> For the complete documentation index, see [llms.txt](https://gilad-rubin.gitbook.io/hypster/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://gilad-rubin.gitbook.io/hypster/integrations/hamilton.md).

# Hamilton

Hamilton and Hypster can be used together by keeping graph construction and parameter selection separate:

* Use Hypster to select a small, replayable set of workflow parameters.
* Pass the instantiated value into your Hamilton driver, module, or execution wrapper.
* Log `instantiate_with_params(...).params` next to Hamilton run metadata.

## Shape

{% code overflow="wrap" %}

```python
from hypster import HP, instantiate_with_params

def hamilton_run_config(hp: HP):
    dataset = hp.select(["sample", "warehouse"], name="dataset", default="sample", options_only=True)
    feature_set = hp.select(["basic", "extended"], name="feature_set", default="basic", options_only=True)
    model_family = hp.select(["linear", "forest"], name="model_family", default="linear", options_only=True)

    return {
        "dataset": dataset,
        "feature_set": feature_set,
        "model_family": model_family,
    }

run = instantiate_with_params(
    hamilton_run_config,
    values={"dataset": "warehouse", "feature_set": "extended"},
)

# driver.execute(..., inputs=run.value)
# tracker.log_params(run.params)
```

{% endcode %}

## Execution Boundary

Use `run.value` at the Hamilton execution boundary, and log `run.params` beside Hamilton metadata:

{% code overflow="wrap" %}

```python
# from hamilton import driver
# import my_hamilton_nodes

run = instantiate_with_params(
    hamilton_run_config,
    values={"dataset": "warehouse", "feature_set": "extended"},
)

# dr = driver.Builder().with_modules(my_hamilton_nodes).build()
# result = dr.execute(
#     ["trained_model", "validation_metrics"],
#     inputs=run.value,
# )
# tracker.log_params(run.params)
# tracker.log_metrics(result["validation_metrics"])
```

{% endcode %}

Use Hamilton `inputs=` for runtime choices such as dataset, feature set, and model family. Use Hamilton `config=` only for static graph-construction choices in your Hamilton project. Hypster stays outside Hamilton's graph; it selects and records the values that you pass into the graph.

Hypster does not ship a Hamilton-specific adapter today. This page documents the integration pattern for projects that already use Hamilton.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://gilad-rubin.gitbook.io/hypster/integrations/hamilton.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.