it defines a source of data, here a piece of weather data from the internet.data_function ( "/hello_data" ) def data () -> str : url = "" return requests. Here is the Hello world example (using type annotations for clarity) import dds import requests. See this notebook for a complete example:ĪPI reference, tutorials and FAQs are located here: Example The pydotplus package is only required with the dds_export_graph option.ĭatabricks users: If you want to use this package with Databricks, some specific hooks for Spark are available. Consult the documentation of the pydotplus package for more details. 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. Python 3.4 and 3.5 might work but they are not supported. No other versions are officially supported. This package is known to work on python 3.6, 3.7, 3.8, 3.9. This package is published on PyPI: pip install dds_py In short, you do not have to think about changes in your data pipelines. DDS allows quick collaboration andĭata software reuse without the complexity. Stale data, disparate storage frameworks or concurrency issues.
Scientists and data scientists to integrate code with data and data with code without fear of The DDS package solves the synchronization problem between code and data. Data-driven software (python implementation) Introduction
0 kommentar(er)
