> ## Documentation Index > Fetch the complete documentation index at: https://docs.prefect.io/llms.txt > Use this file to discover all available pages before exploring further. # core # `prefect.deployments.steps.core` Core primitives for running Prefect deployment steps. Deployment steps are YAML representations of Python functions along with their inputs. Whenever a step is run, the following actions are taken: * The step's inputs and block / variable references are resolved (see [the `prefect deploy` documentation](https://docs.prefect.io/v3/how-to-guides/deployments/prefect-yaml#templating-options) for more details) * The step's function is imported; if it cannot be found, the `requires` keyword is used to install the necessary packages * The step's function is called with the resolved inputs * The step's output is returned and used to resolve inputs for subsequent steps ## Functions ### `run_step` ```python theme={null} run_step(step: dict[str, Any], upstream_outputs: dict[str, Any] | None = None) -> dict[str, Any] ``` Runs a step, returns the step's output. Steps are assumed to be in the format `{"importable.func.name": {"kwarg1": "value1", ...}}`. The 'id and 'requires' keywords are reserved for specific purposes and will be removed from the inputs before passing to the step function: This keyword is used to specify packages that should be installed before running the step. ### `run_steps` ```python theme={null} run_steps(steps: list[dict[str, Any]], upstream_outputs: dict[str, Any] | None = None, print_function: Any = print, deployment: Any | None = None, flow_run: Any | None = None, logger: Any | None = None) -> dict[str, Any] ``` ## Classes ### `StepExecutionError` Raised when a step fails to execute. Built with [Mintlify](https://mintlify.com).