Circleschool Python API Docs | dltHub

Circle is a community platform and developer platform exposing Admin, Headless (Member & Auth) and Data APIs to manage communities and export event data. The REST API base URL is https://api.circle.so/ and all requests require a Bearer token (admin token) or member JWT depending on API (admin vs headless member)..

dlt is an open-source Python library that handles authentication, pagination, and schema evolution automatically. dlthub provides AI context files that enable code assistants to generate production-ready pipelines. Install with uv pip install "dlt[workspace]" and start loading Circleschool data in under 10 minutes.

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What data can I load from Circleschool?

Here are some of the endpoints you can load from Circleschool:

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How do I authenticate with the Circleschool API?

Circle Admin and Headless Admin APIs use Bearer token authentication. Admin API tokens are created in Community > Developers -> Tokens; include header: Authorization: Bearer <API_TOKEN>. Headless Member API uses member JWTs generated via the Auth API for member‑scoped requests.

1. Get your credentials

1. Sign in to your Circle community as an admin. 2) Open Community Settings -> Developers -> Tokens (or Developers -> Tokens). 3) Create a new admin token (name it, set scopes). 4) Copy the token and store it securely; use it in the Authorization header as Bearer .

2. Add them to .dlt/secrets.toml

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[sources.circleschool_source]
api_token = "your_circle_admin_token_here"

dlt reads this automatically at runtime — never hardcode tokens in your pipeline script. For production environments, see setting up credentials with dlt for environment variable and vault-based options.

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How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

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uv venv && source .venv/bin/activate
uv pip install "dlt[workspace]"

1. Install the dlt AI Workbench:

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dlt ai init --agent <your-agent> # <agent>: claude | cursor | codex

This installs project rules, a secrets management skill, appropriate ignore files, and configures the dlt MCP server for your agent. Learn more →

2. Install the rest-api-pipeline toolkit:

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dlt ai toolkit rest-api-pipeline install

This loads the skills and context about dlt the agent uses to build the pipeline iteratively, efficiently, and safely. The agent uses MCP tools to inspect credentials — it never needs to read your secrets.toml directly. Learn more →

3. Start LLM-assisted coding:

Use /find-source to load data from the Circleschool API into DuckDB.

The rest-api-pipeline toolkit takes over from here — it reads relevant API documentation, presents you with options for which endpoints to load, and follows a structured workflow to scaffold, debug, and validate the pipeline step by step.

4. Run the pipeline:

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python circleschool_pipeline.py

If everything is configured correctly, you'll see output like this:

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Pipeline circleschool_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset circleschool_data
The duckdb destination used duckdb:/circleschool.duckdb location to store data
Load package 1749667187.541553 is LOADED and contains no failed jobs

Inspect your pipeline and data:

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dlt pipeline circleschool_pipeline show

This opens the Pipeline Dashboard where you can verify pipeline state, load metrics, schema (tables, columns, types), and query the loaded data directly.

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Python pipeline example

This example loads posts and members from the Circleschool API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

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import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def circleschool_source(api_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.circle.so/",
            "auth": {
                "type": "bearer",
                "token": api_token,
            },
        },
        "resources": [
            {"name": "posts", "endpoint": {"path": "app.circle.so/api/headless/admin/v1/posts", "data_selector": "records"}},
            {"name": "members", "endpoint": {"path": "app.circle.so/api/headless/admin/v1/members", "data_selector": "records"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="circleschool_pipeline",
        destination="duckdb",
        dataset_name="circleschool_data",
    )
    load_info = pipeline.run(circleschool_source())
    print(load_info)

To add more endpoints, append entries from the resource table to the "resources" list using the same name, path, and data_selector pattern.

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How do I query the loaded data?

Once the pipeline runs, dlt creates one table per resource. You can query with Python or SQL.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("circleschool_pipeline").dataset()
sessions_df = data.posts.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM circleschool_data.posts LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("circleschool_pipeline").dataset()
data.posts.df().head()

See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.

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What destinations can I load Circleschool data to?

dlt supports loading into any of these destinations — only the destination parameter changes:

Change the destination in dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. See the full destinations list.

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Troubleshooting

Authentication failures

If you receive 401/403, verify you are using an admin Bearer token in the Authorization header. Admin tokens are created in Community -> Developers -> Tokens. Headless member endpoints require member JWTs from the Auth API.

Pagination and selectors

Admin endpoints are paginated. Requests accept page and per_page. Responses contain page, per_page, has_next_page, count, page_count and records (the array of items). Use records as the data selector for dlt.

Data API access and rate limits

The Data API is available on the Plus plan and exposes an event stream for export; consult Circle Plus/Data API docs and your account for provisioning and rate limits. Common errors include insufficient plan/permissions and 403 for unauthorized access.

Ensure that the API key is valid to avoid 401 Unauthorized errors. Also, verify endpoint paths and parameters to avoid 404 Not Found errors.

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Next steps

Continue your data engineering journey with the other toolkits of the dltHub AI Workbench:

• data-exploration — Build custom notebooks, charts, and dashboards for deeper analysis with marimo notebooks.
• dlthub-runtime — Deploy, schedule, and monitor your pipeline in production.

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dlt ai toolkit data-exploration install
dlt ai toolkit dlthub-runtime install

• How to deploy a pipeline
• How to explore your data in marimo Notebooks
• How to query your data in Python with dataset
• Join the dlt community on Slack