deflow 0.0.2

Lightweight Declarative Data Framework

DeFlow

A Lightweight Declarative Data Framework that build on the 🏃 Workflow package.

I want to use this project is the real-world use-case for my 🏃 Workflow package that able to handle production data pipeline with the DataOps strategy.

[!WARNING] This framework does not allow you to custom your pipeline yet. If you want to create you workflow, you can use the 🏃 Workflow package instead that already installed.

In my opinion, I think it should not create duplicate workflow codes if I can write with dynamic input parameters on the one template workflow that just change the input parameters per use-case instead. This way I can handle a lot of logical workflows in our orgs with only metadata configuration. It called Metadata Driven Data Workflow.

📦 Installation

pip install -U deflow

:dart: Usage

Version 1

After initialize data framework project with Version 1, your data pipeline config files will store with this file structure:

conf/
 ├─ conn/
 │   ├─ c_conn_01.yml
 │   ╰─ c_conn_02.yml
 ├─ routes/
 │   ╰─ routing.yml
 ╰─ stream/
     ╰─ s_stream_01/
         ├─ g_group_01.tier.priority/
         │   ├─ p_proces_01.yml
         │   ╰─ p_proces_02.yml
         ├─ g_group_02.tier.priority/
         │   ├─ p_proces_01.yml
         │   ╰─ p_proces_02.yml
         ╰─ config.yml

You can run the data flow by:

from deflow.flow import Flow
from ddeutil.workflow import Result

flow: Result = Flow(name="s_stream_01").run(mode="N")

:cookie: Configuration

Support data framework version:

Version	Supported	Description
1	Yes	A data framework that base on stream, group, and process

💬 Contribute

I do not think this project will go around the world because it has specific propose, and you can create by your coding without this project dependency for long term solution. So, on this time, you can open the GitHub issue on this project 🙌 for fix bug or request new feature if you want it.