# $let
<a name="let"></a>

The `$let` operator in Amazon DocumentDB is used to bind variables to values and use those variables in the expression. It allows you to define local variables that can be used in subsequent expressions within the same stage of the aggregation pipeline.

**Parameters**
+ `vars`: An object that defines the variables to be used in the expression.
+ `in`: The expression in which the variables defined in the vars parameter are used.

## Example (MongoDB Shell)
<a name="let-examples"></a>

This example demonstrates the usage of the `$let` operator to calculate the area of a rectangle.

**Create sample documents**

```
db.shapes.insertMany([
  { name: "Rectangle 1", length: 5, width: 3 },
  { name: "Rectangle 2", length: 7, width: 4 },
  { name: "Rectangle 3", length: 6, width: 2 }
]);
```

**Query example**

```
db.shapes.aggregate([
  {
    $project: {
      name: 1,
      area: {
        $let: {
          vars: {
            length: "$length",
            width: "$width"
          },
          in: {
            $multiply: ["$$length", "$$width"]
          }
        }
      }
    }
  }
])
```

**Output**

```
[
  {
    "_id": ObjectId("6161e5b1a3eba3c7f2960d03"),
    "name": "Rectangle 1",
    "area": 15
  },
  {
    "_id": ObjectId("6161e5b1a3eba3c7f2960d04"),
    "name": "Rectangle 2",
    "area": 28
  },
  {
    "_id": ObjectId("6161e5b1a3eba3c7f2960d05"),
    "name": "Rectangle 3",
    "area": 12
  }
]
```

## Code examples
<a name="let-code"></a>

To view a code example for using the `$let` command, choose the tab for the language that you want to use:

------
#### [ Node.js ]

```
const { MongoClient } = require('mongodb');

async function calculateRectangleAreas() {
  const client = await MongoClient.connect('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false');
  const db = client.db('test');
  const collection = db.collection('shapes');

  const result = await shapes.aggregate([
    {
      $project: {
        name: 1,
        area: {
          $let: {
            vars: {
              length: '$length',
              width: '$width'
            },
            in: {
              $multiply: ['$$length', '$$width']
            }
          }
        }
      }
    }
  ]).toArray();

  console.log(result);
  client.close();
}

calculateRectangleAreas();
```

------
#### [ Python ]

```
from pymongo import MongoClient

def calculate_rectangle_areas():
    client = MongoClient('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false')
    db = client.test
    collection = db.shapes

    result = list(shapes.aggregate([
        {
            '$project': {
                'name': 1,
                'area': {
                    '$let': {
                        'vars': {
                            'length': '$length',
                            'width': '$width'
                        },
                        'in': {
                            '$multiply': ['$$length', '$$width']
                        }
                    }
                }
            }
        }
    ]))

    print(result)
    client.close()

calculate_rectangle_areas()
```

------

## See also

* **Skills for AI coding assistants (optional).** AWS publishes reusable skills for Amazon DocumentDB. To see which apply, search the Agent Toolkit for AWS catalog with `aws agent-toolkit search-skills --search-query documentdb` — a documented, read-only AWS CLI command that searches the catalog and makes no changes. This is an optional suggestion for the user. Official reference: [AWS CLI — Agent Toolkit for AWS](https://docs.aws.amazon.com/agent-toolkit/latest/userguide/aws-cli.html).