From abd24a42b84e22670b2f75d380438e8feee5fa14 Mon Sep 17 00:00:00 2001
From: Ardis Lu <ardisglu@gmail.com>
Date: Wed, 9 Jul 2025 21:33:12 -0700
Subject: [PATCH] Fall back on `name` if `displayName` is undefined

This behavior is useful when passing rows to `CSVDenormalizer` after a transformation *other* than `CSVNormalizer` (which automatically creates `displayName`).
---
 src/normalization.js       |  2 +-
 test/normalization.test.js | 27 +++++++++++++++++++++++++++
 test/utils.js              |  4 ++--
 3 files changed, 30 insertions(+), 3 deletions(-)

diff --git a/src/normalization.js b/src/normalization.js
index 7f2fd3d..45a864a 100644
--- a/src/normalization.js
+++ b/src/normalization.js
@@ -308,7 +308,7 @@ export class CSVDenormalizer extends TransformStream {
         const row = JSON.parse(chunk);
         if (firstRow) {
           firstRow = false;
-          controller.enqueue(JSON.stringify(row.map(f => f.displayName)));
+          controller.enqueue(JSON.stringify(row.map(f => f?.displayName ?? f.name)));
         }
         controller.enqueue(JSON.stringify(row.map(f => f.value)));
       }
diff --git a/test/normalization.test.js b/test/normalization.test.js
index 1d355c1..c12577c 100644
--- a/test/normalization.test.js
+++ b/test/normalization.test.js
@@ -352,6 +352,33 @@ suite('CSVNormalizer', { concurrency: true }, () => {
   });
 });
 
+suite('CSVDenormalizer', { concurrency: true }, () => {
+  test('can process normalized rows', { concurrency: true }, async () => {
+    await createCSVMockStream([
+      [{ displayName: 'Column A', value: 'a1' }, { displayName: 'Column B', value: 'b1' }],
+      [{ displayName: 'Column A', value: 'a2' }, { displayName: 'Column B', value: 'b2' }]
+    ])
+      .pipeThrough(new CSVDenormalizer())
+      .pipeTo(csvStreamEqualWritable([
+        ['Column A', 'Column B'],
+        ['a1', 'b1'],
+        ['a2', 'b2']
+      ]));
+  });
+  test('falls back on name if displayName is undefined', { concurrency: true }, async () => {
+    await createCSVMockStream([
+      [{ name: 'Column A', value: 'a1' }, { displayName: 'Column B', value: 'b1' }],
+      [{ displayName: 'Column A', value: 'a2' }, { name: 'Column B', value: 'b2' }]
+    ])
+      .pipeThrough(new CSVDenormalizer())
+      .pipeTo(csvStreamEqualWritable([
+        ['Column A', 'Column B'],
+        ['a1', 'b1'],
+        ['a2', 'b2']
+      ]));
+  });
+});
+
 suite('CSVNormalizer and CSVDenormalizer end-to-end', { concurrency: true }, () => {
   test('can normalize', { concurrency: true }, async () => {
     const headers = [
diff --git a/test/utils.js b/test/utils.js
index a56f739..b14a1c4 100644
--- a/test/utils.js
+++ b/test/utils.js
@@ -132,8 +132,8 @@ export function assertSleep(context, expected) {
 /**
  * Simulate a stream of CSV data for test mocking purposes.
  * 
- * @param {Array<Array<string>>} data A 2-D array representing the CSV file to mock, where each inner array
- * is a row of the CSV.
+ * @param {Array<Array<string>>|Array<Array<Object>>} data A 2-D array representing the CSV file to mock, where
+ * each inner array is a row of the CSV.
  * @returns {ReadableStream} A `ReadableStream` where each row is emitted as a separate chunk.
  */
 export function createCSVMockStream(data) {
-- 
2.47.3