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Top 12 Python apache-airflow Projects
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Project mention: Building in Public: Leveraging Tublian's AI Copilot for My Open Source Contributions | dev.to | 2024-02-12
Contributing to Apache Airflow's open-source project immersed me in collaborative coding. Experienced maintainers rigorously reviewed my contributions, providing constructive feedback. This ongoing dialogue refined the codebase and honed my understanding of best practices.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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Use these maintenance DAGs from the project https://github.com/teamclairvoyant/airflow-maintenance-dags
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couler
Unified Interface for Constructing and Managing Workflows on different workflow engines, such as Argo Workflows, Tekton Pipelines, and Apache Airflow.
author seems to be describing the kind of patterns you might make with https://argoproj.github.io/argo-workflows/ . or see for example https://github.com/couler-proj/couler , which is an sdk for describing tasks that may be submitted to different workflow engines on the backend.
it's a little confusing to me that the author seems to object to "pipelines" and then equate them with messaging-queues. for me at least, "pipeline" vs "workflow-engine" vs "scheduler" are all basically synonyms in this context. those things may or may not be implemented with a message-queue for persistence, but the persistence layer itself is usually below the level of abstraction that $current_problem is really concerned with. like the author says, eventually you have to track state/timestamps/logs, but you get that from the beginning if you start with a workflow engine.
i agree with author that message-queues should not be a knee-jerk response to most problems because the LoE for edge-cases/observability/monitoring is huge. (maybe reach for a queue only if you may actually overwhelm whatever the "scheduler" can handle.) but don't build the scheduler from scratch either.. use argowf, kubeflow, or a more opinionated framework like airflow, mlflow, databricks, aws lamda or step-functions. all/any of these should have config or api that's robust enough to express rate-limit/retry stuff. almost any of these choices has better observability out-of-the-box than you can easily get from a queue. but most importantly.. they provide idioms for handling failure that data-science folks and junior devs can work with. the right way to structure code is just much more clear and things like structuring messages/events, subclassing workers, repeating/retrying tasks, is just harder to mess up.
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astronomer-cosmos
Run your dbt Core projects as Apache Airflow DAGs and Task Groups with a few lines of code
Project mention: Run dbt projects as Apache Airflow DAGs and Task Groups with a few lines of code | news.ycombinator.com | 2023-05-01 -
ethereum-etl-airflow
Airflow DAGs for exporting, loading, and parsing the Ethereum blockchain data. How to get any Ethereum smart contract into BigQuery https://towardsdatascience.com/how-to-get-any-ethereum-smart-contract-into-bigquery-in-8-mins-bab5db1fdeee
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astro-sdk
Astro SDK allows rapid and clean development of {Extract, Load, Transform} workflows using Python and SQL, powered by Apache Airflow.
Project mention: Orchestration: Thoughts on Dagster, Airflow and Prefect? | /r/dataengineering | 2023-06-01Have you tried the Astro SDK? https://github.com/astronomer/astro-sdk
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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airflowctl
A CLI tool to streamline getting started with Apache Airflow™ and managing multiple Airflow projects
Project mention: A look at airflowctl, a tool to help developers manage Apache Airflow projects | dev.to | 2023-08-14NOTE! I found a small issue in that when you run in background mode, it creates a file (.airflowctl/.background_process_ids) which contains the parent PID. The PID was always off, so I needed to manually edit this. I have created an issue here so if this happens to you, follow that.
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covid-19-data-engineering-pipeline
A Covid-19 data pipeline on AWS featuring PySpark/Glue, Docker, Great Expectations, Airflow, and Redshift, templated in CloudFormation and CDK, deployable via Github Actions.
Project mention: COVID-19 data pipeline on AWS feat. Glue/PySpark, Docker, Great Expectations, Airflow, and Redshift, templated in CF/CDK, deployable via Github Actions | /r/dataengineering | 2023-04-03I've seen amazing projects here already, which honestly were a great inspiration, and today I would like to show you my project. Some time ago, I had the idea to apply every tool I wanted to learn or try out to the same topic and since then this idea has grown into an entire pipeline: https://github.com/moritzkoerber/covid-19-data-engineering-pipeline
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Project mention: First End-to-End Data Engineering Project: Formula 2 Data Pipeline for for Automated Updates of a Kaggle's dataset. | /r/dataengineering | 2023-07-06
GitHub Repository: here
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twitter_data-lakehouse_minio_drill_superset
Building a Data Lakehouse for Analyzing Elon Musk Tweets using MinIO, Apache Airflow, Apache Drill and Apache Superset
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A note from our sponsor - InfluxDB
www.influxdata.com | 28 Mar 2024
Index
What are some of the best open-source apache-airflow projects in Python? This list will help you:
Project | Stars | |
---|---|---|
1 | Airflow | 34,099 |
2 | elyra | 1,756 |
3 | airflow-maintenance-dags | 1,583 |
4 | couler | 879 |
5 | astronomer-cosmos | 431 |
6 | ethereum-etl-airflow | 385 |
7 | astro-sdk | 312 |
8 | airflow-chart | 266 |
9 | airflowctl | 165 |
10 | covid-19-data-engineering-pipeline | 22 |
11 | F2-Data-Pipeline | 8 |
12 | twitter_data-lakehouse_minio_drill_superset | 3 |