airflow-dag-patterns

Name: airflow-dag-patterns
Author: SamarthaKV29

64stars12forks

How to install airflow-dag-patterns?

samarthakv29/antigravity-god-mode/airflow-dag-patterns

$npx -y skills add SamarthaKV29/antigravity-god-mode --skill airflow-dag-patterns

Installs into the current project.

Summary

Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

Files · 1

View on GitHub

SKILL.md

1	# Apache Airflow DAG Patterns
2
3	Production-ready patterns for Apache Airflow including DAG design, operators, sensors, testing, and deployment strategies.
4
5	## Use this skill when
6
7	- Creating data pipeline orchestration with Airflow
8	- Designing DAG structures and dependencies
9	- Implementing custom operators and sensors
10	- Testing Airflow DAGs locally
11	- Setting up Airflow in production
12	- Debugging failed DAG runs
13
14	## Do not use this skill when
15
16	- You only need a simple cron job or shell script
17	- Airflow is not part of the tooling stack
18	- The task is unrelated to workflow orchestration
19
20	## Instructions
21
22	1. Identify data sources, schedules, and dependencies.
23	2. Design idempotent tasks with clear ownership and retries.
24	3. Implement DAGs with observability and alerting hooks.
25	4. Validate in staging and document operational runbooks.
26
27	Refer to `resources/implementation-playbook.md` for detailed patterns, checklists, and templates.
28
29	## Safety
30
31	- Avoid changing production DAG schedules without approval.
32	- Test backfills and retries carefully to prevent data duplication.
33
34	## Resources
35
36	- `resources/implementation-playbook.md` for detailed patterns, checklists, and templates.

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airflow-dag-patterns

64stars12forks

View on GitHub

How to install airflow-dag-patterns?

samarthakv29/antigravity-god-mode/airflow-dag-patterns

$npx -y skills add SamarthaKV29/antigravity-god-mode --skill airflow-dag-patterns

Installs into the current project.

Summary

Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

Files · 1

View on GitHub

SKILL.md

1	# Apache Airflow DAG Patterns
2
3	Production-ready patterns for Apache Airflow including DAG design, operators, sensors, testing, and deployment strategies.
4
5	## Use this skill when
6
7	- Creating data pipeline orchestration with Airflow
8	- Designing DAG structures and dependencies
9	- Implementing custom operators and sensors
10	- Testing Airflow DAGs locally
11	- Setting up Airflow in production
12	- Debugging failed DAG runs
13
14	## Do not use this skill when
15
16	- You only need a simple cron job or shell script
17	- Airflow is not part of the tooling stack
18	- The task is unrelated to workflow orchestration
19
20	## Instructions
21
22	1. Identify data sources, schedules, and dependencies.
23	2. Design idempotent tasks with clear ownership and retries.
24	3. Implement DAGs with observability and alerting hooks.
25	4. Validate in staging and document operational runbooks.
26
27	Refer to `resources/implementation-playbook.md` for detailed patterns, checklists, and templates.
28
29	## Safety
30
31	- Avoid changing production DAG schedules without approval.
32	- Test backfills and retries carefully to prevent data duplication.
33
34	## Resources
35
36	- `resources/implementation-playbook.md` for detailed patterns, checklists, and templates.

People who liked this also viewed

6 picks

Type