Load OpenReview data to DuckDB

OpenReview is a platform for open peer review, which provides a REST API to access scientific papers, reviews, and conference data. Everything needed to build a working OpenReview → DuckDB pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.

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Build your OpenReview to DuckDB pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

PromptCopy prompt
Run uvx dlthub-init@latest to build a pipeline from OpenReview to DuckDB and run it on dltHub

That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the OpenReview API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →

Prefer to write it yourself? Every fact the agent uses is below.

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OpenReview API at a glance

These values come from the OpenReview API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the OpenReview API?

Authentication is performed by including a Bearer token in the Authorization header. If provided with a 'Bearer ' prefix, the client automatically strips it before re-applying the required 'Authorization: Bearer ' format to requests.

1. Get your credentials

OpenReview does not utilize a traditional API key dashboard for authentication. Instead, it relies on your OpenReview profile credentials (username/email and password) or temporary bearer tokens. To interact with the API, simply use your existing OpenReview credentials. If a token is required, it is generated programmatically by the client or via the OAuth 2.0 / OIDC flow. Ensure you have an active account by signing up at https://openreview.net if you do not already have one.

2. Add them to .dlt/secrets.toml

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[sources.openreview_source]
token = "REPLACE_ME"

dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.

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What OpenReview data can I load into DuckDB?

These are the OpenReview endpoints dlt can load into DuckDB:

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How do I load only new OpenReview records?

OpenReview exposes mintcdate on notes, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.

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{"name": "notes", "endpoint": {
    "path": "notes",
    "data_selector": "notes",
    "incremental": {"cursor_path": "mintcdate", "initial_value": "2024-01-01T00:00:00Z"},
}}

On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.

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What does the generated OpenReview pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading notes and edges from the OpenReview API into DuckDB:

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

@dlt.source
def openreview_source(token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api2.openreview.net",
            "auth": {"type": "bearer", "token": token},
        },
        "resources": [
            {"name": "notes", "endpoint": {"path": "notes", "data_selector": "notes"}},
            {"name": "edges", "endpoint": {"path": "edges", "data_selector": "edges"}}
        ],
    }
    yield from rest_api_resources(config)


def load_openreview_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="openreview_pipeline",
        destination="duckdb",
        dataset_name="openreview_data",
    )
    load_info = pipeline.run(openreview_source())
    print(load_info)


if __name__ == "__main__":
    load_openreview_to_duckdb()

Run it with python openreview_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.

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How do I query OpenReview data in DuckDB?

dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("openreview_pipeline").dataset()
df = data.notes.df()
print(df.head())

SQL:

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SELECT * FROM openreview_data.notes LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.

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How do I deploy the OpenReview to DuckDB pipeline in production?

The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.

• Deploy & schedule — run the pipeline as a managed job with automatic retries.
• Monitor — observable job queues, alerting, and load metrics for every run.
• Transform — promote raw OpenReview loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

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What other destinations can I load OpenReview data to?

dlt loads into any of these — only the destination argument changes:

Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.

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Next steps

• Ready for production? Book a demo of the dltHub platform →
• dlt LLM-native workflow docs
• REST API source reference
• Join the dlt community on Slack