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# flow_runs
# `prefect.deployments.flow_runs`
## Functions
### `arun_deployment`
```python theme={null}
arun_deployment(name: Union[str, UUID], client: Optional['PrefectClient'] = None, parameters: Optional[dict[str, Any]] = None, scheduled_time: Optional[datetime] = None, flow_run_name: Optional[str] = None, timeout: Optional[float] = None, poll_interval: Optional[float] = 5, tags: Optional[Iterable[str]] = None, idempotency_key: Optional[str] = None, work_queue_name: Optional[str] = None, as_subflow: Optional[bool] = True, job_variables: Optional[dict[str, Any]] = None) -> 'FlowRun'
```
Asynchronously create a flow run for a deployment and return it after completion or a timeout.
By default, this function blocks until the flow run finishes executing.
Specify a timeout (in seconds) to wait for the flow run to execute before
returning flow run metadata. To return immediately, without waiting for the
flow run to execute, set `timeout=0`.
Note that if you specify a timeout, this function will return the flow run
metadata whether or not the flow run finished executing.
If called within a flow or task, the flow run this function creates will
be linked to the current flow run as a subflow. Disable this behavior by
passing `as_subflow=False`.
**Args:**
* `name`: The deployment id or deployment name in the form:
`"flow name/deployment name"`
* `client`: An optional PrefectClient to use for API requests.
* `parameters`: Parameter overrides for this flow run. Merged with the deployment
defaults.
* `scheduled_time`: The time to schedule the flow run for, defaults to scheduling
the flow run to start now.
* `flow_run_name`: A name for the created flow run
* `timeout`: The amount of time to wait (in seconds) for the flow run to
complete before returning. Setting `timeout` to 0 will return the flow
run metadata immediately. Setting `timeout` to None will allow this
function to poll indefinitely. Defaults to None.
* `poll_interval`: The number of seconds between polls
* `tags`: A list of tags to associate with this flow run; tags can be used in
automations and for organizational purposes.
* `idempotency_key`: A unique value to recognize retries of the same run, and
prevent creating multiple flow runs.
* `work_queue_name`: The name of a work queue to use for this run. Defaults to
the default work queue for the deployment.
* `as_subflow`: Whether to link the flow run as a subflow of the current
flow or task run.
* `job_variables`: A dictionary of dot delimited infrastructure overrides that
will be applied at runtime; for example `env.CONFIG_KEY=config_value` or
`namespace='prefect'`
### `run_deployment`
```python theme={null}
run_deployment(name: Union[str, UUID], client: Optional['PrefectClient'] = None, parameters: Optional[dict[str, Any]] = None, scheduled_time: Optional[datetime] = None, flow_run_name: Optional[str] = None, timeout: Optional[float] = None, poll_interval: Optional[float] = 5, tags: Optional[Iterable[str]] = None, idempotency_key: Optional[str] = None, work_queue_name: Optional[str] = None, as_subflow: Optional[bool] = True, job_variables: Optional[dict[str, Any]] = None) -> 'FlowRun'
```
Create a flow run for a deployment and return it after completion or a timeout.
This function will dispatch to `arun_deployment` when called from an async context.
By default, this function blocks until the flow run finishes executing.
Specify a timeout (in seconds) to wait for the flow run to execute before
returning flow run metadata. To return immediately, without waiting for the
flow run to execute, set `timeout=0`.
Note that if you specify a timeout, this function will return the flow run
metadata whether or not the flow run finished executing.
If called within a flow or task, the flow run this function creates will
be linked to the current flow run as a subflow. Disable this behavior by
passing `as_subflow=False`.
**Args:**
* `name`: The deployment id or deployment name in the form:
`"flow name/deployment name"`
* `client`: An optional PrefectClient to use for API requests. This is ignored
when called from a synchronous context.
* `parameters`: Parameter overrides for this flow run. Merged with the deployment
defaults.
* `scheduled_time`: The time to schedule the flow run for, defaults to scheduling
the flow run to start now.
* `flow_run_name`: A name for the created flow run
* `timeout`: The amount of time to wait (in seconds) for the flow run to
complete before returning. Setting `timeout` to 0 will return the flow
run metadata immediately. Setting `timeout` to None will allow this
function to poll indefinitely. Defaults to None.
* `poll_interval`: The number of seconds between polls
* `tags`: A list of tags to associate with this flow run; tags can be used in
automations and for organizational purposes.
* `idempotency_key`: A unique value to recognize retries of the same run, and
prevent creating multiple flow runs.
* `work_queue_name`: The name of a work queue to use for this run. Defaults to
the default work queue for the deployment.
* `as_subflow`: Whether to link the flow run as a subflow of the current
flow or task run.
* `job_variables`: A dictionary of dot delimited infrastructure overrides that
will be applied at runtime; for example `env.CONFIG_KEY=config_value` or
`namespace='prefect'`
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