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Skill v1.0.0

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version: "1.0.0" name: aidp-netsuite description: Read NetSuite SuiteAnalytics Connect data from an AIDP notebook through the AIDP aidataplatform Spark format handler. Use when the user mentions NetSuite, SuiteAnalytics Connect, ns.account.id, ns.role.id, or ns.access.token. Supports username/password or OAuth access-token authentication. Read-only. allowed-tools: Read, Write, Edit, Bash

aidp-netsuite — NetSuite SuiteAnalytics Connect via AIDP aidataplatform

Use the built-in NETSUITE connector for read-only SuiteAnalytics Connect ingestion. It supports either username/password authentication or a fresh OAuth 2.0 access token.

When to use

  • Read NetSuite data through SuiteAnalytics Connect from an AIDP notebook.
  • Mentioned: "NetSuite", "SuiteAnalytics Connect", ns.account.id, ns.role.id, or ns.access.token.

When NOT to use

  • For NetSuite RESTlets or SuiteTalk REST APIs, use a REST-specific integration rather than this JDBC-style connector.
  • For NetSuite writes, explain that the AIDP 4.0 NetSuite connector is read-only.

Username and password read

python
import os
from oracle_ai_data_platform_connectors.aidataplatform import (
    AIDP_FORMAT, aidataplatform_options,
)
opts = aidataplatform_options(
    type="NETSUITE",
    host=os.environ["NETSUITE_HOST"],
    port=int(os.environ["NETSUITE_PORT"]),
    user=os.environ["NETSUITE_USER"],
    password=os.environ["NETSUITE_PASSWORD"],
    schema=os.environ["NETSUITE_SCHEMA"],
    table=os.environ["NETSUITE_TABLE"],
    extra={
        "ns.account.id": os.environ["NETSUITE_ACCOUNT_ID"],
        "ns.role.id": os.environ["NETSUITE_ROLE_ID"],
    },
)
df = spark.read.format(AIDP_FORMAT).options(**opts).load()
df.show(10)

OAuth access-token read

Use ns.access.token instead of user.name and password. Keep the access token in an environment variable or secret manager; never hard-code it in a notebook.

python
token_opts = aidataplatform_options(
    type="NETSUITE",
    host=os.environ["NETSUITE_HOST"],
    port=int(os.environ["NETSUITE_PORT"]),
    schema=os.environ["NETSUITE_SCHEMA"],
    table=os.environ["NETSUITE_TABLE"],
    extra={
        "ns.account.id": os.environ["NETSUITE_ACCOUNT_ID"],
        "ns.role.id": os.environ["NETSUITE_ROLE_ID"],
        "ns.access.token": os.environ["NETSUITE_ACCESS_TOKEN"],
    },
)
df = spark.read.format(AIDP_FORMAT).options(**token_opts).load()
df.show(10)

Pushdown SQL

python
pushdown_df = (spark.read.format(AIDP_FORMAT)
    .options(**token_opts)
    .option("pushdown.sql", "SELECT * FROM <SCHEMA>.<TABLE_NAME> WHERE <COLUMN_NAME> = '<VALUE>'")
    .load())
pushdown_df.show(10)

Gotchas

  • Read-only in 4.0. Do not generate df.write, saveAsTable, insertInto, or write.mode examples.
  • Choose one authentication mode. Use either user.name/password or ns.access.token, not both.
  • Token freshness matters. Refresh ns.access.token before it expires.
  • SuiteAnalytics Connect access is required. The account and role must be entitled to the schemas and tables requested.

References

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