30daysofairflow
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Pipeline | 4,159 | a year ago | 85 | July 18, 2017 | 1 | apache-2.0 | Jsonnet | |||
| PipelineAI Kubeflow Distribution | ||||||||||
| Orchest | 3,876 | 4 months ago | 19 | December 13, 2022 | 125 | apache-2.0 | TypeScript | |||
| Build data pipelines, the easy way 🛠️ | ||||||||||
| Docker Airflow | 3,589 | 8 months ago | 269 | apache-2.0 | Shell | |||||
| Docker Apache Airflow | ||||||||||
| Awesome Apache Airflow | 3,060 | a year ago | 2 | Shell | ||||||
| Curated list of resources about Apache Airflow | ||||||||||
| Elyra | 1,672 |  | 14 | 9 hours ago | 111 | March 29, 2023 | 267 | apache-2.0 | Python | |
| Elyra extends JupyterLab with an AI centric approach. | ||||||||||
| Airflow Tutorial | 669 | 2 years ago | 18 | mit | Jupyter Notebook | |||||
| Apache Airflow tutorial | ||||||||||
| Kube Airflow | 556 | 4 years ago | 30 | apache-2.0 | Python | |||||
| A docker image and kubernetes config files to run Airflow on Kubernetes | ||||||||||
| Data Pipelines With Apache Airflow | 503 | 4 months ago | 35 | other | Python | |||||
| Code for Data Pipelines with Apache Airflow | ||||||||||
| Energy Forecasting | 490 | 19 days ago | mit | Python | ||||||
| 🌀 𝗧𝗵𝗲 𝗙𝘂𝗹𝗹 𝗦𝘁𝗮𝗰𝗸 𝟳-𝗦𝘁𝗲𝗽𝘀 𝗠𝗟𝗢𝗽𝘀 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 | Learn MLE & MLOps for free by designing, building and deploying an end-to-end ML batch system ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 2.5 𝘩𝘰𝘶𝘳𝘴 𝘰𝘧 𝘳𝘦𝘢𝘥𝘪𝘯𝘨 & 𝘷𝘪𝘥𝘦𝘰 𝘮𝘢𝘵𝘦𝘳𝘪𝘢𝘭𝘴 | ||||||||||
| Astronomer | 450 | 3 hours ago | 23 | other | Python | |||||
| Helm Charts for the Astronomer Platform, Apache Airflow as a Service on Kubernetes | ||||||||||
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Readme
30 Days Of Airflow
As work needed, I start to learn about building data pipeline and how to use apache airflow. I really love its design and how it works, so I decide to share my experience to who are going to learn airflow.
In this tutorial, I will cover things below:
- Introduction & definition
- Core concept (dag, operators ...)
- Basic operators
- Additional features (var, xcom, branch, hook, conn...)
- Tips & Tricks
- Dockerize
- More advanced features(may not cover)
Hope you can learn from it : )
*If you find this helpful, give me a star or share this to your colleagues/classmates.
Found mistakes?
Feel free to make a pull request if you find any mistake or better way to make the explanation more clear.
Contact me
Contact me through email in english or chinese.
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