///

---

Imaginez que vous êtes l'ordinateur / le programme 🤖 dans cette histoire.

Pendant que vous faites la queue, vous être simplement inactif 😴, attendant votre tour, ne faisant rien de "productif". Mais la queue est rapide car le serveur 💁 prend seulement les commandes (et ne les prépare pas), donc tout va bien.

	DB.Model(&product).Updates(Product3{Code: "L1214"})
	if product.Price != 270 || product.Code != "L1214" {
		t.Errorf("invalid data after update, got %+v", product)
	}

	// Code changed, price should changed
	DB.Model(&product).Select("Name", "Code", "Price").Updates(Product3{Name: "Product New4", Code: ""})
	if product.Name != "Product New4" || product.Price != 320 || product.Code != "" {
		t.Errorf("invalid data after update, got %+v", product)
	}

	}

	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{

		t.Fatalf("Should not find deleted profile")
	}
}

func TestFullSaveAssociations(t *testing.T) {
	coupon := &Coupon{
		AppliesToProduct: []*CouponProduct{
			{ProductId: "full-save-association-product1"},
		},
		AmountOff:  10,
		PercentOff: 0.0,
	}

	err := DB.
		Session(&gorm.Session{FullSaveAssociations: true}).
		Create(coupon).Error
	if err != nil {

      // 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));
    }

   * }
   * }
   *
   * <p>Note that if any input list is empty, the Cartesian product will also be empty. If no lists
   * 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 lists of size {@code m, n, p} is a

    // 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}

## Opinions { #opinions }

"_[...] 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>

---

## Opinions

"_[...] 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>

---

**build** the client, it will error out if you have any **mismatch** in the data used.

So, you would **detect many errors** very early in the development cycle instead of having to wait for the errors to show up to your final users in production and then trying to debug where the problem is. ✨...