This repo contains everything you need to get started with building a new plugin. To get started all you need to do is change a few names, define some tables, and write an API Client to populate the tables.

• plugin/tables/items.py
  • Items - A boilerplate table definition
  • ItemResolver - A boilerplate table resolver
• plugin/example/client.py
• ExampleClient - A boilerplate API Client
• plugin/client/client.py
  • Spec - Defines the CloudQuery Config
  • Client (uses: ExampleClient) - Wraps your API Client
• plugin/plugin.py
  • ExamplePlugin - The plugin registration / how CloudQuery knows what tables your plugin exposes.

The first thing you need to do is identify the tables you want to create with your plugin. Conventionally, CloudQuery plugins have a direct relationship between tables and API responses.

For example: If you had an API endpoint https://api.example.com/items/{num} and for each value of num it provided an object

{
   "num": {{num}},
   "date": "2023-10-12", 
   "title": "A simple example"
}

Then you would design the table class as

class Items(Table):
    def __init__(self) -> None:
        super().__init__(
            name="item",
            title="Item",
            columns=[
                Column("num", pa.uint64(), primary_key=True),
                Column("date", pa.date64()),
                Column("title", pa.string()),
            ],
        )
    ...

Creating one table for each endpoint that you want to capture.

Next you'll need to define how the tables are retrieved, it's recommended to implement this as a generator, as per the example in plugin/example/client.py.

Having written your API Client you will have, identified the authentication and/or operational variables needed. Adding these to the CloudQuery config spec can be done by editing the Spec dataclass using standard python, and adding validation where needed.

Finally, you need to edit the plugin.py file to set the plugin name and version, and add the Tables to the get_tables function.

• Architecture
• Concepts