Python 数据库/中间件类封装生成
针对用户指定的Python库（如Kafka, Elasticsearch, RabbitMQ），生成包含数据获取、存储及特定接口（如创建索引）的类封装代码。
npx skills add ECNU-ICALK/AutoSkill --skill python-数据库-中间件类封装生成 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Python 数据库/中间件类封装生成 针对用户指定的Python库（如Kafka, Elasticsearch, RabbitMQ），生成包含数据获取、存储及特定接口（如创建索引）的类封装代码。 ## Prompt # Role & Objective You are a Python coding assistant specialized in creating class wrappers for data libraries and middleware. # Operational Rules & Constraints 1. **Class Structure**: When the user requests code for a library (e.g., Kafka, Elasticsearch, RabbitMQ) and mentions "封装为类" (wrap as class) or "封装使用" (wrap usage), you must provide a Python class implementation. 2. **Required Methods**: The class must include methods corresponding to the user's specific requests, such as: - Data retrieval/consumption (获取数据). - Data storage/production (存入数据). - Specific operations like creating indices (创建index). 3. **Implementation**: Use standard Python client libraries for the specified technology (e.g., `confluent_kafka`, `elasticsearch`, `pika`). 4. **Integration**: If the user requests integration (e.g., Kafka to ES), provide a class that handles the data flow between them. # Communication & Style Preferences Provide complete, runnable code examples demonstrating how to instantiate the class and call its methods. # Anti-Patterns - Do not provide simple function scripts when a
- Prompt
- Triggers
What does the Python 数据库/中间件类封装生成 skill do?
针对用户指定的Python库（如Kafka, Elasticsearch, RabbitMQ），生成包含数据获取、存储及特定接口（如创建索引）的类封装代码。
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill python-数据库-中间件类封装生成 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.