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dds_py - Data driven software

Data-driven software (python implementation)

Introduction

The DDS package solves the synchronization problem between code and data. It allows programmers, scientists and data scientists to integrate code with data and data with code without fear of stale data, disparate storage frameworks or concurrency issues. DDS allows quick collaboration and data software reuse without the complexity. In short, you do not have to think about changes in your data pipelines.

How to use

This package is published on PyPI:

pip install dds_py

This package is known to work on python 3.8, 3.9, 3.10, 3.11. No other versions are officially supported. Python 3.4 and 3.5 might work but they are not supported.

Plotting dependencies If you want to plot the graph of data dependencies, you must install separately the pydotplus package, which requires graphviz on your system to work properly. Consult the documentation of the pydotplus package for more details. The pydotplus package is only required with the dds_export_graph option.

Databricks users: If you want to use this package with Databricks, some specific hooks for Spark are available. See this notebook for a complete example:

https://databricks-prod-cloudfront.cloud.databricks.com/public/4027ec902e239c93eaaa8714f173bcfc/7816249071411394/4492656151009213/5450662050199348/latest.html

Documentation

API reference, tutorials and FAQs are located here: https://tjhunter.github.io/dds_py/

Example

Here is the Hello world example (using type annotations for clarity)

import dds
import requests 

@dds.data_function("/hello_data")
def data() -> str:
  url = "https://gist.githubusercontent.com/bigsnarfdude/515849391ad37fe593997fe0db98afaa/raw/f663366d17b7d05de61a145bbce7b2b961b3b07f/weather.csv"
  return requests.get(url=url, verify=False).content.decode("utf-8")

data()

This example does the following:

  • it defines a source of data, here a piece of weather data from the internet. This source is defined as the function data_creator
  • it assigns the data produced by this source into a variable (data) and also to a path in a storage system (/hello_data)

The DDS library guarantees the following after evaluation of the code:

  1. the path /hello_data contains a copy of the data returned by data_creator, as if the function data_creator had been called at this moment
  2. the function data_creator is only evaluated when its inputs, or its code, are modified (referential transparency)

License

The dds package is published under the Affero General Public License.