PostgreSQL

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Add credentials

1. Create a new pipeline or open an existing pipeline.
2. Expand the left side of your screen to view the file browser.
3. Scroll down and click on a file named io_config.yaml.
4. Enter the following keys and values under the key named default (you can have multiple profiles, add it under whichever is relevant to you)

version: 0.1.1
default:
  POSTGRES_DBNAME: ...
  POSTGRES_HOST: ...
  POSTGRES_PASSWORD: ...
  POSTGRES_PORT: ...
  POSTGRES_USER: ...
  POSTGRES_CONNECTION_METHOD: direct
  POSTGRES_SSH_HOST:
  POSTGRES_SSH_PORT: 22
  POSTGRES_SSH_USERNAME:
  POSTGRES_SSH_PASSWORD:
  POSTGRES_SSH_PKEY:

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SSH tunneling

If you want to connect to Postgres cluster with ssh tunnel, update the value of POSTGRES_CONNECTION_METHOD to ssh_tunnel, and enter the values for keys with prefix POSTGRES_SSH.

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Using SQL block

1. Create a new pipeline or open an existing pipeline.
2. Add a data loader, transformer, or data exporter block.
3. Select SQL.
4. Under the Data provider dropdown, select PostgreSQL.
5. Under the Profile dropdown, select default (or the profile you added credentials underneath).
6. Next to the Save to schema label, enter the schema name you want this block to save data to.
7. Under the Write policy dropdown, select Replace or Append (please see SQL blocks guide for more information on write policies).
8. Enter in this test query: SELECT 1.
9. Run the block.

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Using Python block

1. Create a new pipeline or open an existing pipeline.
2. Add a data loader, transformer, or data exporter block (the code snippet below is for a data loader).
3. Select Generic (no template).
4. Enter this code snippet (note: change the config_profile from default if you have a different profile):

from mage_ai.data_preparation.repo_manager import get_repo_path
from mage_ai.io.config import ConfigFileLoader
from mage_ai.io.postgres import Postgres
from os import path
from pandas import DataFrame

if 'data_loader' not in globals():
    from mage_ai.data_preparation.decorators import data_loader


@data_loader
def load_data_from_postgres(**kwargs) -> DataFrame:
    query = 'SELECT 1'
    config_path = path.join(get_repo_path(), 'io_config.yaml')
    config_profile = 'default'

    with Postgres.with_config(ConfigFileLoader(config_path, config_profile)) as loader:
        return loader.load(query)

5. Run the block.