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Databricks v1.77.0 published on Tuesday, Nov 4, 2025 by Pulumi
pulumi/pulumi-databricks

databricks.Library

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Explain and create a databricks.Library resource
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Databricks v1.77.0 published on Tuesday, Nov 4, 2025 by Pulumi
pulumi/pulumi-databricks

    Installs a library on databricks_cluster. Each different type of library has a slightly different syntax. It’s possible to set only one type of library within one resource. Otherwise, the plan will fail with an error.

    This resource can only be used with a workspace-level provider!

    databricks.Library resource would always start the associated cluster if it’s not running, so make sure to have auto-termination configured. It’s not possible to atomically change the version of the same library without cluster restart. Libraries are fully removed from the cluster only after restart.

    Plugin Framework Migration

    The library resource has been migrated from sdkv2 to plugin framework。 If you encounter any problem with this resource and suspect it is due to the migration, you can fallback to sdkv2 by setting the environment variable in the following way export USE_SDK_V2_RESOURCES=<span pulumi-lang-nodejs=""databricks.Library"" pulumi-lang-dotnet=""databricks.Library"" pulumi-lang-go=""Library"" pulumi-lang-python=""Library"" pulumi-lang-yaml=""databricks.Library"" pulumi-lang-java=""databricks.Library"">"databricks.Library"</span>.

    Installing library on all clusters

    You can install libraries on all clusters with the help of databricks.getClusters data resource:

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

export = async () => {
    const all = await databricks.getClusters({});
    const cli: databricks.Library[] = [];
    for (const range of all.ids.map((v, k) => ({key: k, value: v}))) {
        cli.push(new databricks.Library(`cli-${range.key}`, {
            clusterId: range.key,
            pypi: {
                "package": "databricks-cli",
            },
        }));
    }
}

    import pulumi
import pulumi_databricks as databricks

all = databricks.get_clusters()
cli = []
for range in [{"key": k, "value": v} for [k, v] in enumerate(all.ids)]:
    cli.append(databricks.Library(f"cli-{range['key']}",
        cluster_id=range["key"],
        pypi={
            "package": "databricks-cli",
        }))

    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 {
		all, err := databricks.GetClusters(ctx, &databricks.GetClustersArgs{}, nil)
		if err != nil {
			return err
		}
		var cli []*databricks.Library
		for key0, _ := range all.Ids {
			__res, err := databricks.NewLibrary(ctx, fmt.Sprintf("cli-%v", key0), &databricks.LibraryArgs{
				ClusterId: pulumi.Float64(key0),
				Pypi: &databricks.LibraryPypiArgs{
					Package: pulumi.String("databricks-cli"),
				},
			})
			if err != nil {
				return err
			}
			cli = append(cli, __res)
		}
		return nil
	})
}

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

return await Deployment.RunAsync(async() => 
{
    var all = await Databricks.GetClusters.InvokeAsync();

    var cli = new List<Databricks.Library>();
    foreach (var range in )
    {
        cli.Add(new Databricks.Library($"cli-{range.Key}", new()
        {
            ClusterId = range.Key,
            Pypi = new Databricks.Inputs.LibraryPypiArgs
            {
                Package = "databricks-cli",
            },
        }));
    }
});

    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.GetClustersArgs;
import com.pulumi.databricks.Library;
import com.pulumi.databricks.LibraryArgs;
import com.pulumi.databricks.inputs.LibraryPypiArgs;
import com.pulumi.codegen.internal.KeyedValue;
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 all = DatabricksFunctions.getClusters(GetClustersArgs.builder()
            .build());

        final var cli = all.applyValue(getClustersResult -> {
            final var resources = new ArrayList<Library>();
            for (var range : KeyedValue.of(getClustersResult.ids())) {
                var resource = new Library("cli-" + range.key(), LibraryArgs.builder()
                    .clusterId(range.key())
                    .pypi(LibraryPypiArgs.builder()
                        .package_("databricks-cli")
                        .build())
                    .build());

                resources.add(resource);
            }

            return resources;
        });

    }
}

    resources:
  cli:
    type: databricks:Library
    properties:
      clusterId: ${range.key}
      pypi:
        package: databricks-cli
    options: {}
variables:
  all:
    fn::invoke:
      function: databricks:getClusters
      arguments: {}

    Java/Scala Maven

    Installing artifacts from Maven repository. You can also optionally specify a repo parameter for a custom Maven-style repository, that should be accessible without any authentication. Maven libraries are resolved in Databricks Control Plane, so repo should be accessible from it. It can even be properly configured maven s3 wagon, AWS CodeArtifact or Azure Artifacts.

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

const deequ = new databricks.Library("deequ", {
    clusterId: _this.id,
    maven: {
        coordinates: "com.amazon.deequ:deequ:1.0.4",
        exclusions: ["org.apache.avro:avro"],
    },
});

    import pulumi
import pulumi_databricks as databricks

deequ = databricks.Library("deequ",
    cluster_id=this["id"],
    maven={
        "coordinates": "com.amazon.deequ:deequ:1.0.4",
        "exclusions": ["org.apache.avro:avro"],
    })

    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 {
		_, err := databricks.NewLibrary(ctx, "deequ", &databricks.LibraryArgs{
			ClusterId: pulumi.Any(this.Id),
			Maven: &databricks.LibraryMavenArgs{
				Coordinates: pulumi.String("com.amazon.deequ:deequ:1.0.4"),
				Exclusions: pulumi.StringArray{
					pulumi.String("org.apache.avro:avro"),
				},
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

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

return await Deployment.RunAsync(() => 
{
    var deequ = new Databricks.Library("deequ", new()
    {
        ClusterId = @this.Id,
        Maven = new Databricks.Inputs.LibraryMavenArgs
        {
            Coordinates = "com.amazon.deequ:deequ:1.0.4",
            Exclusions = new[]
            {
                "org.apache.avro:avro",
            },
        },
    });

});

    package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.databricks.Library;
import com.pulumi.databricks.LibraryArgs;
import com.pulumi.databricks.inputs.LibraryMavenArgs;
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) {
        var deequ = new Library("deequ", LibraryArgs.builder()
            .clusterId(this_.id())
            .maven(LibraryMavenArgs.builder()
                .coordinates("com.amazon.deequ:deequ:1.0.4")
                .exclusions("org.apache.avro:avro")
                .build())
            .build());

    }
}

    resources:
  deequ:
    type: databricks:Library
    properties:
      clusterId: ${this.id}
      maven:
        coordinates: com.amazon.deequ:deequ:1.0.4
        exclusions:
          - org.apache.avro:avro

    Python PyPI

    Installing Python PyPI artifacts. You can optionally also specify the repo parameter for a custom PyPI mirror, which should be accessible without any authentication for the network that cluster runs in.

    repo host should be accessible from the Internet by Databricks control plane. If connectivity to custom PyPI repositories is required, please modify cluster-node /etc/pip.conf through databricks_global_init_script.

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

const fbprophet = new databricks.Library("fbprophet", {
    clusterId: _this.id,
    pypi: {
        "package": "fbprophet==0.6",
    },
});

    import pulumi
import pulumi_databricks as databricks

fbprophet = databricks.Library("fbprophet",
    cluster_id=this["id"],
    pypi={
        "package": "fbprophet==0.6",
    })

    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 {
		_, err := databricks.NewLibrary(ctx, "fbprophet", &databricks.LibraryArgs{
			ClusterId: pulumi.Any(this.Id),
			Pypi: &databricks.LibraryPypiArgs{
				Package: pulumi.String("fbprophet==0.6"),
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

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

return await Deployment.RunAsync(() => 
{
    var fbprophet = new Databricks.Library("fbprophet", new()
    {
        ClusterId = @this.Id,
        Pypi = new Databricks.Inputs.LibraryPypiArgs
        {
            Package = "fbprophet==0.6",
        },
    });

});

    package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.databricks.Library;
import com.pulumi.databricks.LibraryArgs;
import com.pulumi.databricks.inputs.LibraryPypiArgs;
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) {
        var fbprophet = new Library("fbprophet", LibraryArgs.builder()
            .clusterId(this_.id())
            .pypi(LibraryPypiArgs.builder()
                .package_("fbprophet==0.6")
                .build())
            .build());

    }
}

    resources:
  fbprophet:
    type: databricks:Library
    properties:
      clusterId: ${this.id}
      pypi:
        package: fbprophet==0.6

    Python requirements files

    Installing Python libraries listed in the requirements.txt file. Only Workspace paths and Unity Catalog Volumes paths are supported. Requires a cluster with DBR 15.0+.

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

const libraries = new databricks.Library("libraries", {
    clusterId: _this.id,
    requirements: "/Workspace/path/to/requirements.txt",
});

    import pulumi
import pulumi_databricks as databricks

libraries = databricks.Library("libraries",
    cluster_id=this["id"],
    requirements="/Workspace/path/to/requirements.txt")

    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 {
		_, err := databricks.NewLibrary(ctx, "libraries", &databricks.LibraryArgs{
			ClusterId:    pulumi.Any(this.Id),
			Requirements: pulumi.String("/Workspace/path/to/requirements.txt"),
		})
		if err != nil {
			return err
		}
		return nil
	})
}

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

return await Deployment.RunAsync(() => 
{
    var libraries = new Databricks.Library("libraries", new()
    {
        ClusterId = @this.Id,
        Requirements = "/Workspace/path/to/requirements.txt",
    });

});

    package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.databricks.Library;
import com.pulumi.databricks.LibraryArgs;
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) {
        var libraries = new Library("libraries", LibraryArgs.builder()
            .clusterId(this_.id())
            .requirements("/Workspace/path/to/requirements.txt")
            .build());

    }
}

    resources:
  libraries:
    type: databricks:Library
    properties:
      clusterId: ${this.id}
      requirements: /Workspace/path/to/requirements.txt

    R CRan

    Installing artifacts from CRan. You can also optionally specify a repo parameter for a custom cran mirror.

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

const rkeops = new databricks.Library("rkeops", {
    clusterId: _this.id,
    cran: {
        "package": "rkeops",
    },
});

    import pulumi
import pulumi_databricks as databricks

rkeops = databricks.Library("rkeops",
    cluster_id=this["id"],
    cran={
        "package": "rkeops",
    })

    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 {
		_, err := databricks.NewLibrary(ctx, "rkeops", &databricks.LibraryArgs{
			ClusterId: pulumi.Any(this.Id),
			Cran: &databricks.LibraryCranArgs{
				Package: pulumi.String("rkeops"),
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

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

return await Deployment.RunAsync(() => 
{
    var rkeops = new Databricks.Library("rkeops", new()
    {
        ClusterId = @this.Id,
        Cran = new Databricks.Inputs.LibraryCranArgs
        {
            Package = "rkeops",
        },
    });

});

    package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.databricks.Library;
import com.pulumi.databricks.LibraryArgs;
import com.pulumi.databricks.inputs.LibraryCranArgs;
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) {
        var rkeops = new Library("rkeops", LibraryArgs.builder()
            .clusterId(this_.id())
            .cran(LibraryCranArgs.builder()
                .package_("rkeops")
                .build())
            .build());

    }
}

    resources:
  rkeops:
    type: databricks:Library
    properties:
      clusterId: ${this.id}
      cran:
        package: rkeops

    The following resources are often used in the same context:

    • End to end workspace management guide. * databricks.getClusters data to retrieve a list of databricks.Cluster ids. * databricks.Cluster to create Databricks Clusters. * databricks.ClusterPolicy to create a databricks.Cluster policy, which limits the ability to create clusters based on a set of rules. * databricks.GlobalInitScript to manage global init scripts, which are run on all databricks.Cluster and databricks_job. * databricks.Job to manage Databricks Jobs to run non-interactive code in a databricks_cluster. * databricks.Pipeline to deploy Lakeflow Declarative Pipelines. * databricks.Repo to manage Databricks Repos.

    Create Library Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new Library(name: string, args: LibraryArgs, opts?: CustomResourceOptions);
    @overload
def Library(resource_name: str,
            args: LibraryArgs,
            opts: Optional[ResourceOptions] = None)

@overload
def Library(resource_name: str,
            opts: Optional[ResourceOptions] = None,
            cluster_id: Optional[str] = None,
            cran: Optional[LibraryCranArgs] = None,
            egg: Optional[str] = None,
            jar: Optional[str] = None,
            library_id: Optional[str] = None,
            maven: Optional[LibraryMavenArgs] = None,
            provider_config: Optional[LibraryProviderConfigArgs] = None,
            pypi: Optional[LibraryPypiArgs] = None,
            requirements: Optional[str] = None,
            whl: Optional[str] = None)
    func NewLibrary(ctx *Context, name string, args LibraryArgs, opts ...ResourceOption) (*Library, error)
    public Library(string name, LibraryArgs args, CustomResourceOptions? opts = null)
    public Library(String name, LibraryArgs args)
public Library(String name, LibraryArgs args, CustomResourceOptions options)

    type: databricks:Library
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

    Parameters

    name string
    The unique name of the resource.
    args LibraryArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    resource_name str
    The unique name of the resource.
    args LibraryArgs
    The arguments to resource properties.
    opts ResourceOptions
    Bag of options to control resource's behavior.
    ctx Context
    Context object for the current deployment.
    name string
    The unique name of the resource.
    args LibraryArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args LibraryArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args LibraryArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    Constructor example

    The following reference example uses placeholder values for all input properties.

    var libraryResource = new Databricks.Library("libraryResource", new()
{
    ClusterId = "string",
    Cran = new Databricks.Inputs.LibraryCranArgs
    {
        Package = "string",
        Repo = "string",
    },
    Jar = "string",
    LibraryId = "string",
    Maven = new Databricks.Inputs.LibraryMavenArgs
    {
        Coordinates = "string",
        Exclusions = new[]
        {
            "string",
        },
        Repo = "string",
    },
    ProviderConfig = new Databricks.Inputs.LibraryProviderConfigArgs
    {
        WorkspaceId = "string",
    },
    Pypi = new Databricks.Inputs.LibraryPypiArgs
    {
        Package = "string",
        Repo = "string",
    },
    Requirements = "string",
    Whl = "string",
});

    example, err := databricks.NewLibrary(ctx, "libraryResource", &databricks.LibraryArgs{
	ClusterId: pulumi.String("string"),
	Cran: &databricks.LibraryCranArgs{
		Package: pulumi.String("string"),
		Repo:    pulumi.String("string"),
	},
	Jar:       pulumi.String("string"),
	LibraryId: pulumi.String("string"),
	Maven: &databricks.LibraryMavenArgs{
		Coordinates: pulumi.String("string"),
		Exclusions: pulumi.StringArray{
			pulumi.String("string"),
		},
		Repo: pulumi.String("string"),
	},
	ProviderConfig: &databricks.LibraryProviderConfigArgs{
		WorkspaceId: pulumi.String("string"),
	},
	Pypi: &databricks.LibraryPypiArgs{
		Package: pulumi.String("string"),
		Repo:    pulumi.String("string"),
	},
	Requirements: pulumi.String("string"),
	Whl:          pulumi.String("string"),
})

    var libraryResource = new Library("libraryResource", LibraryArgs.builder()
    .clusterId("string")
    .cran(LibraryCranArgs.builder()
        .package_("string")
        .repo("string")
        .build())
    .jar("string")
    .libraryId("string")
    .maven(LibraryMavenArgs.builder()
        .coordinates("string")
        .exclusions("string")
        .repo("string")
        .build())
    .providerConfig(LibraryProviderConfigArgs.builder()
        .workspaceId("string")
        .build())
    .pypi(LibraryPypiArgs.builder()
        .package_("string")
        .repo("string")
        .build())
    .requirements("string")
    .whl("string")
    .build());

    library_resource = databricks.Library("libraryResource",
    cluster_id="string",
    cran={
        "package": "string",
        "repo": "string",
    },
    jar="string",
    library_id="string",
    maven={
        "coordinates": "string",
        "exclusions": ["string"],
        "repo": "string",
    },
    provider_config={
        "workspace_id": "string",
    },
    pypi={
        "package": "string",
        "repo": "string",
    },
    requirements="string",
    whl="string")

    const libraryResource = new databricks.Library("libraryResource", {
    clusterId: "string",
    cran: {
        "package": "string",
        repo: "string",
    },
    jar: "string",
    libraryId: "string",
    maven: {
        coordinates: "string",
        exclusions: ["string"],
        repo: "string",
    },
    providerConfig: {
        workspaceId: "string",
    },
    pypi: {
        "package": "string",
        repo: "string",
    },
    requirements: "string",
    whl: "string",
});

    type: databricks:Library
properties:
    clusterId: string
    cran:
        package: string
        repo: string
    jar: string
    libraryId: string
    maven:
        coordinates: string
        exclusions:
            - string
        repo: string
    providerConfig:
        workspaceId: string
    pypi:
        package: string
        repo: string
    requirements: string
    whl: string

    Library Resource Properties

    To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

    Inputs

    In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

    The Library resource accepts the following input properties:

    ClusterId string

    ID of the databricks.Cluster to install the library on.

    You must specify exactly one of the following library types:

    Cran LibraryCran
    Configuration block for a CRAN library. The block consists of the following fields:
    Egg string
    Path to the EGG library. Installing Python egg files is deprecated and is not supported in Databricks Runtime 14.0 and above. Use whl or pypi instead.

    Deprecated: The egg library type is deprecated. Please use whl or pypi instead.

    Jar string
    Path to the JAR library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.jar, /Volumes/path/to/library.jar or s3://my-bucket/library.jar. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    LibraryId string
    Maven LibraryMaven
    Configuration block for a Maven library. The block consists of the following fields:
    ProviderConfig LibraryProviderConfig
    Configuration block for management through the account provider. This block consists of the following fields:
    Pypi LibraryPypi
    Configuration block for a PyPI library. The block consists of the following fields:
    Requirements string
    Path to the requirements.txt file. Only Workspace paths and Unity Catalog Volumes paths are supported. For example: /Workspace/path/to/requirements.txt or /Volumes/path/to/requirements.txt. Requires a cluster with DBR 15.0+.
    Whl string
    Path to the wheel library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.whl, /Volumes/path/to/library.whl or s3://my-bucket/library.whl. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    ClusterId string

    ID of the databricks.Cluster to install the library on.

    You must specify exactly one of the following library types:

    Cran LibraryCranArgs
    Configuration block for a CRAN library. The block consists of the following fields:
    Egg string
    Path to the EGG library. Installing Python egg files is deprecated and is not supported in Databricks Runtime 14.0 and above. Use whl or pypi instead.

    Deprecated: The egg library type is deprecated. Please use whl or pypi instead.

    Jar string
    Path to the JAR library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.jar, /Volumes/path/to/library.jar or s3://my-bucket/library.jar. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    LibraryId string
    Maven LibraryMavenArgs
    Configuration block for a Maven library. The block consists of the following fields:
    ProviderConfig LibraryProviderConfigArgs
    Configuration block for management through the account provider. This block consists of the following fields:
    Pypi LibraryPypiArgs
    Configuration block for a PyPI library. The block consists of the following fields:
    Requirements string
    Path to the requirements.txt file. Only Workspace paths and Unity Catalog Volumes paths are supported. For example: /Workspace/path/to/requirements.txt or /Volumes/path/to/requirements.txt. Requires a cluster with DBR 15.0+.
    Whl string
    Path to the wheel library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.whl, /Volumes/path/to/library.whl or s3://my-bucket/library.whl. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    clusterId String

    ID of the databricks.Cluster to install the library on.

    You must specify exactly one of the following library types:

    cran LibraryCran
    Configuration block for a CRAN library. The block consists of the following fields:
    egg String
    Path to the EGG library. Installing Python egg files is deprecated and is not supported in Databricks Runtime 14.0 and above. Use whl or pypi instead.

    Deprecated: The egg library type is deprecated. Please use whl or pypi instead.

    jar String
    Path to the JAR library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.jar, /Volumes/path/to/library.jar or s3://my-bucket/library.jar. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    libraryId String
    maven LibraryMaven
    Configuration block for a Maven library. The block consists of the following fields:
    providerConfig LibraryProviderConfig
    Configuration block for management through the account provider. This block consists of the following fields:
    pypi LibraryPypi
    Configuration block for a PyPI library. The block consists of the following fields:
    requirements String
    Path to the requirements.txt file. Only Workspace paths and Unity Catalog Volumes paths are supported. For example: /Workspace/path/to/requirements.txt or /Volumes/path/to/requirements.txt. Requires a cluster with DBR 15.0+.
    whl String
    Path to the wheel library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.whl, /Volumes/path/to/library.whl or s3://my-bucket/library.whl. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    clusterId string

    ID of the databricks.Cluster to install the library on.

    You must specify exactly one of the following library types:

    cran LibraryCran
    Configuration block for a CRAN library. The block consists of the following fields:
    egg string
    Path to the EGG library. Installing Python egg files is deprecated and is not supported in Databricks Runtime 14.0 and above. Use whl or pypi instead.

    Deprecated: The egg library type is deprecated. Please use whl or pypi instead.

    jar string
    Path to the JAR library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.jar, /Volumes/path/to/library.jar or s3://my-bucket/library.jar. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    libraryId string
    maven LibraryMaven
    Configuration block for a Maven library. The block consists of the following fields:
    providerConfig LibraryProviderConfig
    Configuration block for management through the account provider. This block consists of the following fields:
    pypi LibraryPypi
    Configuration block for a PyPI library. The block consists of the following fields:
    requirements string
    Path to the requirements.txt file. Only Workspace paths and Unity Catalog Volumes paths are supported. For example: /Workspace/path/to/requirements.txt or /Volumes/path/to/requirements.txt. Requires a cluster with DBR 15.0+.
    whl string
    Path to the wheel library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.whl, /Volumes/path/to/library.whl or s3://my-bucket/library.whl. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    cluster_id str

    ID of the databricks.Cluster to install the library on.

    You must specify exactly one of the following library types:

    cran LibraryCranArgs
    Configuration block for a CRAN library. The block consists of the following fields:
    egg str
    Path to the EGG library. Installing Python egg files is deprecated and is not supported in Databricks Runtime 14.0 and above. Use whl or pypi instead.

    Deprecated: The egg library type is deprecated. Please use whl or pypi instead.

    jar str
    Path to the JAR library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.jar, /Volumes/path/to/library.jar or s3://my-bucket/library.jar. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    library_id str
    maven LibraryMavenArgs
    Configuration block for a Maven library. The block consists of the following fields:
    provider_config LibraryProviderConfigArgs
    Configuration block for management through the account provider. This block consists of the following fields:
    pypi LibraryPypiArgs
    Configuration block for a PyPI library. The block consists of the following fields:
    requirements str
    Path to the requirements.txt file. Only Workspace paths and Unity Catalog Volumes paths are supported. For example: /Workspace/path/to/requirements.txt or /Volumes/path/to/requirements.txt. Requires a cluster with DBR 15.0+.
    whl str
    Path to the wheel library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.whl, /Volumes/path/to/library.whl or s3://my-bucket/library.whl. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    clusterId String

    ID of the databricks.Cluster to install the library on.

    You must specify exactly one of the following library types:

    cran Property Map
    Configuration block for a CRAN library. The block consists of the following fields:
    egg String
    Path to the EGG library. Installing Python egg files is deprecated and is not supported in Databricks Runtime 14.0 and above. Use whl or pypi instead.

    Deprecated: The egg library type is deprecated. Please use whl or pypi instead.

    jar String
    Path to the JAR library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.jar, /Volumes/path/to/library.jar or s3://my-bucket/library.jar. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    libraryId String
    maven Property Map
    Configuration block for a Maven library. The block consists of the following fields:
    providerConfig Property Map
    Configuration block for management through the account provider. This block consists of the following fields:
    pypi Property Map
    Configuration block for a PyPI library. The block consists of the following fields:
    requirements String
    Path to the requirements.txt file. Only Workspace paths and Unity Catalog Volumes paths are supported. For example: /Workspace/path/to/requirements.txt or /Volumes/path/to/requirements.txt. Requires a cluster with DBR 15.0+.
    whl String
    Path to the wheel library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.whl, /Volumes/path/to/library.whl or s3://my-bucket/library.whl. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.

    Outputs

    All input properties are implicitly available as output properties. Additionally, the Library resource produces the following output properties:

    Id string
    The provider-assigned unique ID for this managed resource.
    Id string
    The provider-assigned unique ID for this managed resource.
    id String
    The provider-assigned unique ID for this managed resource.
    id string
    The provider-assigned unique ID for this managed resource.
    id str
    The provider-assigned unique ID for this managed resource.
    id String
    The provider-assigned unique ID for this managed resource.

    Look up Existing Library Resource

    Get an existing Library resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.

    public static get(name: string, id: Input<ID>, state?: LibraryState, opts?: CustomResourceOptions): Library
    @staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        cluster_id: Optional[str] = None,
        cran: Optional[LibraryCranArgs] = None,
        egg: Optional[str] = None,
        jar: Optional[str] = None,
        library_id: Optional[str] = None,
        maven: Optional[LibraryMavenArgs] = None,
        provider_config: Optional[LibraryProviderConfigArgs] = None,
        pypi: Optional[LibraryPypiArgs] = None,
        requirements: Optional[str] = None,
        whl: Optional[str] = None) -> Library
    func GetLibrary(ctx *Context, name string, id IDInput, state *LibraryState, opts ...ResourceOption) (*Library, error)
    public static Library Get(string name, Input<string> id, LibraryState? state, CustomResourceOptions? opts = null)
    public static Library get(String name, Output<String> id, LibraryState state, CustomResourceOptions options)
    resources:  _:    type: databricks:Library    get:      id: ${id}
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    resource_name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    The following state arguments are supported:
    ClusterId string

    ID of the databricks.Cluster to install the library on.

    You must specify exactly one of the following library types:

    Cran LibraryCran
    Configuration block for a CRAN library. The block consists of the following fields:
    Egg string
    Path to the EGG library. Installing Python egg files is deprecated and is not supported in Databricks Runtime 14.0 and above. Use whl or pypi instead.

    Deprecated: The egg library type is deprecated. Please use whl or pypi instead.

    Jar string
    Path to the JAR library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.jar, /Volumes/path/to/library.jar or s3://my-bucket/library.jar. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    LibraryId string
    Maven LibraryMaven
    Configuration block for a Maven library. The block consists of the following fields:
    ProviderConfig LibraryProviderConfig
    Configuration block for management through the account provider. This block consists of the following fields:
    Pypi LibraryPypi
    Configuration block for a PyPI library. The block consists of the following fields:
    Requirements string
    Path to the requirements.txt file. Only Workspace paths and Unity Catalog Volumes paths are supported. For example: /Workspace/path/to/requirements.txt or /Volumes/path/to/requirements.txt. Requires a cluster with DBR 15.0+.
    Whl string
    Path to the wheel library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.whl, /Volumes/path/to/library.whl or s3://my-bucket/library.whl. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    ClusterId string

    ID of the databricks.Cluster to install the library on.

    You must specify exactly one of the following library types:

    Cran LibraryCranArgs
    Configuration block for a CRAN library. The block consists of the following fields:
    Egg string
    Path to the EGG library. Installing Python egg files is deprecated and is not supported in Databricks Runtime 14.0 and above. Use whl or pypi instead.

    Deprecated: The egg library type is deprecated. Please use whl or pypi instead.

    Jar string
    Path to the JAR library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.jar, /Volumes/path/to/library.jar or s3://my-bucket/library.jar. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    LibraryId string
    Maven LibraryMavenArgs
    Configuration block for a Maven library. The block consists of the following fields:
    ProviderConfig LibraryProviderConfigArgs
    Configuration block for management through the account provider. This block consists of the following fields:
    Pypi LibraryPypiArgs
    Configuration block for a PyPI library. The block consists of the following fields:
    Requirements string
    Path to the requirements.txt file. Only Workspace paths and Unity Catalog Volumes paths are supported. For example: /Workspace/path/to/requirements.txt or /Volumes/path/to/requirements.txt. Requires a cluster with DBR 15.0+.
    Whl string
    Path to the wheel library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.whl, /Volumes/path/to/library.whl or s3://my-bucket/library.whl. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    clusterId String

    ID of the databricks.Cluster to install the library on.

    You must specify exactly one of the following library types:

    cran LibraryCran
    Configuration block for a CRAN library. The block consists of the following fields:
    egg String
    Path to the EGG library. Installing Python egg files is deprecated and is not supported in Databricks Runtime 14.0 and above. Use whl or pypi instead.

    Deprecated: The egg library type is deprecated. Please use whl or pypi instead.

    jar String
    Path to the JAR library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.jar, /Volumes/path/to/library.jar or s3://my-bucket/library.jar. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    libraryId String
    maven LibraryMaven
    Configuration block for a Maven library. The block consists of the following fields:
    providerConfig LibraryProviderConfig
    Configuration block for management through the account provider. This block consists of the following fields:
    pypi LibraryPypi
    Configuration block for a PyPI library. The block consists of the following fields:
    requirements String
    Path to the requirements.txt file. Only Workspace paths and Unity Catalog Volumes paths are supported. For example: /Workspace/path/to/requirements.txt or /Volumes/path/to/requirements.txt. Requires a cluster with DBR 15.0+.
    whl String
    Path to the wheel library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.whl, /Volumes/path/to/library.whl or s3://my-bucket/library.whl. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    clusterId string

    ID of the databricks.Cluster to install the library on.

    You must specify exactly one of the following library types:

    cran LibraryCran
    Configuration block for a CRAN library. The block consists of the following fields:
    egg string
    Path to the EGG library. Installing Python egg files is deprecated and is not supported in Databricks Runtime 14.0 and above. Use whl or pypi instead.

    Deprecated: The egg library type is deprecated. Please use whl or pypi instead.

    jar string
    Path to the JAR library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.jar, /Volumes/path/to/library.jar or s3://my-bucket/library.jar. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    libraryId string
    maven LibraryMaven
    Configuration block for a Maven library. The block consists of the following fields:
    providerConfig LibraryProviderConfig
    Configuration block for management through the account provider. This block consists of the following fields:
    pypi LibraryPypi
    Configuration block for a PyPI library. The block consists of the following fields:
    requirements string
    Path to the requirements.txt file. Only Workspace paths and Unity Catalog Volumes paths are supported. For example: /Workspace/path/to/requirements.txt or /Volumes/path/to/requirements.txt. Requires a cluster with DBR 15.0+.
    whl string
    Path to the wheel library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.whl, /Volumes/path/to/library.whl or s3://my-bucket/library.whl. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    cluster_id str

    ID of the databricks.Cluster to install the library on.

    You must specify exactly one of the following library types:

    cran LibraryCranArgs
    Configuration block for a CRAN library. The block consists of the following fields:
    egg str
    Path to the EGG library. Installing Python egg files is deprecated and is not supported in Databricks Runtime 14.0 and above. Use whl or pypi instead.

    Deprecated: The egg library type is deprecated. Please use whl or pypi instead.

    jar str
    Path to the JAR library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.jar, /Volumes/path/to/library.jar or s3://my-bucket/library.jar. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    library_id str
    maven LibraryMavenArgs
    Configuration block for a Maven library. The block consists of the following fields:
    provider_config LibraryProviderConfigArgs
    Configuration block for management through the account provider. This block consists of the following fields:
    pypi LibraryPypiArgs
    Configuration block for a PyPI library. The block consists of the following fields:
    requirements str
    Path to the requirements.txt file. Only Workspace paths and Unity Catalog Volumes paths are supported. For example: /Workspace/path/to/requirements.txt or /Volumes/path/to/requirements.txt. Requires a cluster with DBR 15.0+.
    whl str
    Path to the wheel library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.whl, /Volumes/path/to/library.whl or s3://my-bucket/library.whl. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    clusterId String

    ID of the databricks.Cluster to install the library on.

    You must specify exactly one of the following library types:

    cran Property Map
    Configuration block for a CRAN library. The block consists of the following fields:
    egg String
    Path to the EGG library. Installing Python egg files is deprecated and is not supported in Databricks Runtime 14.0 and above. Use whl or pypi instead.

    Deprecated: The egg library type is deprecated. Please use whl or pypi instead.

    jar String
    Path to the JAR library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.jar, /Volumes/path/to/library.jar or s3://my-bucket/library.jar. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.
    libraryId String
    maven Property Map
    Configuration block for a Maven library. The block consists of the following fields:
    providerConfig Property Map
    Configuration block for management through the account provider. This block consists of the following fields:
    pypi Property Map
    Configuration block for a PyPI library. The block consists of the following fields:
    requirements String
    Path to the requirements.txt file. Only Workspace paths and Unity Catalog Volumes paths are supported. For example: /Workspace/path/to/requirements.txt or /Volumes/path/to/requirements.txt. Requires a cluster with DBR 15.0+.
    whl String
    Path to the wheel library. Supported URIs include Workspace paths, Unity Catalog Volumes paths, and S3 URIs. For example: /Workspace/path/to/library.whl, /Volumes/path/to/library.whl or s3://my-bucket/library.whl. If S3 is used, make sure the cluster has read access to the library. You may need to launch the cluster with an IAM role to access the S3 URI.

    Supporting Types

    LibraryCran, LibraryCranArgs

    Package string
    The name of the CRAN package to install.
    Repo string
    The repository where the package can be found. If not specified, the default CRAN repo is used.
    Package string
    The name of the CRAN package to install.
    Repo string
    The repository where the package can be found. If not specified, the default CRAN repo is used.
    package_ String
    The name of the CRAN package to install.
    repo String
    The repository where the package can be found. If not specified, the default CRAN repo is used.
    package string
    The name of the CRAN package to install.
    repo string
    The repository where the package can be found. If not specified, the default CRAN repo is used.
    package str
    The name of the CRAN package to install.
    repo str
    The repository where the package can be found. If not specified, the default CRAN repo is used.
    package String
    The name of the CRAN package to install.
    repo String
    The repository where the package can be found. If not specified, the default CRAN repo is used.

    LibraryMaven, LibraryMavenArgs

    Coordinates string
    Gradle-style Maven coordinates. For example: org.jsoup:jsoup:1.7.2.
    Exclusions List<string>
    List of dependencies to exclude. For example: ["slf4j:slf4j", "*:hadoop-client"]. See Maven dependency exclusions for more information.
    Repo string
    Maven repository to install the Maven package from. If omitted, both Maven Central Repository and Spark Packages are searched.
    Coordinates string
    Gradle-style Maven coordinates. For example: org.jsoup:jsoup:1.7.2.
    Exclusions []string
    List of dependencies to exclude. For example: ["slf4j:slf4j", "*:hadoop-client"]. See Maven dependency exclusions for more information.
    Repo string
    Maven repository to install the Maven package from. If omitted, both Maven Central Repository and Spark Packages are searched.
    coordinates String
    Gradle-style Maven coordinates. For example: org.jsoup:jsoup:1.7.2.
    exclusions List<String>
    List of dependencies to exclude. For example: ["slf4j:slf4j", "*:hadoop-client"]. See Maven dependency exclusions for more information.
    repo String
    Maven repository to install the Maven package from. If omitted, both Maven Central Repository and Spark Packages are searched.
    coordinates string
    Gradle-style Maven coordinates. For example: org.jsoup:jsoup:1.7.2.
    exclusions string[]
    List of dependencies to exclude. For example: ["slf4j:slf4j", "*:hadoop-client"]. See Maven dependency exclusions for more information.
    repo string
    Maven repository to install the Maven package from. If omitted, both Maven Central Repository and Spark Packages are searched.
    coordinates str
    Gradle-style Maven coordinates. For example: org.jsoup:jsoup:1.7.2.
    exclusions Sequence[str]
    List of dependencies to exclude. For example: ["slf4j:slf4j", "*:hadoop-client"]. See Maven dependency exclusions for more information.
    repo str
    Maven repository to install the Maven package from. If omitted, both Maven Central Repository and Spark Packages are searched.
    coordinates String
    Gradle-style Maven coordinates. For example: org.jsoup:jsoup:1.7.2.
    exclusions List<String>
    List of dependencies to exclude. For example: ["slf4j:slf4j", "*:hadoop-client"]. See Maven dependency exclusions for more information.
    repo String
    Maven repository to install the Maven package from. If omitted, both Maven Central Repository and Spark Packages are searched.

    LibraryProviderConfig, LibraryProviderConfigArgs

    WorkspaceId string
    Workspace ID that the resource belongs to. This workspace must be part of the account that the provider is configured with.
    WorkspaceId string
    Workspace ID that the resource belongs to. This workspace must be part of the account that the provider is configured with.
    workspaceId String
    Workspace ID that the resource belongs to. This workspace must be part of the account that the provider is configured with.
    workspaceId string
    Workspace ID that the resource belongs to. This workspace must be part of the account that the provider is configured with.
    workspace_id str
    Workspace ID that the resource belongs to. This workspace must be part of the account that the provider is configured with.
    workspaceId String
    Workspace ID that the resource belongs to. This workspace must be part of the account that the provider is configured with.

    LibraryPypi, LibraryPypiArgs

    Package string
    The name of the PyPI package to install. An optional exact version specification is also supported. For example: simplejson or simplejson==3.8.0.
    Repo string
    The repository where the package can be found. If not specified, the default pip index is used.
    Package string
    The name of the PyPI package to install. An optional exact version specification is also supported. For example: simplejson or simplejson==3.8.0.
    Repo string
    The repository where the package can be found. If not specified, the default pip index is used.
    package_ String
    The name of the PyPI package to install. An optional exact version specification is also supported. For example: simplejson or simplejson==3.8.0.
    repo String
    The repository where the package can be found. If not specified, the default pip index is used.
    package string
    The name of the PyPI package to install. An optional exact version specification is also supported. For example: simplejson or simplejson==3.8.0.
    repo string
    The repository where the package can be found. If not specified, the default pip index is used.
    package str
    The name of the PyPI package to install. An optional exact version specification is also supported. For example: simplejson or simplejson==3.8.0.
    repo str
    The repository where the package can be found. If not specified, the default pip index is used.
    package String
    The name of the PyPI package to install. An optional exact version specification is also supported. For example: simplejson or simplejson==3.8.0.
    repo String
    The repository where the package can be found. If not specified, the default pip index is used.

    Import

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    Package Details

    Repository
    databricks pulumi/pulumi-databricks
    License
    Apache-2.0
    Notes
    This Pulumi package is based on the databricks Terraform Provider.
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    Databricks v1.77.0 published on Tuesday, Nov 4, 2025 by Pulumi
    pulumi/pulumi-databricks
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