syngenta-digital-dta 0.0.3

A DRY multi-database normalizer.

Syngenta Digital DTA (Database Adapter)

A DRY multi-database normalizer.

Features

• Use the same package with multiple database engines
• Able to validate your data against predefined schema in code (for no-schems solutions)
• Creates easy pub-sub architecture based on model changes
• Local development support

Philosophy

The dta philosophy is to use one pattern with multiple databases

The dta encourages pub-sub architecture by allowing for the automatic publishing of data over SNS.

Installation

This is a python module available through the pypi registry.

Before installing, download and install python. python 3 or higher is required.

Installation is done using the pip install command:

$ pip install syngenta_digital_dta

or

$ pipenv install syngenta_digital_dta

Common Usage: DynamoDB

import os
import syngenta_digital_dta

adapter = syngenta_digital_dta.adapter(
    engine='dynamodb',
    table=os.getenv('DYNAMODB_TABLE'),
    endpoint='http://localhost:4000',
    model_schema='v1-table-model',
    model_schema_file='application/openapi.yml',
    model_identifier='test_id',
    model_version_key='modified'
)

Initialize Options

Option Name	Required	Type	Description
engine	true	string	name of supported db engine (dynamodb)
table	true	string	name of dynamodb table
endpoint	false	string	url of the dynamodb table (useful for local development)
model_schema	true	string	key of openapi schema this is being set against
model_schema_file	true	string	path where your schema file can found (accepts JSON as well)
model_identifier	true	string	unique identifier key on the model
model_version_key	true	string	key that can be used as a version key (modified timestamps often suffice)
author_identifier	false	string	unique identifier of the author who made the change (optional)
sns_topic_arn	false	string	sns topic arn you want to broadcast the changes to

# create
result = adapter.create(
    operation='insert', # or overwrite (optional); defaults to insert
	data=some_dict_to_insert_into_the_table,
)

# insert
result = adapter.insert(
	data=some_dict_to_insert_into_the_table,
)

# get
result = adapter.read(
    operation='get', # or query or scan (optional); defaults to get
	query={
	   'Key': {
	        'example_id': '3'
	   }
    }
)

# get
result = adapter.get(
	query={
	   'Key': {
	        'example_id': '3'
	   }
    }
)

# update
result = adapter.update(
	data=some_dict_to_update_the_model,
	operation='get',
	query={
	   'Key': {
	        'example_id': '3'
	   }
    }
)

# delete
result = adapter.delete(
	query={
	   'Key': {
	        'example_id': '3'
	   }
    }
)

Contributing

If you would like to contribute please make sure to follow the established patterns and unit test your code:

Unit Testing

To run unit test, enter command:

RUN_MODE=unittest python -m unittest discover