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databeaver

Data Model Orchestration

  • 0.2.11
  • PyPI
  • Socket score

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DataBeaver - Data Model Orchestration

DataBeaver is a tool that allows teams to easily realize, test, version, and share their data models.

Overview

The aim of data beaver is to create a deterministic process for realizing a given data model. Data beaver can be used as easily a command line utility or integrated into your application via the DataBeaver class.

Installing DataBeaver

To install Data Beaver you can run the command below.

pip install databeaver

Using Data Beaver

What Can I Do With Data Beaver

  • Build your data model - Traditionally creating your data was a labor intensive process. First you would write some sql then you would run the manually one by one. With Data Beaver a simple beaver build command will generate all the models in their correct order, respecting dependencies.
  • (Not Yet) Visualize Model Dependencies - In a large model it can be tricky to keep track on what tables depend on what other tables. Instead of trying to keep track of that yourself, let DataBeaver extract it directly from the sql and generate and image file for you all with the simple beaver visualize command

Using DataBeaver as a command line application

Step 1 - Create a New Project

Before we start we need to create the basic directory structure needed and a configuration file that can be edited.

Command

beaver create-project --name=<projectName>

Execute a model

Data Beaver can be used as either a command line application or as a module for a more direct integration.

Module Usage
from databeaver import DataModel
model = DataModel()
model.build()

Major Releases

VersionGoalStatus
0.1.0Add the command line utility 'beaver' and 'DataBeaver' classIn Progress
0.2.0Build a Model against in Postgres
0.3.0Build database models in MySQL

Minor Releases

VersionPurpose
0.0.37DataBeaver.build() now returns info on the models and files that were processed

Additional Documentation

Classes
Configuration

FAQs


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