
||||
payload = response.get_json()
|
||||
assert payload['success'] is False
|
||||
|
||||
|
||||
@patch('mes_dashboard.routes.mid_section_defect_routes.query_analysis')
|
||||
def test_analysis_service_failure_returns_500(mock_query_analysis):
|
||||
mock_query_analysis.return_value = None
|
||||
|
||||
client = _client()
|
||||
response = client.get('/api/mid-section-defect/analysis?start_date=2025-01-01&end_date=2025-01-31')
|
||||
|
||||
assert response.status_code == 500
|
||||
payload = response.get_json()
|
||||
assert payload['success'] is False
|
||||
|
||||
|
||||
@patch('mes_dashboard.routes.mid_section_defect_routes.query_analysis')
|
||||
@patch('mes_dashboard.core.rate_limit.check_and_record', return_value=(True, 7))
|
||||
def test_analysis_rate_limited_returns_429(_mock_rate_limit, mock_query_analysis):
|
||||
client = _client()
|
||||
response = client.get('/api/mid-section-defect/analysis?start_date=2025-01-01&end_date=2025-01-31')
|
||||
|
||||
assert response.status_code == 429
|
||||
assert response.headers.get('Retry-After') == '7'
|
||||
payload = response.get_json()
|
||||
assert payload['error']['code'] == 'TOO_MANY_REQUESTS'
|
||||
mock_query_analysis.assert_not_called()
|
||||
|
||||
|
||||
@patch('mes_dashboard.routes.mid_section_defect_routes.query_analysis_detail')
|
||||
def test_detail_success(mock_query_detail):
|
||||
mock_query_detail.return_value = {
|
||||
'detail': [{'CONTAINERNAME': 'LOT-1'}],
|
||||
'pagination': {'page': 2, 'page_size': 200, 'total_count': 350, 'total_pages': 2},
|
||||
}
|
||||
|
||||
client = _client()
|
||||
response = client.get(
|
||||
'/api/mid-section-defect/analysis/detail?start_date=2025-01-01&end_date=2025-01-31&page=2&page_size=200'
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
payload = response.get_json()
|
||||
assert payload['success'] is True
|
||||
assert payload['data']['pagination']['page'] == 2
|
||||
mock_query_detail.assert_called_once_with(
|
||||
'2025-01-01',
|
||||
'2025-01-31',
|
||||
None,
|
||||
page=2,
|
||||
page_size=200,
|
||||
)
|
||||
|
||||
|
||||
def test_detail_missing_dates_returns_400():
|
||||
client = _client()
|
||||
response = client.get('/api/mid-section-defect/analysis/detail?end_date=2025-01-31')
|
||||
|
||||
assert response.status_code == 400
|
||||
payload = response.get_json()
|
||||
assert payload['success'] is False
|
||||
|
||||
|
||||
@patch('mes_dashboard.routes.mid_section_defect_routes.query_analysis_detail')
|
||||
@patch('mes_dashboard.core.rate_limit.check_and_record', return_value=(True, 5))
|
||||
def test_detail_rate_limited_returns_429(_mock_rate_limit, mock_query_detail):
|
||||
client = _client()
|
||||
response = client.get('/api/mid-section-defect/analysis/detail?start_date=2025-01-01&end_date=2025-01-31')
|
||||
|
||||
assert response.status_code == 429
|
||||
assert response.headers.get('Retry-After') == '5'
|
||||
payload = response.get_json()
|
||||
assert payload['error']['code'] == 'TOO_MANY_REQUESTS'
|
||||
mock_query_detail.assert_not_called()
|
||||
|
||||
|
||||
@patch('mes_dashboard.routes.mid_section_defect_routes.export_csv')
|
||||
def test_export_success(mock_export_csv):
|
||||
mock_export_csv.return_value = iter([
|
||||
'\ufeff',
|
||||
'LOT ID,TYPE\r\n',
|
||||
'A001,T1\r\n',
|
||||
])
|
||||
|
||||
client = _client()
|
||||
response = client.get(
|
||||
'/api/mid-section-defect/export?start_date=2025-01-01&end_date=2025-01-31&loss_reasons=A,B'
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
assert 'text/csv' in response.content_type
|
||||
assert 'attachment;' in response.headers.get('Content-Disposition', '')
|
||||
mock_export_csv.assert_called_once_with('2025-01-01', '2025-01-31', ['A', 'B'])
|
||||
|
||||
|
||||
@patch('mes_dashboard.routes.mid_section_defect_routes.export_csv')
|
||||
@patch('mes_dashboard.core.rate_limit.check_and_record', return_value=(True, 9))
|
||||
def test_export_rate_limited_returns_429(_mock_rate_limit, mock_export_csv):
|
||||
client = _client()
|
||||
response = client.get('/api/mid-section-defect/export?start_date=2025-01-01&end_date=2025-01-31')
|
||||
|
||||
assert response.status_code == 429
|
||||
assert response.headers.get('Retry-After') == '9'
|
||||
payload = response.get_json()
|
||||
assert payload['error']['code'] == 'TOO_MANY_REQUESTS'
|
||||
mock_export_csv.assert_not_called()
|
||||
128
tests/test_mid_section_defect_service.py
Normal file
128
tests/test_mid_section_defect_service.py
Normal file
@@ -0,0 +1,128 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
"""Service tests for mid-section defect analysis."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from unittest.mock import patch
|
||||
|
||||
import pandas as pd
|
||||
|
||||
from mes_dashboard.services.mid_section_defect_service import (
|
||||
query_analysis,
|
||||
query_analysis_detail,
|
||||
query_all_loss_reasons,
|
||||
)
|
||||
|
||||
|
||||
def test_query_analysis_invalid_date_format_returns_error():
|
||||
result = query_analysis('2025/01/01', '2025-01-31')
|
||||
|
||||
assert 'error' in result
|
||||
assert 'YYYY-MM-DD' in result['error']
|
||||
|
||||
|
||||
def test_query_analysis_start_after_end_returns_error():
|
||||
result = query_analysis('2025-02-01', '2025-01-31')
|
||||
|
||||
assert 'error' in result
|
||||
assert '起始日期不能晚於結束日期' in result['error']
|
||||
|
||||
|
||||
def test_query_analysis_exceeds_max_days_returns_error():
|
||||
result = query_analysis('2025-01-01', '2025-12-31')
|
||||
|
||||
assert 'error' in result
|
||||
assert '180' in result['error']
|
||||
|
||||
|
||||
@patch('mes_dashboard.services.mid_section_defect_service.query_analysis')
|
||||
def test_query_analysis_detail_returns_sorted_first_page(mock_query_analysis):
|
||||
mock_query_analysis.return_value = {
|
||||
'detail': [
|
||||
{'CONTAINERNAME': 'C', 'DEFECT_RATE': 0.3},
|
||||
{'CONTAINERNAME': 'A', 'DEFECT_RATE': 5.2},
|
||||
{'CONTAINERNAME': 'B', 'DEFECT_RATE': 3.1},
|
||||
]
|
||||
}
|
||||
|
||||
result = query_analysis_detail('2025-01-01', '2025-01-31', page=1, page_size=2)
|
||||
|
||||
assert [row['CONTAINERNAME'] for row in result['detail']] == ['A', 'B']
|
||||
assert result['pagination'] == {
|
||||
'page': 1,
|
||||
'page_size': 2,
|
||||
'total_count': 3,
|
||||
'total_pages': 2,
|
||||
}
|
||||
|
||||
|
||||
@patch('mes_dashboard.services.mid_section_defect_service.query_analysis')
|
||||
def test_query_analysis_detail_clamps_page_to_last_page(mock_query_analysis):
|
||||
mock_query_analysis.return_value = {
|
||||
'detail': [
|
||||
{'CONTAINERNAME': 'A', 'DEFECT_RATE': 9.9},
|
||||
{'CONTAINERNAME': 'B', 'DEFECT_RATE': 8.8},
|
||||
{'CONTAINERNAME': 'C', 'DEFECT_RATE': 7.7},
|
||||
]
|
||||
}
|
||||
|
||||
result = query_analysis_detail('2025-01-01', '2025-01-31', page=10, page_size=2)
|
||||
|
||||
assert result['pagination']['page'] == 2
|
||||
assert result['pagination']['total_pages'] == 2
|
||||
assert len(result['detail']) == 1
|
||||
assert result['detail'][0]['CONTAINERNAME'] == 'C'
|
||||
|
||||
|
||||
@patch('mes_dashboard.services.mid_section_defect_service.query_analysis')
|
||||
def test_query_analysis_detail_returns_error_passthrough(mock_query_analysis):
|
||||
mock_query_analysis.return_value = {'error': '日期格式無效'}
|
||||
|
||||
result = query_analysis_detail('2025-01-01', '2025-01-31', page=1, page_size=200)
|
||||
|
||||
assert result == {'error': '日期格式無效'}
|
||||
|
||||
|
||||
@patch('mes_dashboard.services.mid_section_defect_service.query_analysis')
|
||||
def test_query_analysis_detail_returns_none_on_service_failure(mock_query_analysis):
|
||||
mock_query_analysis.return_value = None
|
||||
|
||||
result = query_analysis_detail('2025-01-01', '2025-01-31', page=1, page_size=200)
|
||||
|
||||
assert result is None
|
||||
|
||||
|
||||
@patch('mes_dashboard.services.mid_section_defect_service.cache_get')
|
||||
@patch('mes_dashboard.services.mid_section_defect_service.read_sql_df')
|
||||
def test_query_all_loss_reasons_cache_hit_skips_query(mock_read_sql_df, mock_cache_get):
|
||||
mock_cache_get.return_value = {'loss_reasons': ['Cached_A', 'Cached_B']}
|
||||
|
||||
result = query_all_loss_reasons()
|
||||
|
||||
assert result == {'loss_reasons': ['Cached_A', 'Cached_B']}
|
||||
mock_read_sql_df.assert_not_called()
|
||||
|
||||
|
||||
@patch('mes_dashboard.services.mid_section_defect_service.cache_get', return_value=None)
|
||||
@patch('mes_dashboard.services.mid_section_defect_service.cache_set')
|
||||
@patch('mes_dashboard.services.mid_section_defect_service.read_sql_df')
|
||||
@patch('mes_dashboard.services.mid_section_defect_service.SQLLoader.load')
|
||||
def test_query_all_loss_reasons_cache_miss_queries_and_caches_sorted_values(
|
||||
mock_sql_load,
|
||||
mock_read_sql_df,
|
||||
mock_cache_set,
|
||||
_mock_cache_get,
|
||||
):
|
||||
mock_sql_load.return_value = 'SELECT ...'
|
||||
mock_read_sql_df.return_value = pd.DataFrame(
|
||||
{'LOSSREASONNAME': ['B_REASON', None, 'A_REASON', 'B_REASON']}
|
||||
)
|
||||
|
||||
result = query_all_loss_reasons()
|
||||
|
||||
assert result == {'loss_reasons': ['A_REASON', 'B_REASON']}
|
||||
mock_cache_set.assert_called_once_with(
|
||||
'mid_section_loss_reasons:None:',
|
||||
{'loss_reasons': ['A_REASON', 'B_REASON']},
|
||||
ttl=86400,
|
||||
)
|
||||
Reference in New Issue
Block a user