realit-singer-python 5.0.0

Singer.io utility library - PipelineWise and Meltano compatible

pipelinewise-singer-python

Writes the Singer format from Python.

This is a fork of Singer's singer-python made for PipelineWise.

Usage

Setup environment

This library depends on python3. We recommend using a virtualenv like this:

python3 -m venv ~/.virtualenvs/singer-python

Installation

Next, install this library:

source ~/.virtualenvs/singer-python/bin/activate
git clone http://github.com/singer-io/singer-python
cd singer-python
pip install

Usage example

Now, from python code within the same virtualenv, you can use the library:

import singer

singer.write_schema('my_table',
	            {'properties':{'id': {'type': 'string', 'key': True}}},
		    ['id'])
singer.write_records('my_table',
                     [{'id': 'b'}, {'id':'d'}])
singer.write_state({'my_table': 'd'})

Logging configuration

pipelinewise-singer-python by default doesn't use any predefined logging configuration, it's up to the calling library to define it. However, if the environment variable LOGGING_CONF_FILE is found and set then the pipelinewise-singer-python would use the path provided in the env variable as the logging configuration for the logger.

Singer Decimal

Enabling the use_singer_decimal = True in a tap will output decimal and floats as a string rather than their numeric representation.

Optional Setting:

A boolean setting: when enabled true in the config will outputs decimal and floating point numbers as strings to avoid loss of precision and scale. For supporting taps, there are hints in the schema message, format = "singer.decimal", and additionalProperties scale_precision dictionary providing precision and scale. For decimal data, the target can use this information to correctly replicate decimal data without loss. For the Floats and Number data type without precision and scale it is recommended that post processing formats the datatype based on an inspection of the data because the true data size is unknown / dynamic.

{
  "use_singer_decimal": true,
}

Developer Resources

Initialize your Development Environment

pip install poetry
poetry install

Create and Run Tests

Create tests within the tests/ directory and then run:

poetry run pytest

or

poetry run coverage run --parallel -m pytest

Continuous Integration

Run through the full suite of tests and linters by running

poetry run tox

These must pass in order for PR's to be merged.

License

Distributed under the Apache License Version 2.0