vdk-oracle 0.1.1245476944

Support for VDK Managed Oracle connection

oracle

Support for VDK Managed Oracle connection

TODO: what the project is about, what is its purpose

Usage

pip install vdk-oracle

Configuration

(vdk config-help is useful command to browse all config options of your installation of vdk)

Name	Description	(example) Value
oracle_user	Username used when connecting to Oracle database	my_user
oracle_password	Password used when connecting to Oracle database	super_secret_shhhh
oracle_use_secrets	Set to True to use secrets to connect to Oracle	True
oracle_connection_string	The Oracle connection string	localhost:1521/free
oracle_host	The host of the Oracle database. Note: This gets overridden if oracle_connection_string is set.	localhost
oracle_port	The port of the Oracle database. Note: This gets overridden if oracle_connection_string is set.	1521
oracle_sid	The SID of the Oracle database. Note: This gets overridden if oracle_connection_string is set.	free
oracle_service_name	The Service name of the Oracle database. Note: This gets overridden if oracle_connection_string is set.	free
oracle_thick_mode	Python-oracledb is said to be in Thick mode when Oracle Client libraries are used. True by default. Set to False to disable Oracle Thick mode. More info: https://python-oracledb.readthedocs.io/en/latest/user_guide/appendix_b.html	True
oracle_ingest_batch_size	vdk-oracle splits ingestion payloads into batches. Change this config to control the batch size. Default is set to 100.	100

Example

CLI Queries

export VDK_ORACLE_USER=my_username
export VDK_ORACLE_PASSWORD=my_password
export VDK_ORACLE_CONNECTION_STRING=localhost:1521/free
vdk oracle-query -q "SELECT * FROM TEST_TABLE"

Note: Running CLI queries does not support secrets

Ingestion

import datetime
from decimal import Decimal

def run(job_input):

    # Ingest object
    payload_with_types = {
        "id": 5,
        "str_data": "string",
        "int_data": 12,
        "float_data": 1.2,
        "bool_data": True,
        "timestamp_data": datetime.datetime.fromtimestamp(1700554373),
        "decimal_data": Decimal(0.1),
    }

    job_input.send_object_for_ingestion(
        payload=payload_with_types, destination_table="test_table"
    )

    # Ingest tabular data
    col_names = [
        "id",
        "str_data",
        "int_data",
        "float_data",
        "bool_data",
        "timestamp_data",
        "decimal_data",
    ]
    row_data = [
        [
            0,
            "string",
            12,
            1.2,
            True,
            datetime.datetime.fromtimestamp(1700554373),
            Decimal(1.1),
        ],
        [
            1,
            "string",
            12,
            1.2,
            True,
            datetime.datetime.fromtimestamp(1700554373),
            Decimal(1.1),
        ],
        [
            2,
            "string",
            12,
            1.2,
            True,
            datetime.datetime.fromtimestamp(1700554373),
            Decimal(1.1),
        ],
    ]
    job_input.send_tabular_data_for_ingestion(
        rows=row_data, column_names=col_names, destination_table="test_table"
    )

Ingestion with type inference

Ingestion works with an already created table even if you pass strings in the payload. vdk-oracle infers the correct type based on the existing table.

create table test_table (
    id number,
    str_data varchar2(255),
    int_data number,
    float_data float,
    bool_data number(1),
    timestamp_data timestamp,
    decimal_data decimal(14,8),
    primary key(id))

def run(job_input):
    payload = {
        "id": "5",
        "str_data": "string",
        "int_data": "12",
        "float_data": "1.2",
        "bool_data": "False",
        "timestamp_data": "2023-11-21T08:12:53",
        "decimal_data": "0.1",
    }

    job_input.send_object_for_ingestion(payload=payload, destination_table="test_table")

Build and testing

pip install -r requirements.txt
pip install -e .
pytest

In VDK repo ../build-plugin.sh script can be used also.

Note about the CICD:

.plugin-ci.yaml is needed only for plugins part of Versatile Data Kit Plugin repo.

The CI/CD is separated in two stages, a build stage and a release stage. The build stage is made up of a few jobs, all which inherit from the same job configuration and only differ in the Python version they use (3.7, 3.8, 3.9 and 3.10). They run according to rules, which are ordered in a way such that changes to a plugin's directory trigger the plugin CI, but changes to a different plugin does not.