# Materializing artifacts

You can materialize an artifact by executing the task or workflow that emits the artifact.

In the example below, to materialize the `BasicArtifact` artifact, the `t1` task must be executed. The `wf` workflow runs the `t1` task three times with different values for the `key1` partition each time.
Note that each time `t1` is executed, it emits a new version of the `BasicArtifact` artifact.

> [!NOTE]
> To use the example code on this page, you will need to add your `registry` to the `pandas_image` ImageSpec block.

```python
# partition_keys_runtime.py

from datetime import datetime

import pandas as pd
import union
from flytekit.core.artifact import Inputs, Granularity
from typing_extensions import Annotated

pandas_image = union.ImageSpec(
    packages=["pandas==2.2.2"]
)

BasicArtifact = union.Artifact(
    name="my_basic_artifact",
    time_partitioned=True,
    time_partition_granularity=Granularity.HOUR,
    partition_keys=["key1"]
)

@union.task(container_image=pandas_image)
def t1(
    key1: str, date: datetime
) -> Annotated[pd.DataFrame, BasicArtifact(key1=Inputs.key1)]:
    df = pd.DataFrame({"col1": [1, 2, 3], "col2": ["a", "b", "c"]})
    return BasicArtifact.create_from(
        df,
        time_partition=date
    )

@union.workflow
def wf():
    run_date = datetime.now()
    values = ["value1", "value2", "value3"]
    for value in values:
        t1(key1=value, date=run_date)
```

> [!NOTE]
> You can also materialize an artifact by executing the `create_artifact` method of `UnionRemote`.
> For more information, see the [UnionRemote documentation](https://www.union.ai/docs/v1/union/user-guide/core-concepts/development-cycle/union-remote).

---
**Source**: https://github.com/unionai/unionai-docs/blob/main/content/user-guide/core-concepts/artifacts/materializing-artifacts.md
**HTML**: https://www.union.ai/docs/v1/union/user-guide/core-concepts/artifacts/materializing-artifacts/