Add unit test for crop

prettier on crop test
update snapshot

Author: Doug Toppin

source/constructs/test/__snapshots__/constructs.test.ts.snap

@@ -1167,7 +1167,7 @@ exports[`Serverless Image Handler Stack Snapshot 1`] = `
           "S3Bucket": {
             "Fn::Sub": "cdk-hnb659fds-assets-\${AWS::AccountId}-\${AWS::Region}",
           },
-          "S3Key": "81baf2ab3a41584170190dc0f2ce62f50e091a14cab8fd069cb3aebe903297c5.zip",
+          "S3Key": "c835083515d3d05edc1afeea0c49b2617385f676492fc6dc7e805f829947db72.zip",
         },
         "Description": "sih (v6.1.0): Performs image edits and manipulations",
         "Environment": {
@@ -1621,7 +1621,7 @@ exports[`Serverless Image Handler Stack Snapshot 1`] = `
           },
         ],
         "SourceObjectKeys": [
-          "b17ee622b8fe21bd9a4189063340647fbb783d07261ea136b83db1d58255b0b2.zip",
+          "297994e5975cd83b2ec43f52720181be7d5daf08af8987cc4d5749f99db8f777.zip",
         ],
       },
       "Type": "Custom::CDKBucketDeployment",

source/image-handler/test/image-handler/crop.spec.ts

@@ -10,16 +10,21 @@ import { ImageEdits, StatusCodes } from "../../lib";
 const s3Client = new S3();
 const rekognitionClient = new Rekognition();
 
+// base64 encoded images
+const image_png_1x1 =
+  "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8z8BQDwAEhQGAhKmMIQAAAABJRU5ErkJggg==";
+const image_png_white_5x5 =
+  "iVBORw0KGgoAAAANSUhEUgAAAAUAAAAFAQAAAAClFBtIAAAABGdBTUEAALGPC/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3CculE8AAAAAmJLR0QAAd2KE6QAAAAHdElNRQfnAxYODhUMhxdmAAAADElEQVQI12P4wQCFABhCBNn4i/hQAAAAJXRFWHRkYXRlOmNyZWF0ZQAyMDIzLTAzLTIyVDE0OjE0OjIxKzAwOjAwtK8ALAAAACV0RVh0ZGF0ZTptb2RpZnkAMjAyMy0wMy0yMlQxNDoxNDoyMSswMDowMMXyuJAAAAAASUVORK5CYII=";
+const image_png_white_1x1 =
+  "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAIAAACQd1PeAAAACXBIWXMAAAsTAAALEwEAmpwYAAAADElEQVR4nGP4//8/AAX+Av4N70a4AAAAAElFTkSuQmCC";
+
 describe("crop", () => {
   it("Should pass if a cropping area value is out of bounds", async () => {
     // Arrange
-    const originalImage = Buffer.from(
-      "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8z8BQDwAEhQGAhKmMIQAAAABJRU5ErkJggg==",
-      "base64"
-    );
+    const originalImage = Buffer.from(image_png_1x1, "base64");
     const image = sharp(originalImage, { failOnError: false }).withMetadata();
     const edits: ImageEdits = {
-      crop: { left: 0, right: 0, width: 100, height: 100 },
+      crop: { left: 0, top: 0, width: 100, height: 100 },
     };
 
     // Act
@@ -36,4 +41,53 @@ describe("crop", () => {
       });
     }
   });
+
+  // confirm that crops perform as expected
+  it("Should pass with a standard crop", async () => {
+    // 5x5 png
+    const originalImage = Buffer.from(image_png_white_5x5, "base64");
+    const image = sharp(originalImage, { failOnError: false }).withMetadata();
+    const edits: ImageEdits = {
+      crop: { left: 0, top: 0, width: 1, height: 1 },
+    };
+
+    // crop an image and compare with the result expected
+    try {
+      const imageHandler = new ImageHandler(s3Client, rekognitionClient);
+      const result = await imageHandler.applyEdits(image, edits, false);
+      const resultBuffer = await result.toBuffer();
+      expect(resultBuffer).toEqual(Buffer.from(image_png_white_1x1, "base64"));
+    } catch (error) {
+      console.log(error);
+      throw error;
+    }
+  });
+
+  // confirm that an invalid attribute sharp crop request containing *right* rather than *top* returns as a cropping error,
+  // note that this only confirms the behavior of the image-handler in this case,
+  // it is not an accurate description of the actual error
+  it("Should fail with an invalid crop request", async () => {
+    // 5x5 png
+    const originalImage = Buffer.from(image_png_white_5x5, "base64");
+    const image = sharp(originalImage, { failOnError: false }).withMetadata();
+    const edits: ImageEdits = {
+      crop: { left: 0, right: 0, width: 1, height: 1 },
+    };
+
+    // crop an image and compare with the result expected
+    try {
+      const imageHandler = new ImageHandler(s3Client, rekognitionClient);
+      const result = await imageHandler.applyEdits(image, edits, false);
+      const resultBuffer = await result.toBuffer();
+      expect(resultBuffer).toEqual(Buffer.from(image_png_white_1x1, "base64"));
+    } catch (error) {
+      // Assert
+      expect(error).toMatchObject({
+        status: StatusCodes.BAD_REQUEST,
+        code: "Crop::AreaOutOfBounds",
+        message:
+          "The cropping area you provided exceeds the boundaries of the original image. Please try choosing a correct cropping value.",
+      });
+    }
+  });
 });