product2 := Product3{Name: "Product", Price: 0}
	DB.Session(&gorm.Session{SkipHooks: true}).Create(&product2)

	if product2.Price != 0 {
		t.Errorf("invalid price after create without hooks, got %+v", product2)
	}
}

func TestHooksForSlice(t *testing.T) {
	DB.Migrator().DropTable(&Product3{})
	DB.AutoMigrate(&Product3{})

	products := []*Product3{
		{Name: "Product-1", Price: 100},

	}

	product, err := schema.Parse(&Product{}, &sync.Map{}, schema.NamingStrategy{})
	if err != nil {
		t.Fatalf("failed to parse product struct with composite primary key, got error %v", err)
	}

	prioritizedPrimaryField := schema.Field{

      // If it won't fit in a long, then we store off the intermediate product.
      if (normalizedBits + productBits >= Long.SIZE) {
        bignums.add(BigInteger.valueOf(product));
        product = 1;
        productBits = 0;
      }
      product *= normalizedNum;
      productBits = LongMath.log2(product, FLOOR) + 1;
    }
    // Check for leftovers.
    if (product > 1) {
      bignums.add(BigInteger.valueOf(product));
    }

//     that gets offloaded). The same registry key setting overwrites the storage-defined setting.
//     Optional value, default 64, range: 1-unlimited
//
//   - <S3MultiObjectDeleteLimit>
//     Some of the Veeam products use Multi Delete operations. This setting can reduce how many objects are included in one
//     multi-delete operation. The same registry key setting overwrites the storage-defined setting.

    // vol. 2, Knuth, 4.2.2, (16) to the two-variable case. We have two value series x_i and y_i.
    // We define the arithmetic means X_n = 1/n \sum_{i=1}^n x_i, and Y_n = 1/n \sum_{i=1}^n y_i.
    // We also define the sum of the products of the differences from the means
    //           C_n = \sum_{i=1}^n x_i y_i - n X_n Y_n
    // for all n >= 1. Then for all n > 1:
    //       C_{n-1} = \sum_{i=1}^{n-1} x_i y_i - (n-1) X_{n-1} Y_{n-1}

   * }
   * }
   *
   * <p>Note that if any input set is empty, the Cartesian product will also be empty. If no sets at
   * all are provided (an empty list), the resulting Cartesian product has one element, an empty
   * list (counter-intuitive, but mathematically consistent).
   *
   * <p><i>Performance notes:</i> while the cartesian product of sets of size {@code m, n, p} is a

in the documentation and/or other materials provided with the
distribution.
   * Neither the name of Google Inc. nor the names of its
contributors may be used to endorse or promote products derived from
this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT

## Враження

"_[...] I'm using **FastAPI** a ton these days. [...] I'm actually planning to use it for all of my team's **ML services at Microsoft**. Some of them are getting integrated into the core **Windows** product and some **Office** products._"

<div style="text-align: right; margin-right: 10%;">Kabir Khan - <strong>Microsoft</strong> <a href="https://github.com/fastapi/fastapi/pull/26" target="_blank"><small>(ref)</small></a></div>

---

            assertNull(nc.dc);
        }
    }

    @Nested
    @DisplayName("toString() Tests")
    class ToStringTests {

        @Test
        @DisplayName("toString with valid data produces expected format")
        void testToStringWithValidData() {
            byte[] challenge = new byte[] { (byte) 0x01, (byte) 0x02, (byte) 0x03, (byte) 0xFF };
            UniAddress dc = mock(UniAddress.class);

        hmac.engineUpdate(TEST_DATA, 0, TEST_DATA.length);
        byte[] result = hmac.engineDigest();

        assertNotNull(result);
        assertEquals(16, result.length); // MD5 produces 16 bytes
    }

    @Test
    void testEngineDigestWithBuffer() {
        // Test engineDigest(byte[] buf, int offset, int len)
        HMACT64 hmac = new HMACT64(TEST_KEY);