Skip to main content

`target-postgres` is a Singer target for Postgres, built with the Meltano SDK for Singer Targets.

Project description

target-postgres

Target for Postgres.

Built with the Meltano SDK for Singer Taps and Targets. This target is in development, it probably doesn't work yet, stick with https://hub.meltano.com/loaders/target-postgres . Generally the goal here is to create a generalized target enough so that the SDK can automate >80% of testing for new targets, and potentially so taps can test very easily with a real local target.

Limitations

  1. Target is not working with Empty key properties. See https://github.com/MeltanoLabs/target-postgres/issues/54

Capabilities

  • about
  • stream-maps
  • schema-flattening

Settings

Setting Required Default Description
host False None Hostname for postgres instance. Note if sqlalchemy_url is set this will be ignored.
port False 5432 The port on which postgres is awaiting connection. Note if sqlalchemy_url is set this will be ignored.
user False None User name used to authenticate. Note if sqlalchemy_url is set this will be ignored.
password False None Password used to authenticate. Note if sqlalchemy_url is set this will be ignored.
database False None Database name. Note if sqlalchemy_url is set this will be ignored.
sqlalchemy_url False None SQLAlchemy connection string. This will override using host, user, password, port,dialect. Note that you must escape password special characters properly. See https://docs.sqlalchemy.org/en/20/core/engines.html#escaping-special-characters-such-as-signs-in-passwords
dialect+driver False postgresql+psycopg2 Dialect+driver see https://docs.sqlalchemy.org/en/20/core/engines.html. Generally just leave this alone. Note if sqlalchemy_url is set this will be ignored.
default_target_schema False None Postgres schema to send data to, example: tap-clickup
hard_delete False 0 When activate version is sent from a tap this specefies if we should delete the records that don't match, or mark them with a date in the _sdc_deleted_at column.
add_record_metadata False 1 Note that this must be enabled for activate_version to work!This adds _sdc_extracted_at, _sdc_batched_at, and more to every table. See https://sdk.meltano.com/en/latest/implementation/record_metadata.html for more information.
stream_maps False None Config object for stream maps capability. For more information check out Stream Maps.
stream_map_config False None User-defined config values to be used within map expressions.
flattening_enabled False None 'True' to enable schema flattening and automatically expand nested properties.
flattening_max_depth False None The max depth to flatten schemas.

A full list of supported settings and capabilities is available by running: target-postgres --about

Installation

  • Developer TODO: Come back to this re #5
pipx install -e .

Configuration

Configure using environment variables

This Singer target will automatically import any environment variables within the working directory's .env if the --config=ENV is provided, such that config values will be considered if a matching environment variable is set either in the terminal context or in the .env file.

Source Authentication and Authorization

The database account provided must have access to:

  1. Create schemas
  2. Create tables (DDL)
  3. Push Data to tables (DML)

Usage

You can easily run target-postgres by itself or in a pipeline using Meltano.

Executing the Target Directly

target-postgres --version
target-postgres --help
# Test using the "Carbon Intensity" sample:
pipx install git+https://gitlab.com/meltano/tap-carbon-intensity
tap-carbon-intensity | target-postgres --config /path/to/target-postgres-config.json

Developer Resources

Initialize your Development Environment

pipx install poetry
poetry install
pipx install pre-commit
pre-commit install

Create and Run Tests

Create tests within the target_postgres/tests subfolder and then run:

poetry run pytest

You can also test the target-postgres CLI interface directly using poetry run:

poetry run target-postgres --help

Testing with Meltano

Note: This target will work in any Singer environment and does not require Meltano. Examples here are for convenience and to streamline end-to-end orchestration scenarios.

Your project comes with a custom meltano.yml project file already created.

Next, install Meltano (if you haven't already) and any needed plugins:

# Install meltano
pipx install meltano
# Initialize meltano within this directory
meltano install

Now you can test and orchestrate using Meltano:

# Test invocation:
meltano invoke target-postgres --version

SDK Dev Guide

See the dev guide for more instructions on how to use the Meltano SDK to develop your own Singer taps and targets.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

meltanolabs_target_postgres-0.0.5.tar.gz (210.0 kB view hashes)

Uploaded Source

Built Distribution

meltanolabs_target_postgres-0.0.5-py3-none-any.whl (231.0 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page