> ## Documentation Index
> Fetch the complete documentation index at: https://upstash.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Fetch

## Method

The `fetch` method allows you to retrieve vectors from the index based on their identifiers. It takes the following input parameters:

* `ids`: A string or a list of strings representing the identifiers of the vectors to be fetched.
* `prefix`: A string prefix to match vector IDs. All vectors with IDs that start with this prefix will be retrieved.
* `include_vectors`: A boolean flag indicating whether to include vectors in the fetch results.
* `include_metadata`: A boolean flag indicating whether to include metadata in the fetch results.
* `include_data`: A boolean flag indicating whether to include data in the fetch results.
* `namespace`: The namespace to use. When not specified, the default namespace is used.

As a response, following field is returned:

* `vectors`: A list containing information for each fetched vector, including `id`, `vector`, `sparse_vector`, `metadata`, and `data`.

## Fetch Example

```python theme={"system"}
from upstash_vector import Index

index = Index.from_env()

# Specify the identifiers of vectors to be fetched
ids_to_fetch = ["id-1", "id-2", "id-3"]

# Fetch the specified vectors with vectors and metadata included
fetch_result = index.fetch(
    ids=ids_to_fetch,
    include_vectors=True,
    include_metadata=True,
    include_data=True,
)

# Display the fetched vectors
for vector_info in fetch_result:
    print("ID:", vector_info.id)
    print("Vector:", vector_info.vector)
    print("Metadata:", vector_info.metadata)
    print("Data:", vector_info.data)
```

Alternatively, you can fetch a singular vector:

```python theme={"system"}
index.fetch("id-4")
```

Also, you can specify a namespace to operate on. When no namespace
is provided, the default namespace will be used.

```python theme={"system"}
index.fetch("id-4", namespace="ns")
```

## Fetch with id prefix

This will fetch all vectors with IDs that start with the prefix.

<Warning>
  For fetching larger datasets with id prefix, prefer using the paginated
  `range` command to prevent timeouts.
</Warning>

```python theme={"system"}
index.fetch(prefix="id-")
```