> Documentation index: https://www.gooddata.ai/docs/gooddata-ui/llms.txt lists every page of these docs as Markdown.

# defFingerprint()

- Package: [@gooddata/sdk-model](https://www.gooddata.ai/docs/gooddata-ui/latest/api-reference/sdk-model/index.md)
- Kind: function
- Source: https://github.com/gooddata/gooddata-ui-sdk/blob/rel/11.64/libs/sdk-model/src/execution/executionDefinition/index.ts

Calculates fingerprint for the execution definition.

**Signature:**

```typescript
export declare function defFingerprint(def: IExecutionDefinition): string;
```

## Parameters

| Parameter | Type | Description |
| --- | --- | --- |
| def | [IExecutionDefinition](https://www.gooddata.ai/docs/gooddata-ui/latest/api-reference/sdk-model/sdk-model.iexecutiondefinition/index.md) | execution definition |

**Returns:**

string

## Remarks

Fingerprinting is used as an \_approximate\_, quick, first-level assessment whether two execution definitions are or are not effectively same = they lead to the same computation on the backend.

The contract and the approximate nature of the fingerprint can be described as follows:

- If two execution definitions have the same fingerprint, then they definitely are effectively the same  from the result calculation point of view and the backend will perform the same computation for them.

- If two execution definition have different fingerprint, they MAY OR MAY NOT lead to different execution. Or  more concrete: two executions with two different fingerprints MAY lead to the same execution and same results.

While not optimal, this contract allows for safe usage of fingerprints to determine whether two execution definitions have changed. For instance it can be used in React lifecycle methods (shouldComponentUpdate) or for client-side caching.