databricks.getMlflowModels

import * as pulumi from "@pulumi/pulumi";
import * as databricks from "@pulumi/databricks";

const this = databricks.getMlflowModels({});
export const model = _this;

import pulumi
import pulumi_databricks as databricks

this = databricks.get_mlflow_models()
pulumi.export("model", this)

package main

import (
	"github.com/pulumi/pulumi-databricks/sdk/go/databricks"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		this, err := databricks.GetMlflowModels(ctx, &databricks.GetMlflowModelsArgs{}, nil)
		if err != nil {
			return err
		}
		ctx.Export("model", this)
		return nil
	})
}

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Databricks = Pulumi.Databricks;

return await Deployment.RunAsync(() => 
{
    var @this = Databricks.GetMlflowModels.Invoke();

    return new Dictionary<string, object?>
    {
        ["model"] = @this,
    };
});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.databricks.DatabricksFunctions;
import com.pulumi.databricks.inputs.GetMlflowModelsArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        final var this = DatabricksFunctions.getMlflowModels();

        ctx.export("model", this_);
    }
}

variables:
  this:
    fn::invoke:
      Function: databricks:getMlflowModels
      Arguments: {}
outputs:
  model: ${this}

function getMlflowModels(args: GetMlflowModelsArgs, opts?: InvokeOptions): Promise<GetMlflowModelsResult>
function getMlflowModelsOutput(args: GetMlflowModelsOutputArgs, opts?: InvokeOptions): Output<GetMlflowModelsResult>

def get_mlflow_models(names: Optional[Sequence[str]] = None,
                      opts: Optional[InvokeOptions] = None) -> GetMlflowModelsResult
def get_mlflow_models_output(names: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
                      opts: Optional[InvokeOptions] = None) -> Output[GetMlflowModelsResult]

func GetMlflowModels(ctx *Context, args *GetMlflowModelsArgs, opts ...InvokeOption) (*GetMlflowModelsResult, error)
func GetMlflowModelsOutput(ctx *Context, args *GetMlflowModelsOutputArgs, opts ...InvokeOption) GetMlflowModelsResultOutput

public static class GetMlflowModels 
{
    public static Task<GetMlflowModelsResult> InvokeAsync(GetMlflowModelsArgs args, InvokeOptions? opts = null)
    public static Output<GetMlflowModelsResult> Invoke(GetMlflowModelsInvokeArgs args, InvokeOptions? opts = null)
}

public static CompletableFuture<GetMlflowModelsResult> getMlflowModels(GetMlflowModelsArgs args, InvokeOptions options)
// Output-based functions aren't available in Java yet

fn::invoke:
  function: databricks:index/getMlflowModels:getMlflowModels
  arguments:
    # arguments dictionary