Search examples

Connection by name and type

You may have noticed that connections in Atlan have qualifiedNames that include a timestamp. As a result, they are not trivial to directly construct.

1.4.0 1.1.0

However, you can search for them by name and type to resolve their qualifiedName:

Java Python Kotlin Raw REST API

List<Connection> connections = Connection.findByName( // (1)
    "production", // (2)
    AtlanConnectorType.SNOWFLAKE); // (3)

1. Use the findByName static method on the Connection class to search for connections by name and type. If you name your connections uniquely (by type), this should only return a single-item list.
2. Provide the name of the connection (this will be exact-matched).
3. Provide the type of the connection. You can also (optionally) provide a list of extra attributes you want to retrieve for the connection. Core attributes like qualifiedName and its GUID are already included.

from pyatlan.client.atlan import AtlanClient
from pyatlan.model.enums import AtlanConnectorType

client = AtlanClient()
connections = client.asset.find_connections_by_name( # (1)
    name="production", # (2)
    connector_type=AtlanConnectorType.SNOWFLAKE, # (3)
    attributes=[] # (4)
)

1. Use the asset.find_connections_by_name method on the AtlanClient class to search for connections by name and type. If you name your connections uniquely (by type), this should only return a single-item list.
2. Provide the name of the connection (this will be exact-matched).
3. Provide the type of the connection.
4. You can also (optionally) provide a list of extra attributes you want to retrieve for the connection. Core attributes like qualifiedName and its GUID are already included.

val connections = Connection.findByName( // (1)
    "production", // (2)
    AtlanConnectorType.SNOWFLAKE) // (3)

1. Use the findByName static method on the Connection class to search for connections by name and type. If you name your connections uniquely (by type), this should only return a single-item list.
2. Provide the name of the connection (this will be exact-matched).
3. Provide the type of the connection. You can also (optionally) provide a list of extra attributes you want to retrieve for the connection. Core attributes like qualifiedName and its GUID are already included.

{
  "dsl": { // (1)
    "query": {
      "bool": { // (2)
        "filter": [ // (3)
          {
            "term": { // (4)
              "__state": {
                "value": "ACTIVE"
              }
            }
          },
          {
            "term": { // (5)
              "__typeName.keyword": {
                "value": "Connection"
              }
            }
          },
          {
            "term": { // (6)
              "name.keyword": {
                "value": "production"
              }
            }
          },
          {
            "term": { // (7)
              "connectorName": {
                "value": "snowflake"
              }
            }
          }
        ]
      }
    },
    "track_total_hits": true
  },
  "suppressLogs": true,
  "showSearchScore": false,
  "excludeMeanings": false,
  "excludeClassifications": false
}

1. Run a search to find the connections.
2. To start building up a query with multiple conditions, you can use a bool query in Elasticsearch.
3. You can use the filter criteria to define all the conditions the search results must match in a binary way (either matches or doesn't). This avoids the need to calculate a score for each result.
4. Searches by default will return all assets that are found — whether active or archived (soft-deleted). In most cases, you probably only want the active ones.
5. Since there could be tables, views, materialized views, columns, databases, schemas, etc in this connection — but you only want the connection itself — you can use an exact match on the type to restrict results to only connections.
6. Exact match search (case-sensitive) on the name of the connection.
7. Exact match search on the type of the connector for the connection.

All connections

1.4.0 1.1.0

On the other hand, you may want to find all the connections that exist in the environment:

Java Python Kotlin Raw REST API

Connection.select() // (1)
    .pageSize(100) // (2)
    .stream() // (3)
    .filter(a -> a instanceof Connection) // (4)
    .forEach(c -> { // (5)
        log.info("Connection: {}", c);
    });

1. To start building up a query to include all connections, you can use the select() convenience method on Connection itself. This will already limit results to only active (non-archived) connections.
2. (Optional) You can chain a pageSize() method to control the page sizes, to further limit API calls by retrieving more results per page.
3. The search will only run when you call the stream() method, which will then lazily-load each page of results into a stream.
4. (Optional) You can do any other operations you might do on a stream, such as filtering the results to ensure they are of a certain type.
5. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

from pyatlan.client.atlan import AtlanClient
from pyatlan.model.assets import Connection
from pyatlan.model.fluent_search import FluentSearch, CompoundQuery

client = AtlanClient()  # (1)
request = (
    FluentSearch()  # (2)
    .where(CompoundQuery.asset_type(Connection))  # (3)
    .where(CompoundQuery.active_assets())  # (4)
    .page_size(100)  # (5)
).to_request()  # (6)
for result in client.asset.search(request):  # (7)
    if isinstance(result, Connection):  # (8)
        print(result)

1. Start with a client to run the search through. For the default client, you can always use AtlanClient().
2. To search across all assets, you can use a FluentSearch object.
3. The .where() method allows you to limit to only certain assets. In this example, we are looking for connections, so use the CompoundQuery.asset_type() helper to narrow to only connections.
4. You can chain additional .where() methods to add further conditions, like this example where we limit to only active (non-archived) assets.
5. (Optional) You can chain a pageSize() method to control the page sizes, to further limit API calls by retrieving more results per page.
6. You can then translate the fluent search into an index search request.
7. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.
8. Use the isinstance method to ensure that the asset is of the desired type. This will also allow an IDE to provide specific type hints for this asset type.

Connection.select() // (1)
    .pageSize(100) // (2)
    .stream() // (3)
    .filter { it is Connection } // (4)
    .forEach {  // (5)
        log.info { "Connection: $it" }
    }

1. To start building up a query to include all connections, you can use the select() convenience method on Connection itself. This will already limit results to only active (non-archived) connections.
2. (Optional) You can chain a pageSize() method to control the page sizes, to further limit API calls by retrieving more results per page.
3. The search will only run when you call the stream() method, which will then lazily-load each page of results into a stream.
4. (Optional) You can do any other operations you might do on a stream, such as filtering the results to ensure they are of a certain type.
5. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

{
  "dsl": { // (1)
    "from": 0,
    "size": 100,
    "query": {
      "bool": { // (2)
        "filter": [ // (3)
          {
            "term": { // (4)
              "__typeName.keyword": {
                "value": "Connection"
              }
            }
          },
          {
            "term": {
              "__state": { // (5)
                "value": "ACTIVE"
              }
            }
          }
        ]
      }
    },
    "track_total_hits": true
  },
  "suppressLogs": true,
  "showSearchScore": false,
  "excludeMeanings": false,
  "excludeClassifications": false
}

1. Run a search to find the connections.

2. To start building up a query with multiple conditions, you can use a bool query in Elasticsearch.

3. You can use the filter criteria to define all the conditions the search results must match in a binary way (either matches or doesn't). This avoids the need to calculate a score for each result.

4. You can use an exact match on the type to restrict results to only connections.

5. Searches by default will return all assets that are found — whether active or archived (soft-deleted). In most cases, you probably only want the active ones.

Columns in a schema

1.4.0 1.1.0

This example finds all columns that exist in a particular schema — irrespective of the table, view, or materialized view they exist within.

Java Python Kotlin Raw REST API

String schemaQN = "default/snowflake/1662194632/MYDB/MY_SCH"; // (1)
Column.select() // (2)
    .where(Asset.QUALIFIED_NAME.startsWith(schemaQN)) // (3)
    .pageSize(100) // (4)
    .includeOnResults(Asset.DESCRIPTION) // (5)
    .stream() // (6)
    .filter(a -> a instanceof Column) // (7)
    .forEach(c -> { // (8)
        log.info("Column: {}", c);
    });

1. Part of the trick here is that the qualifiedName of a column starts with the qualifiedName of its parent (table, view or materialized view). Similarly, the qualifiedName of the table, view or materialized view starts with the qualifiedName of its parent schema. (And so on, all the way up to the connection itself.)
2. To start building up a query specifically for columns, you can use the select() convenience method on Column itself.
3. You can use the where() method to define all the conditions the search results must match. For this example, use the Asset.QUALIFIED_NAME constant to limit to only those assets whose qualifiedName starts with the qualifiedName of the schema (by using the startsWith() predicate). In this example, that means only assets that are within this particular schema will be returned as results.
4. (Optional) You can play around with different page sizes, to further limit API calls by retrieving more results per page.
5. Add as many attributes as needed. Each attribute you add here will ensure that detail is included in each search result. So in this example, every column will include its description. (Limit these attributes to the minimum you need about each column to do your intended work.)
6. The search will only run when you call the stream() method, which will then lazily-load each page of results into a stream.
7. (Optional) You can do any other operations you might do on a stream, such as filtering the results to ensure they are of a certain type.
8. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

from pyatlan.client.atlan import AtlanClient
from pyatlan.model.assets import Column
from pyatlan.model.fluent_search import FluentSearch, CompoundQuery

schema_qn = "default/snowflake/1646836521/ATLAN_SAMPLE_DATA/PUBLIC"  # (1)
client = AtlanClient()  # (2)
request = (
    FluentSearch()  # (3)
    .where(CompoundQuery.asset_type(Column))  # (4)
    .where(CompoundQuery.active_assets())  # (5)
    .where(Column.QUALIFIED_NAME.startswith(schema_qn))  # (6)
).to_request()  # (7)
for result in client.asset.search(request):  # (8)
    if isinstance(result, Column):  # (9)
        print(result)

1. Part of the trick here is that the qualified_name of a column starts with the qualified_name of its parent (table, view or materialized view). Similarly, the qualified_name of the table, view or materialized view starts with the qualified_name of its parent schema. (And so on, all the way up to the connection itself.)
2. Start with a client to run the search through. For the default client, you can always use AtlanClient().
3. To search across all assets, you can use a FluentSearch object.
4. The .where() method allows you to limit to only certain assets. In this example, we are looking for columns, so use the CompoundQuery.asset_type() helper to narrow to only columns.
5. You can chain additional .where() methods to add further conditions, like this example where we limit to only active (non-archived) assets.
6. For this example, use the Column.QUALIFIED_NAME constant to limit to only those columns whose qualified_name starts with the qualified_name of the schema (by using the startswith() predicate). In this example, that means only columns that are within this particular schema will be returned as results.
7. You can then translate the fluent search into an index search request.
8. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.
9. Use the isinstance method to ensure that the asset is of the desired type. This will also allow an IDE to provide specific type hints for this asset type.

val schemaQN = "default/snowflake/1662194632/MYDB/MY_SCH" // (1)
Column.select() // (2)
    .where(Asset.QUALIFIED_NAME.startsWith(schemaQN)) // (3)
    .pageSize(100) // (4)
    .includeOnResults(Asset.DESCRIPTION) // (5)
    .stream() // (6)
    .filter { it is Column } // (7)
    .forEach { // (8)
        log.info { "Column: $it" }
    });

1. Part of the trick here is that the qualifiedName of a column starts with the qualifiedName of its parent (table, view or materialized view). Similarly, the qualifiedName of the table, view or materialized view starts with the qualifiedName of its parent schema. (And so on, all the way up to the connection itself.)
2. To start building up a query specifically for columns, you can use the select() convenience method on Column itself.
3. You can use the where() method to define all the conditions the search results must match. For this example, use the Asset.QUALIFIED_NAME constant to limit to only those assets whose qualifiedName starts with the qualifiedName of the schema (by using the startsWith() predicate). In this example, that means only assets that are within this particular schema will be returned as results.
4. (Optional) You can play around with different page sizes, to further limit API calls by retrieving more results per page.
5. Add as many attributes as needed. Each attribute you add here will ensure that detail is included in each search result. So in this example, every column will include its description. (Limit these attributes to the minimum you need about each column to do your intended work.)
6. The search will only run when you call the stream() method, which will then lazily-load each page of results into a stream.
7. (Optional) You can do any other operations you might do on a stream, such as filtering the results to ensure they are of a certain type.
8. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

{
  "dsl": { // (1)
    "query": {
      "bool": { // (2)
        "filter": [ // (3)
          {
            "prefix": { // (4)
              "qualifiedName": {
                "value": "default/snowflake/1662194632/MYDB/MY_SCH"
              }
            }
          },
          {
            "term": { // (5)
              "__typeName.keyword": {
                "value": "Column"
              }
            }
          },
          {
            "term": { // (6)
              "__state": {
                "value": "ACTIVE"
              }
            }
          }
        ]
      }
    },
    "from": 0, // (7)
    "size": 100,
    "track_total_hits": true
  },
  "attributes": [ // (8)
    "description"
  ],
  "suppressLogs": true,
  "showSearchScore": false,
  "excludeMeanings": false,
  "excludeClassifications": false
}

1. Run a search to find the columns.

2. To start building up a query with multiple conditions, you can use a bool query in Elasticsearch.

3. You can use the filter criteria to define all the conditions the search results must match in a binary way (either matches or doesn't). This avoids the need to calculate a score for each result.

4. Part of the trick here is that the qualifiedName of a column starts with the qualifiedName of its parent (table, view or materialized view). Similarly, the qualifiedName of the table, view or materialized view starts with the qualifiedName of its parent schema. (And so on, all the way up to the connection itself.)

5. Since there could be tables, views, materialized views and columns in this schema — but you only want columns — you can use an exact match on the type to restrict results to only columns.

6. Searches by default will return all assets that are found — whether active or archived (soft-deleted). In most cases, you probably only want the active ones.

7. Here you can play around with different page sizes, to further limit API calls by retrieving more results per page.

8. Add as many attributes as needed. Each attribute you add here will ensure that detail is included in each search result. So in this example, every column will include its description. (Limit these attributes to the minimum you need about each column to do your intended work.)

Assets with custom metadata

1.4.0 1.1.0

This example finds all assets with a particular custom metadata attribute populated — irrespective of the specific value of the attribute.

Java Python Kotlin Raw REST API

AtlanClient client = Atlan.getDefaultClient(); // (1)
client.assets.select() // (2)
    .where(CustomMetadataField.of(client, "RACI", "Responsible").hasAnyValue()) // (3)
    ._includesOnResults(client.getCustomMetadataCache().getAttributesForSearchResults("RACI")) // (4)
    .stream() // (5)
    .forEach(a -> { // (6)
        log.info("Asset: {}", a);
    });

1. Start with a client to run the search through. For the default client, you can always use Atlan.getDefaultClient().
2. To search across all assets, you can use the assets.select() convenience method on a client.

3. When searching for custom metadata attributes, you can construct a CustomMetadataField to start a clause that will match a custom metadata property. Since you are searching for the custom metadata attribute itself, there is no enum for the custom metadata or its property names, so these must be provided as strings. (The CustomMetadataField will handle translating these from their human-readable values to the Atlan-internal ID strings needed for the search.)

   The hasAnyValue() predicate allows you to limit to assets that have any value for this custom metadata attribute.

4. Since you are searching for custom metadata, you probably want to include the values for custom metadata in each search result. This getAttributesForSearchResults() helper method will return all of the custom attributes within the RACI custom metadata structure. These will be encoded in the specific form required by the search for you.

   Note the use of _includesOnResults

   Since the getAttributesForSearchResults() helper will return a list of strings, you'll need to use the special _includesOnResults() method to add these for inclusion.

5. The search will only run when you call the stream() method, which will then lazily-load each page of results into a stream.

6. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

from pyatlan.cache.custom_metadata_cache import CustomMetadataCache
from pyatlan.client.atlan import AtlanClient
from pyatlan.model.fields.atlan_fields import CustomMetadataField
from pyatlan.model.fluent_search import FluentSearch

client = AtlanClient()  # (1)
request = (
    FluentSearch(_includes_on_results=CustomMetadataCache.get_attributes_for_search_results("RACI"))  # (2)
    .where(CustomMetadataField(set_name="RACI", attribute_name="Responsible").has_any_value())  # (3)
).to_request()  # (4)
for result in client.asset.search(request):  # (5)
    print(result)

1. Start with a client to run the search through. For the default client, you can always use AtlanClient().

2. To search across all assets, you can use a FluentSearch object.

   Since you are searching for custom metadata, you probably want to include the values for custom metadata in each search result. This get_attributes_for_search_results() helper method will return all of the custom attributes within the RACI custom metadata structure. These will be encoded in the specific form required by the search for you.

   Note the use of _includes_on_results

   Since the get_attributes_for_search_results() helper will return a list of strings, you'll need to use the special _includes_on_results parameter to add these for inclusion.

3. When searching for custom metadata attributes, you can construct a CustomMetadataField to start a clause that will match a custom metadata property. Since you are searching for the custom metadata attribute itself, there is no enum for the custom metadata or its property names, so these must be provided as strings. (The CustomMetadataField will handle translating these from their human-readable values to the Atlan-internal ID strings needed for the search.)

   The has_any_value() predicate allows you to limit to assets that have any value for this custom metadata attribute.

4. You can then translate the fluent search into an index search request.

5. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

val client = Atlan.getDefaultClient() // (1)
client.assets.select() // (2)
    .where(CustomMetadataField.of(client, "RACI", "Responsible").hasAnyValue()) // (3)
    ._includesOnResults(client.customMetadataCache.getAttributesForSearchResults("RACI")) // (4)
    .stream() // (5)
    .forEach { // (6)
        log.info { "Asset: $it" }
    }

1. Start with a client to run the search through. For the default client, you can always use Atlan.getDefaultClient().
2. To search across all assets, you can use the assets.select() convenience method on a client.

3. When searching for custom metadata attributes, you can construct a CustomMetadataField to start a clause that will match a custom metadata property. Since you are searching for the custom metadata attribute itself, there is no enum for the custom metadata or its property names, so these must be provided as strings. (The CustomMetadataField will handle translating these from their human-readable values to the Atlan-internal ID strings needed for the search.)

   The hasAnyValue() predicate allows you to limit to assets that have any value for this custom metadata attribute.

4. Since you are searching for custom metadata, you probably want to include the values for custom metadata in each search result. This getAttributesForSearchResults() helper method will return all of the custom attributes within the RACI custom metadata structure. These will be encoded in the specific form required by the search for you.

   Note the use of _includesOnResults

   Since the getAttributesForSearchResults() helper will return a list of strings, you'll need to use the special _includesOnResults() method to add these for inclusion.

5. The search will only run when you call the stream() method, which will then lazily-load each page of results into a stream.

6. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

Requires multiple API operations

Before you can search for custom metadata, you first need to have the Atlan-internal hashed-string representation of the custom metadata property. You will likely need to first retrieve the hashed-string representation.

{
  "dsl": { // (1)
    "query": { // (2)
      "exists": { // (3)
        "field": "omrIzGB4oYlZrFKfTIUz6D" // (4)
      }
    },
    "track_total_hits": true
  },
  "attributes": [
    "UQot6bU4XcGcIx8gAQ1dsW.omrIzGB4oYlZrFKfTIUz6D" // (5)
  ],
  "suppressLogs": true,
  "showSearchScore": false,
  "excludeMeanings": false,
  "excludeClassifications": false
}

1. Run a search to find the assets.
2. For a search with only a single condition, we can directly provide the condition.
3. You can use the exists criteria to match any assets that have some value (no matter what that value is) for a given field.
4. Use the Atlan-internal hashed-string representation of the custom metadata field name.
5. Include the Atlan-internal hashed-string representation of the custom metadata field name in the attributes list, so you can see the value of the custom metadata on each result. In this attributes list it needs to be written as <CustomMetadata>.<Attribute>, using the hashed-string representation for both pieces.

Assets with specific custom metadata value

1.4.0 1.1.0

This example finds all assets with a particular custom metadata attribute populated — with a specific value for the attribute.

Java Python Kotlin Raw REST API

AtlanClient client = Atlan.getDefaultClient(); // (1)
client.assets.select() // (2)
    .where(CustomMetadataField.of(client, "RACI", "Responsible").eq("This exact value", false)) // (3)
    ._includesOnResults(client.getCustomMetadataCache().getAttributesForSearchResults("RACI")) // (4)
    .stream() // (5)
    .forEach(a -> { // (6)
        log.info("Asset: {}", a);
    });

1. Start with a client to run the search through. For the default client, you can always use Atlan.getDefaultClient().
2. To search across all assets, you can use the assets.select() convenience method on a client.

3. When searching for custom metadata attributes, you can construct a CustomMetadataField to start a clause that will match a custom metadata property. Since you are searching for the custom metadata attribute itself, there is no enum for the custom metadata or its property names, so these must be provided as strings. (The CustomMetadataField will handle translating these from their human-readable values to the Atlan-internal ID strings needed for the search.)

   The eq() predicate allows you to limit to assets that have only the exact value provided for this custom metadata attribute (and in the case of a string value, you must supply a second parameter indicating whether the search should be case-sensitive (false) or case-insensitive (true)).

4. Since you are searching for custom metadata, you probably want to include the values for custom metadata in each search result. This getAttributesForSearchResults() helper method will return all of the custom attributes within the RACI custom metadata structure. These will be encoded in the specific form required by the search for you.

   Note the use of _includesOnResults

   Since the getAttributesForSearchResults() helper will return a list of strings, you'll need to use the special _includesOnResults() method to add these for inclusion.

5. The search will only run when you call the stream() method, which will then lazily-load each page of results into a stream.

6. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

from pyatlan.cache.custom_metadata_cache import CustomMetadataCache
from pyatlan.client.atlan import AtlanClient
from pyatlan.model.fields.atlan_fields import CustomMetadataField
from pyatlan.model.fluent_search import FluentSearch

client = AtlanClient()  # (1)
request = (
    FluentSearch(_includes_on_results=CustomMetadataCache.get_attributes_for_search_results("RACI"))  # (2)
    .where(CustomMetadataField(set_name="RACI", attribute_name="Responsible").eq("This exact value"))  # (3)
).to_request()  # (4)
for result in client.asset.search(request):  # (5)
    print(result)

1. Start with a client to run the search through. For the default client, you can always use AtlanClient().

2. To search across all assets, you can use a FluentSearch object.

   Since you are searching for custom metadata, you probably want to include the values for custom metadata in each search result. This get_attributes_for_search_results() helper method will return all of the custom attributes within the RACI custom metadata structure. These will be encoded in the specific form required by the search for you.

   Note the use of _includes_on_results

   Since the get_attributes_for_search_results() helper will return a list of strings, you'll need to use the special _includes_on_results parameter to add these for inclusion.

3. When searching for custom metadata attributes, you can construct a CustomMetadataField to start a clause that will match a custom metadata property. Since you are searching for the custom metadata attribute itself, there is no enum for the custom metadata or its property names, so these must be provided as strings. (The CustomMetadataField will handle translating these from their human-readable values to the Atlan-internal ID strings needed for the search.)

   The eq() predicate allows you to limit to assets that have only the exact value provided for this custom metadata attribute.

4. You can then translate the fluent search into an index search request.

5. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

val client = Atlan.getDefaultClient() // (1)
client.assets.select() // (2)
    .where(CustomMetadataField.of(client, "RACI", "Responsible").eq("This exact value", false)) // (3)
    ._includesOnResults(client.customMetadataCache.getAttributesForSearchResults("RACI")) // (4)
    .stream() // (5)
    .forEach { // (6)
        log.info { "Asset: $it" }
    }

1. Start with a client to run the search through. For the default client, you can always use Atlan.getDefaultClient().
2. To search across all assets, you can use the assets.select() convenience method on a client.

3. When searching for custom metadata attributes, you can construct a CustomMetadataField to start a clause that will match a custom metadata property. Since you are searching for the custom metadata attribute itself, there is no enum for the custom metadata or its property names, so these must be provided as strings. (The CustomMetadataField will handle translating these from their human-readable values to the Atlan-internal ID strings needed for the search.)

   The eq() predicate allows you to limit to assets that have only the exact value provided for this custom metadata attribute (and in the case of a string value, you must supply a second parameter indicating whether the search should be case-sensitive (false) or case-insensitive (true)).

4. Since you are searching for custom metadata, you probably want to include the values for custom metadata in each search result. This getAttributesForSearchResults() helper method will return all of the custom attributes within the RACI custom metadata structure. These will be encoded in the specific form required by the search for you.

   Note the use of _includesOnResults

   Since the getAttributesForSearchResults() helper will return a list of strings, you'll need to use the special _includesOnResults() method to add these for inclusion.

5. The search will only run when you call the stream() method, which will then lazily-load each page of results into a stream.

6. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

Requires multiple API operations

Before you can search for custom metadata, you first need to have the Atlan-internal hashed-string representation of the custom metadata property. You will likely need to first retrieve the hashed-string representation.

{
  "dsl": { // (1)
    "query": { // (2)
      "term": { // (3)
        "omrIzGB4oYlZrFKfTIUz6D": { // (4)
          "value": "This exact value" // (5)
        }
      }
    },
    "track_total_hits": true
  },
  "attributes": [
    "UQot6bU4XcGcIx8gAQ1dsW.omrIzGB4oYlZrFKfTIUz6D" // (6)
  ],
  "suppressLogs": true,
  "showSearchScore": false,
  "excludeMeanings": false,
  "excludeClassifications": false
}

1. Run a search to find the assets.
2. For a search with only a single condition, we can directly provide the condition.
3. You can use the term query to exactly match a value on assets, for a given field.
4. Use the Atlan-internal hashed-string representation of the custom metadata field name.
5. Provide the exact value you want to match in that custom metadata property.
6. Include the Atlan-internal hashed-string representation of the custom metadata field name in the attributes list, so you can see the value of the custom metadata on each result. In this attributes list it needs to be written as <CustomMetadata>.<Attribute>, using the hashed-string representation for both pieces.

Assets linked to a term

This example finds all assets that are linked to a specific glossary term. (And could be extended to do find assets linked to any one of a number of glossary terms.) In this specific example we will find any assets linked to a glossary term named Revenue in a glossary named Metrics.

You'll need the qualifiedName of the glossary term

To find the assets linked to the glossary term, you'll need to search using the qualifiedName of the term. This is not the human-readable name you see in the UI. So this example is split into two parts:

1. Finding the qualifiedName of the glossary term from its human-readable name and the result of (1).
2. Finding all assets linked to that glossary term.

1.4.0 1.1.0

For example:

Java Python Kotlin Raw REST API

GlossaryTerm term = GlossaryTerm.findByName("Revenue", "Concepts"); // (1)
String termQualifiedName = term.getQualifiedName(); // (2)

1. The GlossaryTerm.findByName() helper method will retrieve the glossary term by its human-readable name, given the name of the glossary in which it should exist. If the term does not exist (within that glossary), it will throw a NotFoundException.
2. If no exception was thrown, you can retrieve the qualifiedName of the glossary term.

AtlanClient client = Atlan.getDefaultClient(); // (1)
client.assets.select() // (2)
    .where(Asset.ASSIGNED_TERMS.in(List.of(termQualifiedName))) // (3)
    .stream() // (4)
    .forEach(a -> { // (5)
        log.info("Asset: {}", a);
    });

1. Start with a client to run the search through. For the default client, you can always use Atlan.getDefaultClient().
2. To search across all assets, you can use the assets.select() convenience method on a client.
3. When searching for assets linked to one or more terms, you need to use the qualifiedName of the term(s). (This example shows searching for just one term, but you could search for any number of them in the list. The search will find assets that are assigned at least one of those terms in the list.)
4. The search will only run when you call the stream() method, which will then lazily-load each page of results into a stream.
5. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

from pyatlan.client.atlan import AtlanClient
from pyatlan.model.fluent_search import FluentSearch, CompoundQuery

client = AtlanClient()  # (1)
term = client.asset.find_term_by_name("Revenue", "Concepts")  # (2)
term_qualified_name = term.qualified_name  # (3)

1. Start with a client to run the search through. For the default client, you can always use AtlanClient().
2. The asset.find_term_by_name() helper method will retrieve the glossary term by its human-readable name, given the name of the glossary in which it should exist. If the term does not exist (within that glossary), it will throw a NotFoundError.
3. If no exception was thrown, you can retrieve the qualified_name of the glossary term.

request = (
    FluentSearch()  # (1)
    .where(CompoundQuery.assigned_term([term_qualified_name]))  # (2)
).to_request()  # (3)
for result in client.asset.search(request):  # (4)
    print(result)

1. To search across all assets, you can use a FluentSearch object.
2. When searching for assets linked to a given term, you need to use the qualified_name of the term.
3. You can then translate the fluent search into an index search request.
4. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

val term = GlossaryTerm.findByName("Revenue", "Concepts") // (1)
val termQualifiedName = term.qualifiedName // (2)

1. The GlossaryTerm.findByName() helper method will retrieve the glossary term by its human-readable name, given the name of the glossary in which it should exist. If the term does not exist (within that glossary), it will throw a NotFoundException.
2. If no exception was thrown, you can retrieve the qualifiedName of the glossary term.

val client = Atlan.getDefaultClient() // (1)
client.assets.select() // (2)
    .where(Asset.ASSIGNED_TERMS.`in`(listOf(termQualifiedName))) // (3)
    .stream() // (4)
    .forEach { // (5)
        log.info { "Asset: $it" }
    }

1. Start with a client to run the search through. For the default client, you can always use Atlan.getDefaultClient().
2. To search across all assets, you can use the assets.select() convenience method on a client.
3. When searching for assets linked to one or more terms, you need to use the qualifiedName of the term(s). (This example shows searching for just one term, but you could search for any number of them in the list. The search will find assets that are assigned at least one of those terms in the list.)
4. The search will only run when you call the stream() method, which will then lazily-load each page of results into a stream.
5. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

Requires multiple API operations

Before you can search for assets linked to a term, you first need to have the qualifiedName of the term. You will likely need to first find the term by its name.

{
  "dsl": { // (1)
    "query": { // (2)
      "terms": { // (3)
        "__meanings": [ // (4)
          "5h2wMbSbWtRN1V1b05Mtb@LD5Tb30qbuYCZKsmFRpmS" // (5)
        ]
      }
    },
    "track_total_hits": true
  },
  "suppressLogs": true,
  "showSearchScore": false,
  "excludeMeanings": false,
  "excludeClassifications": false
}

1. Run a search to find the assets.
2. For a search with only a single condition, we can directly provide the condition.
3. You can use the terms query to exactly match a value on assets, for a given field, against a list of possible matches.
4. To find terms, match against the __meanings field.
5. Provide the exact value of the qualifiedName for the term for which you want to find linked assets.

Assets with an Atlan tag

1.4.0 2.0.0

This example finds all assets that are assigned a specific Atlan tag — irrespective of whether they were directly assigned the tag or it was propagated.

Java Python Kotlin Raw REST API

AtlanClient client = Atlan.getDefaultClient(); // (1)
client.assets.select() // (2)
    .tagged(List.of("PII")) // (3)
    .stream() // (4)
    .forEach(a -> { // (5)
        log.info("Asset: {}", a);
    });

1. Start with a client to run the search through. For the default client, you can always use Atlan.getDefaultClient().
2. To search across all assets, you can use the assets.select() convenience method on a client.
3. The .tagged() helper method allows us to limit to assets that match at least one of potentially multiple values (since there could be many tags on an asset). The SDK will translate the provided Atlan tag into the necessary internal representation required for the search — you can just provide the human-readable names of the Atlan tags.
4. The search will only run when you call the stream() method, which will then lazily-load each page of results into a stream.
5. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

from pyatlan.client.atlan import AtlanClient
from pyatlan.model.fluent_search import FluentSearch, CompoundQuery

client = AtlanClient()  # (1)
request = (
    FluentSearch()  # (2)
    .where(CompoundQuery.tagged(["PII"]))  # (3)
).to_request()  # (4)
for result in client.asset.search(request):  # (5)
    print(result)

1. Start with a client to run the search through. For the default client, you can always use AtlanClient().
2. To search across all assets, you can use a FluentSearch object.
3. The CompoundQuery.tagged() helper method allows us to limit to assets that match at least one of potentially multiple values (since there could be many tags on an asset). The SDK will translate the provided Atlan tag into the necessary internal representation required for the search — you can just provide the human-readable names of the Atlan tags.
4. You can then translate the fluent search into an index search request.
5. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

val client = Atlan.getDefaultClient() // (1)
client.assets.select() // (2)
    .tagged(listOf("PII")) // (3)
    .stream() // (4)
    .forEach { // (5)
        log.info { "Asset: $it" }
    }

1. Start with a client to run the search through. For the default client, you can always use Atlan.getDefaultClient().
2. To search across all assets, you can use the assets.select() convenience method on a client.
3. The .tagged() helper method allows us to limit to assets that match at least one of potentially multiple values (since there could be many tags on an asset). The SDK will translate the provided Atlan tag into the necessary internal representation required for the search — you can just provide the human-readable names of the Atlan tags.
4. The search will only run when you call the stream() method, which will then lazily-load each page of results into a stream.
5. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

Requires multiple API operations

Before you can search for Atlan tags, you first need to have the Atlan-internal hashed-string representation of the tags. You will likely need to first retrieve the hashed-string representation.

{
  "dsl": { // (1)
    "query": {
      "bool": { // (2)
        "minimum_should_match": "1", // (3)
        "should": [ // (4)
          {
            "terms": {
              "__traitNames": [ // (4)
                "wAI4bROOqCQzES8HCNso9F" // (5)
              ]
            }
          },
          {
            "terms": {
              "__propagatedTraitNames": [ // (6)
                "wAI4bROOqCQzES8HCNso9F" // (7)
              ]
            }
          }
        ]
      }
    },
    "track_total_hits": true
  },
  "suppressLogs": true,
  "showSearchScore": false,
  "excludeMeanings": false,
  "excludeClassifications": false
}

1. Run a search to find the assets.
2. To match both assets that are directly assigned the Atlan tag and those that were propagated the Atlan tag, use a bool query for multiple conditions.
3. Define the minimum number of conditions that need to match on an asset to be included in the results. In this example, you want either a direct or propagated Atlan tag, so should match at least one of the conditions provided.
4. Use __traitNames to match directly-classified assets.
5. Use the Atlan-internal hashed-string representation of the Atlan tag.
6. Use __propagatedTraitNames to match assets that have been propagated this Atlan tag.
7. Once again, use the Atlan-internal hashed-string representation of the Atlan tag.

Assets with a source tag

2.4.7 2.0.0

This example finds all assets that are assigned a specific source tag.

Java Python Kotlin Raw REST API

AtlanClient client = Atlan.getDefaultClient(); // (1)
client.assets.select() // (2)
    .taggedWithValue( // (3)
        "Sensitivity", // (4)
        "Highly Restricted", // (5)
        true // (6)
    )
    .stream() // (7)
    .forEach(a -> { // (8)
        log.info("Asset: {}", a);
    });

1. Start with a client to run the search through. For the default client, you can always use Atlan.getDefaultClient().
2. To search across all assets, you can use the assets.select() convenience method on a client.
3. The .taggedWithValue() helper method allows us to limit to assets that match having this particular tag and value combination.
4. You must specify the human-readable name of the Atlan tag that is mapped to a source tag. The SDK will translate the provided Atlan tag into the necessary internal representation required for the search — you can just provide the human-readable names of the Atlan tags.
5. You must also provide the value you want to match.
6. (Optional) You can restrict the search to only directly-tagged assets with the value using true, or look for all assets tagged with the value (whether directly or propagated).
7. The search will only run when you call the stream() method, which will then lazily-load each page of results into a stream.
8. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

from pyatlan.client.atlan import AtlanClient
from pyatlan.model.assets.core.asset import Asset
from pyatlan.model.fluent_search import CompoundQuery, FluentSearch

client = AtlanClient() # (1)

request = (
    FluentSearch()
    .select() # (2)
    .where(CompoundQuery.tagged_with_value( # (3)
      "Confidential", # (4)
      "Highly Restricted", # (5)
      True # (6)
    )
  )
).to_request() # (7)

response = client.asset.search(request) # (8)

for asset in response: # (9)
    ...

1. Start with a client to run the search through.
2. To search across all active assets, you can use the FluentSearch.select() method.
3. The CompoundQuery.tagged_with_value() helper method allows us to limit to assets that match having this particular tag and value combination.
4. You must specify the human-readable name of the Atlan tag that is mapped to a source tag. The SDK will translate the provided Atlan tag into the necessary internal representation required for the search — you can just provide the human-readable names of the Atlan tags.
5. You must also provide the value you want to match.
6. (Optional) You can restrict the search to only directly-tagged assets with the value using True, or look for all assets tagged with the value (whether directly or propagated) (False).
7. Now convert the given FluentSearch into an IndexSearchRequest object for the search.
8. The search will only run when you call the client.asset.search() method.
9. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

val client = Atlan.getDefaultClient() // (1)
client.assets.select() // (2)
    .taggedWithValue( // (3)
        "Sensitivity", // (4)
        "Highly Restricted", // (5)
        true // (6)
    )
    .stream() // (7)
    .forEach { // (8)
        log.info { "Asset: $it" }
    }

1. Start with a client to run the search through. For the default client, you can always use Atlan.getDefaultClient().
2. To search across all assets, you can use the assets.select() convenience method on a client.
3. The .taggedWithValue() helper method allows us to limit to assets that match having this particular tag and value combination.
4. You must specify the human-readable name of the Atlan tag that is mapped to a source tag. The SDK will translate the provided Atlan tag into the necessary internal representation required for the search — you can just provide the human-readable names of the Atlan tags.
5. You must also provide the value you want to match.
6. (Optional) You can restrict the search to only directly-tagged assets with the value using true, or look for all assets tagged with the value (whether directly or propagated).
7. The search will only run when you call the stream() method, which will then lazily-load each page of results into a stream.
8. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

Requires multiple API operations

Before you can search for Atlan tags, you first need to have the Atlan-internal hashed-string representation of the tags. You will likely need to first retrieve the hashed-string representation.

{
  "dsl": { // (1)
    "query": {
      "bool": { // (2)
        "filter": [
          {
            "term": {
              "__traitNames": { // (3)
                "value": "Z96sGJrF0S68PxYTUdKG6b", // (4)
                "case_insensitive": false
              }
            }
          },
          {
            "span_within": { // (5)
              "big": {
                "span_near": {
                  "clauses": [
                    {
                      "span_term": {
                        "__classificationsText.text": { // (6)
                          "value": "Z96sGJrF0S68PxYTUdKG6b"
                        }
                      }
                    },
                    {
                      "span_term": {
                        "__classificationsText.text": { // (7)
                          "value": "default/snowflake/1726834662/ANALYTICS/WIDE_WORLD_IMPORTERS/CONFIDENTIAL"
                        }
                      }
                    }
                  ],
                  "in_order": true,
                  "slop": 10000000
                }
              },
              "little": {
                "span_near": {
                  "clauses": [
                    {
                      "span_term": {
                        "__classificationsText.text": { // (8)
                          "value": "tagAttachmentValue"
                        }
                      }
                    },
                    {
                      "span_term": {
                        "__classificationsText.text": {
                          "value": "Highly" // (9)
                        }
                      }
                    },
                    {
                      "span_term": {
                        "__classificationsText.text": {
                          "value": "Restricted"
                        }
                      }
                    },
                    {
                      "span_term": {
                        "__classificationsText.text": {
                          "value": "tagAttachmentKey" // (10)
                        }
                      }
                    }
                  ],
                  "in_order": true,
                  "slop": 0
                }
              }
            }
          }
        ]
      }
    },
    "track_total_hits": true
  },
  "suppressLogs": true,
  "showSearchScore": false,
  "excludeMeanings": false,
  "excludeClassifications": false
}

1. Run a search to find the assets.
2. To match assets that are directly assigned the Atlan tag, use a bool query for multiple conditions.
3. Use __traitNames to match directly-classified assets.
4. Use the Atlan-internal hashed-string representation of the Atlan tag.
5. To match a source tag, you must use a span_within query that has this exact structure.
6. Once again, everywhere you specify the Atlan tag you must use the Atlan-internal hashed-string representation of the Atlan tag.
7. You must also specify the qualifiedName of the source Tag asset.
8. When matching a value, you must specify these little.span_near clauses in exactly the order shown in this example, starting with tagAttachmentValue.
9. The value itself should come next, but note that if there are any spaces in the value then you must specify a span_term for each individual word of the value.
10. Finally you must specify a span_term of tagAttachmentKey as the final clause.

Deprecated assets

1.4.0 1.1.0

This example finds all assets that are marked as deprecated.

Java Python Kotlin Raw REST API

AtlanClient client = Atlan.getDefaultClient(); // (1)
client.assets.select() // (2)
    .where(Asset.CERTIFICATE_STATUS.eq(CertificateStatus.DEPRECATED)) // (3)
    .stream() // (4)
    .forEach(a -> { // (5)
        log.info("Asset: {}", a);
    });

1. Start with a client to run the search through. For the default client, you can always use Atlan.getDefaultClient().
2. To search across all assets, you can use the assets.select() convenience method on a client.

3. The .where() method allows you to limit to only assets that have a particular value in a particular field. In this example, we are looking for values for the certificate status, so use Asset.CERTIFICATE_STATUS.

   Since we only want assets that are deprecated, we will query where that certificate is set to the CertificateStatus.DEPRECATED value. (No need to try to remember or ever even know what the precise string values for the certificates are — we've provided enums for them in the SDK.)

4. The search will only run when you call the stream() method, which will then lazily-load each page of results into a stream.

5. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

from pyatlan.client.atlan import AtlanClient
from pyatlan.model.assets import Asset
from pyatlan.model.enums import CertificateStatus
from pyatlan.model.fluent_search import FluentSearch

client = AtlanClient()  # (1)
request = (
    FluentSearch()  # (2)
    .where(Asset.CERTIFICATE_STATUS.eq(CertificateStatus.DEPRECATED.value))  # (3)
).to_request()  # (4)
for result in client.asset.search(request):  # (5)
    print(result)

1. Start with a client to run the search through. For the default client, you can always use AtlanClient().
2. To search across all assets, you can use a FluentSearch object.

3. The .where() method allows you to limit to only assets that have a particular value in a particular field. In this example, we are looking for values for the certificate status, so use Asset.CERTIFICATE_STATUS.

   Since we only want assets that are deprecated, we will query where that certificate is set to the CertificateStatus.DEPRECATED value. (No need to try to remember or ever even know what the precise string values for the certificates are — we've provided enums for them in the SDK.)

4. You can then translate the fluent search into an index search request.

5. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

val client = Atlan.getDefaultClient() // (1)
client.assets.select() // (2)
    .where(Asset.CERTIFICATE_STATUS.eq(CertificateStatus.DEPRECATED)) // (3)
    .stream() // (4)
    .forEach { // (5)
        log.info { "Asset: $it" }
    }

1. Start with a client to run the search through. For the default client, you can always use Atlan.getDefaultClient().
2. To search across all assets, you can use the assets.select() convenience method on a client.

3. The .where() method allows you to limit to only assets that have a particular value in a particular field. In this example, we are looking for values for the certificate status, so use Asset.CERTIFICATE_STATUS.

   Since we only want assets that are deprecated, we will query where that certificate is set to the CertificateStatus.DEPRECATED value. (No need to try to remember or ever even know what the precise string values for the certificates are — we've provided enums for them in the SDK.)

4. The search will only run when you call the stream() method, which will then lazily-load each page of results into a stream.

5. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

Requires multiple API operations

Before you can search for classifications, you first need to have the Atlan-internal hashed-string representation of the classification. You will likely need to first retrieve the hashed-string representation.

{
  "dsl": { // (1)
    "query": { // (2)
      "term": { // (3)
        "certificateStatus": { // (4)
          "value": "DEPRECATED" // (5)
        }
      }
    },
    "track_total_hits": true
  },
  "suppressLogs": true,
  "showSearchScore": false,
  "excludeMeanings": false,
  "excludeClassifications": false
}

1. Run a search to find the assets.
2. For a search with only a single condition, we can directly provide the condition.
3. You can use the term query to exactly match a value on assets, for a given field.
4. Use the name of the field you want to match. In this example, since you want to match a specific certificate, you can use the certificateStatus field.
5. Provide the exact value you want to match in that field. In this example, you will be matching only assets with a certificate of DEPRECATED.

Certified but incomplete assets

1.4.0 1.1.0

This example finds all assets that are marked as verified, but are missing a description — suggesting they are in fact incomplete.

Java Python Kotlin Raw REST API

AtlanClient client = Atlan.getDefaultClient(); // (1)
client.assets.select() // (2)
    .where(Asset.CERTIFICATE_STATUS.eq(CertificateStatus.VERIFIED)) // (3)
    .whereNot(Asset.DESCRIPTION.hasAnyValue()) // (4)
    .whereNot(Asset.USER_DESCRIPTION.hasAnyValue())
    .includeOnResults(Asset.OWNER_USERS) // (5)
    .includeOnResults(Asset.OWNER_GROUPS) // (6)
    .stream() // (7)
    .forEach(a -> { // (8)
        log.info("Asset: {}", a);
    });

1. Start with a client to run the search through. For the default client, you can always use Atlan.getDefaultClient().
2. To search across all assets, you can use the assets.select() convenience method on a client.

3. The where() helper method allows us to limit to only assets that meet a a particular condition. In this example, we are looking for values for the certificate status, so use Asset.CERTIFICATE_STATUS. (No need to try to remember or ever even know what the precise string value is for the name of this field — we've provided enums for them in the SDK.)

   Since we only want assets that are verified, we will query where that certificate is set to the CertificateStatus.VERIFIED value. (No need to try to remember or ever even know what the precise string values for the certificates are — we've provided enums for them in the SDK.)

4. You can use the whereNot() method to do the opposite — define all the conditions the search results must not match. Here we are limiting to only assets that have a description populated.

   The hasAnyValue() predicate method allows us to limit to only assets that have a user-defined description populated. In Atlan you have both description (crawled from source) and userDescription (user-defined or overridden). For this example use case, you probably want to check that both of these are empty.

5. As part of the search, you may want certain details included in every result. In this use case, you may want to know the asset owner — someone to confirm this should really be certified when there is no description.

6. In Atlan you have both users and groups that can own assets. For this example use case, you probably want to retrieve both of these for every result.
7. The search will only run when you call the stream() method, which will then lazily-load each page of results into a stream.
8. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

from pyatlan.client.atlan import AtlanClient
from pyatlan.model.assets import Asset
from pyatlan.model.enums import CertificateStatus
from pyatlan.model.fluent_search import FluentSearch

client = AtlanClient()  # (1)
request = (
    FluentSearch()  # (2)
    .where(Asset.CERTIFICATE_STATUS.eq(CertificateStatus.VERIFIED.value))  # (3)
    .where_not(Asset.DESCRIPTION.has_any_value())  # (4)
    .where_not(Asset.USER_DESCRIPTION.has_any_value())
    .include_on_results(Asset.OWNER_USERS)  # (5)
    .include_on_results(Asset.OWNER_GROUPS)  # (6)
).to_request()  # (7)
for result in client.asset.search(request):  # (8)
    print(result)

1. Start with a client to run the search through. For the default client, you can always use AtlanClient().
2. To search across all assets, you can use a FluentSearch object.

3. The .where() method allows you to limit to only assets that have a particular value in a particular field. In this example, we are looking for values for the certificate status, so use Asset.CERTIFICATE_STATUS.

   Since we only want assets that are verified, we will query where that certificate is set to the CertificateStatus.VERIFIED value. (No need to try to remember or ever even know what the precise string values for the certificates are — we've provided enums for them in the SDK.)

4. You can use the .where_not() method to do the opposite — define all the conditions the search results must not match. Here we are limiting to only assets that have a description populated.

   The has_any_value() predicate method allows us to limit to only assets that have a user-defined description populated. In Atlan you have both description (crawled from source) and userDescription (user-defined or overridden). For this example use case, you probably want to check that both of these are empty.

5. As part of the search, you may want certain details included in every result. In this use case, you may want to know the asset owner — someone to confirm this should really be certified when there is no description.

6. In Atlan you have both users and groups that can own assets. For this example use case, you probably want to retrieve both of these for every result.
7. You can then translate the fluent search into an index search request.
8. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

val client = Atlan.getDefaultClient() // (1)
client.assets.select() // (2)
    .where(Asset.CERTIFICATE_STATUS.eq(CertificateStatus.VERIFIED)) // (3)
    .whereNot(Asset.DESCRIPTION.hasAnyValue()) // (4)
    .whereNot(Asset.USER_DESCRIPTION.hasAnyValue())
    .includeOnResults(Asset.OWNER_USERS) // (5)
    .includeOnResults(Asset.OWNER_GROUPS) // (6)
    .stream() // (7)
    .forEach { // (8)
        log.info { "Asset: $it" }
    }

1. Start with a client to run the search through. For the default client, you can always use Atlan.getDefaultClient().
2. To search across all assets, you can use the assets.select() convenience method on a client.

3. The where() helper method allows us to limit to only assets that meet a a particular condition. In this example, we are looking for values for the certificate status, so use Asset.CERTIFICATE_STATUS. (No need to try to remember or ever even know what the precise string value is for the name of this field — we've provided enums for them in the SDK.)

   Since we only want assets that are verified, we will query where that certificate is set to the CertificateStatus.VERIFIED value. (No need to try to remember or ever even know what the precise string values for the certificates are — we've provided enums for them in the SDK.)

4. You can use the whereNot() method to do the opposite — define all the conditions the search results must not match. Here we are limiting to only assets that have a description populated.

   The hasAnyValue() predicate method allows us to limit to only assets that have a user-defined description populated. In Atlan you have both description (crawled from source) and userDescription (user-defined or overridden). For this example use case, you probably want to check that both of these are empty.

5. As part of the search, you may want certain details included in every result. In this use case, you may want to know the asset owner — someone to confirm this should really be certified when there is no description.

6. In Atlan you have both users and groups that can own assets. For this example use case, you probably want to retrieve both of these for every result.
7. The search will only run when you call the stream() method, which will then lazily-load each page of results into a stream.
8. This is the pattern for iterating through all results (across pages) covered in the Searching for assets portion of the SDK documentation.

{
  "dsl": { // (1)
    "query": {
      "bool": { // (2)
        "filter": [ // (3)
          {
            "term": {
              "certificateStatus": { // (4)
                "value": "VERIFIED"
              }
            }
          }
        ],
        "must_not": [ // (5)
          {
            "exists": {
              "field": "description"
            }
          },
          {
            "exists": {
              "field": "userDescription"
            }
          }
        ]
      }
    },
    "track_total_hits": true
  },
  "attributes": [
    "ownerUsers", // (6)
    "ownerGroups" // (7)
  ],
  "suppressLogs": true,
  "showSearchScore": false,
  "excludeMeanings": false,
  "excludeClassifications": false
}

1. Run a search to find the columns.

2. To start building up a query with multiple conditions, you can use a bool query in Elasticsearch.

3. You can use the filter criteria to define all the conditions the search results must match in a binary way (either matches or doesn't). This avoids the need to calculate a score for each result.

4. In this example, you are looking for verified assets. So you can begin by filtering only those assets with a certificateStatus of VERIFIED.

5. Since you want to find assets that specifically do not have other characteristics, use the must_not criteria to specify these. Specifically, match assets that do not have either a description or userDescription populated.

6. As part of the search, you may want certain details included in every result. In this use case, you may want to know the asset owner — someone to confirm this should really be certified when there is no description.

   Where did ownerUsers come from?

   The Models section of the site details all the attributes that exist in each different type of asset, and therefore which ones you can retrieve as additional details in each search result, like ownerUsers.

7. In Atlan you have both users and groups that can own assets. For this example use case, you probably want to retrieve both of these for every result.

   Where did ownerGroups come from?

   The Models section of the site details all the attributes that exist in each different type of asset, and therefore which ones you can retrieve as additional details in each search result, like ownerGroups.

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