PostgreSQL assets app

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The PostgreSQL assets app crawls PostgreSQL databases, schemas, tables, views, and columns and publishes them to Atlan. Build it with the PostgresCrawler builder, which mirrors the "new app" wizard: Credential → Connection → Metadata.

Creating an app creates a new connection

Each create mints a new connection and new assets. To re-crawl, re-run the existing workflow (see Re-run an existing app).

PostgreSQL supports three authentication methods: basic (username/password) and two AWS RDS IAM methods (IAM role and IAM user). The port is optional and defaults to 5432.

Basic authentication

Python

PostgreSQL crawling with basic auth

from pyatlan.client.atlan import AtlanClient
from pyatlan.model.apps import PostgresCrawler

client = AtlanClient()

response = (
    PostgresCrawler(client)
    .basic( # (1)
        username="atlan_user", # (2)
        password="••••••", # (3)
        database="analytics", # (4)
        host="mydb.abc123.us-east-1.rds.amazonaws.com", # (5)
    )
    .connection( # (6)
        name="production-postgres",
        admin_roles=[client.role_cache.get_id_for_name("$admin")],
    )
    .include_metadata({"analytics": ["public", "sales"]}) # (7)
    .run(name="postgres-prod") # (8)
)
print(response.slug, response.run_id)

1. Step 1—Credential. Username/password auth; the secret is vaulted.
2. Required. Database username.
3. Required. Password.
4. Required. Database to connect to.
5. Optional. Database host. The port (port=) is optional and defaults to 5432.
6. Step 2—Connection. Display name + at least one admin.
7. Step 3—Metadata. Schemas to crawl, as {database: [schema, ...]}. Omit to crawl everything. Exclude takes priority over include.
8. .run(name=...) creates and submits a run; use .create(name=...) to create without running.

AWS RDS IAM authentication

For PostgreSQL on AWS RDS, authenticate with an IAM role or IAM user:

Python

PostgreSQL on RDS with IAM auth

# IAM role
PostgresCrawler(client).iam_role(
    username="db_user", # (1)
    aws_role_arn="arn:aws:iam::123456789012:role/atlan", # (2)
    aws_region="us-east-1", # (3)
    database="analytics", # (4)
    aws_external_id="...", # (5)
    host="mydb.abc123.us-east-1.rds.amazonaws.com",
)

# IAM user
PostgresCrawler(client).iam_user(
    username="AKIA...", # (6)
    password="••••••", # (7)
    username_2="db_user", # (8)
    aws_region="us-east-1",
    database="analytics",
    host="mydb.abc123.us-east-1.rds.amazonaws.com",
)

1. Required. Database username.
2. Required. The IAM role ARN to assume.
3. Required. AWS region. rds_port and port are optional.
4. Required. Database to connect to.
5. Optional. AWS external id for the role.
6. Required. AWS access key.
7. Required. AWS secret key.
8. Required. The database username (distinct from the AWS access key).

Configuration options

All metadata options are optional—set only what you need:

Python

PostgreSQL metadata configuration

(
    PostgresCrawler(client)
    .basic(username="atlan_user", password="••••••", database="analytics", host="...")
    .connection(name="production-postgres", admin_roles=[...])
    .include_metadata({"analytics": ["public"]}) # (1)
    .exclude_metadata({"analytics": ["staging"]}) # (2)
    .exclude_regex_for_tables_views(".*_tmp$") # (3)
    .enable_source_level_filtering(False) # (4)
    .advanced_config("default") # (5)
    .control_config("custom") # (6)
    .custom_config('{"flag": true}') # (7)
    .run(name="postgres-prod")
)

1. Databases/schemas to include, as {database: [schema, ...]}.
2. Databases/schemas to exclude—exclude takes priority over include.
3. Regex of tables/views to ignore.
4. Apply schema-level filtering at the source (only the include-filter schemas are fetched).
5. Set the crawler's advanced configuration.
6. Switch advanced config to custom to enable experimental feature flags.
7. Custom feature-flag config as a JSON string (used when control_config is custom).