vamseeachanta
vamseeachanta/workspace-hub
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/vamseeachanta/workspace-hub --skill airflow-2-advanced-operators命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Write outbound email and external messages in Vamsee Achanta's voice — a subtle offer to help, never bold or rash claims. Load before drafting ANY email, LinkedIn/Collide reply, proposal note, or outreach sent under his name.
Save/publish analysis or computation results from ANY ecosystem repo to Hugging Face as a queryable, viewer-renderable dataset. Use when the user wants to "save results to hugging face", "publish dataset to HF", "hugging face data saving", "save analysis results", "hf dataset", "make results queryable", or "render via datasets-server API". Reshapes nested results into flat parquet tables, writes a dataset card with a viewer `configs:` block and provenance, applies license/public-vs-private routing, enforces a domain data-quality gate (faithful-to-source != correct), publishes to `aceengineer/<repo>-<projection>`, and verifies via the datasets-server API.
Clone, create, fork, configure, and manage GitHub repositories. Manage remotes, secrets, releases, and workflows. Works with gh CLI or falls back to git + GitHub REST API via curl.
基于 SOC 职业分类
正在显示 SKILL.md
| name | airflow-2-advanced-operators |
| description | Sub-skill of airflow: 2. Advanced Operators (+6). |
| version | 1.0.0 |
| category | operations |
| type | reference |
| scripts_exempt | true |
# dags/advanced_operators.py
"""
DAG demonstrating advanced operator patterns.
"""
from datetime import datetime, timedelta
from airflow import DAG
from airflow.operators.python import PythonOperator, BranchPythonOperator
from airflow.operators.bash import BashOperator
from airflow.operators.empty import EmptyOperator
*See sub-skills for full details.*
## 3. Sensors for Event-Driven Workflows
```python
# dags/sensor_patterns.py
"""
DAG demonstrating sensor patterns for event-driven workflows.
"""
from datetime import datetime, timedelta
from airflow import DAG
from airflow.operators.python import PythonOperator
from airflow.sensors.filesystem import FileSensor
from airflow.sensors.external_task import ExternalTaskSensor
*See sub-skills for full details.*
## 4. Hooks for External System Integration
```python
# dags/hooks_demo.py
"""
DAG demonstrating hook patterns for external system integration.
"""
from datetime import datetime, timedelta
from airflow import DAG
from airflow.operators.python import PythonOperator
from airflow.providers.postgres.hooks.postgres import PostgresHook
from airflow.providers.amazon.aws.hooks.s3 import S3Hook
*See sub-skills for full details.*
## 5. XCom for Task Communication
```python
# dags/xcom_patterns.py
"""
DAG demonstrating XCom patterns for inter-task communication.
"""
from datetime import datetime, timedelta
from airflow import DAG
from airflow.operators.python import PythonOperator
from airflow.models import XCom
*See sub-skills for full details.*
## 6. Variables and Connections
```python
# dags/config_management.py
"""
DAG demonstrating Variables and Connections for configuration.
"""
from datetime import datetime, timedelta
from airflow import DAG
from airflow.operators.python import PythonOperator
from airflow.models import Variable
from airflow.hooks.base import BaseHook
*See sub-skills for full details.*
## 7. Error Handling and Callbacks
```python
# dags/error_handling.py
"""
DAG demonstrating error handling and callback patterns.
"""
from datetime import datetime, timedelta
from airflow import DAG
from airflow.operators.python import PythonOperator
from airflow.operators.bash import BashOperator
from airflow.utils.trigger_rule import TriggerRule
*See sub-skills for full details.*
## 8. Docker and Kubernetes Deployment
```yaml
# docker-compose.yml - Production-ready Airflow deployment
version: '3.8'
x-airflow-common:
&airflow-common
image: apache/airflow:2.8.1
environment:
&airflow-common-env
AIRFLOW__CORE__EXECUTOR: CeleryExecutor
*See sub-skills for full details.*