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Basic pipeline for all vedana projects.

This pipeline:

  • Parses Grist Data & Data Model
  • Ensures that Memgraph index/vector index structure is in sync with data model
  • Updates Memgraph database in incremental fashion

To add steps:

  1. Pass extra transformations to get_pipeline
  2. Create new app configuration from app.py

Pipeline Labels Hierarchy

Pipeline

labels=("pipeline", "pipeline_name") defines a set of operations as standalone, sort of like a DAG in Airflow or a Dagster Job. Its purpose is to be able to render it as a separate tab on the ETL page of Backoffice in order to look at it independently of other transformations

Stage

labels=("stage", "stage_name") defines a stage of pipeline. Currently, stages are useful for creating and managing observability features, such as main dashboard's Ingest table, which displays DataTable's of all transformations with labels=("stage", "extract"). Stages are also useful when running the pipeline manually.

Flow

labels=("flow", "flow_name") helps execute a pipeline (or possibly several pipelines) in a nice fashion, used in defining cron jobs, etc.

Metadata

Release files for vedana-etl 0.9.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for vedana-etl 0.9.0
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vedana_etl-0.9.0.tar.gz 1.7 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for vedana-etl 0.9.0
File Interpreter ABI Platform
vedana_etl-0.9.0-py3-none-any.whl Python 3 none any Details

Total release size: 1.7 MB

Release files / vedana_etl-0.9.0.tar.gz

Download URL vedana_etl-0.9.0.tar.gz
Size 1.7 MB
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Release files / vedana_etl-0.9.0-py3-none-any.whl

Download URL vedana_etl-0.9.0-py3-none-any.whl
Size 14.5 kB
Tags Python 3
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Uploaded via twine/6.1.0 CPython/3.13.12

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