No logo available for VWO to DuckDB connector icon

Load VWO data to DuckDB

Build a VWO to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the VWO API base URL, auth, endpoints, and incremental loading.

SourceVWODestinationDuckDBIn-process analytical database. The default local destination for dlt pipelines.

VWO (Wingify) provides a REST API for managing accounts, campaigns, and experiment data programmatically. Everything needed to build a working VWO → 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.


Build your VWO to DuckDB pipeline

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

Prompt
Run uvx dlthub-init@latest to build a pipeline from VWO 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 VWO 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.


VWO API at a glance

Base URLhttps://app.wingify.com/api/v2
Example endpointGET accounts/{account_id}/campaigns
Records found atcampaigns
Authenticationall requests require an API token passed in a header named 'token' — sent in the token header
PaginationOffset-based via offset, page size via limit. The API uses offset-based pagination. Specifically, the 'offset' parameter is used for paging, and the documentation for list endpoints indicates these endpoints often enforce a hard cap on results per page (e.g., 25 for campaigns), requiring sequential fetching via offset.
API referencehttps://developers.vwo.com/reference

These values come from the VWO API reference — the authoritative source if anything here looks out of date.


How do I authenticate with the VWO API?

Authentication is performed by passing a token in the request header named 'token'.

1. Get your credentials

To obtain a VWO API token, log into your VWO account. Navigate to the bottom of the dashboard and click on 'Developers' or 'Developer resources'. On the Developer Dashboard that appears, go to the 'Tokens' tab. Click 'Add another API token', provide a name, select the required permissions (e.g., Browse), and click 'Generate'. Copy the token immediately, as it will only be visible once.

2. Add them to .dlt/secrets.toml

[sources.vwo_source] api_token = "your_api_token_here" account_id = "your_account_id_here"

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.


What VWO data can I load into DuckDB?

These are the VWO endpoints dlt can load into DuckDB:

ResourceEndpointMethodData selectorDescription
campaigns/accounts/{account_id}/campaignsGETcampaignsList campaigns in a workspace.
variations/accounts/{account_id}/campaigns/{campaign_id}/variationsGET_dataGet all variations of a campaign.
workspaces/accounts/{account_id}/workspacesGETworkspacesRetrieve all workspaces for an account.
users/accounts/{account_id}/usersGETusersList users associated with the account.
feature_flag_rules/accounts/{account_id}/environments/{env_id}/features/{feature_id}/rulesGETrulesList rules for a feature flag.

How do I load only new VWO records?

The VWO API reference does not document a timestamp or sequence field for these endpoints, so there is nothing to advertise here as verified. Pick a field from the endpoints table above that increases with every write, then set it as the cursor_path.

{"name": "campaigns", "endpoint": { "path": "accounts/{account_id}/campaigns", # Replace with a field that increases on every write. "incremental": {"cursor_path": "REPLACE_ME", "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.


What does the generated VWO pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /accounts/{account_id}/campaigns/{campaign_id}/variations and /accounts/{account_id}/campaigns/{campaign_id}/goals from the VWO API into DuckDB:

import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def vwo_source(api_key=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://app.wingify.com/api/v2", "auth": {"type": "api_key", "api_key": api_key, "name": "token", "location": "header"}, }, "resources": [ {"name": "campaigns", "endpoint": {"path": "accounts/{account_id}/campaigns", "data_selector": "campaigns"}}, {"name": "workspaces", "endpoint": {"path": "accounts/{account_id}/workspaces", "data_selector": "workspaces"}} ], } yield from rest_api_resources(config) def load_vwo_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="vwo_pipeline", destination="duckdb", dataset_name="vwo_data", ) load_info = pipeline.run(vwo_source()) print(load_info) if __name__ == "__main__": load_vwo_to_duckdb()

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


How do I query VWO 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):

import dlt data = dlt.pipeline("vwo_pipeline").dataset() df = data.campaigns.df() print(df.head())

SQL:

SELECT * FROM vwo_data.campaigns LIMIT 10;

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


How do I deploy the VWO 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 VWO loads into governed, documented models.
  • Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →


What other destinations can I load VWO data to?

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

DestinationExample value
PostgreSQL"postgres"
BigQuery"bigquery"
Snowflake"snowflake"
Redshift"redshift"
Databricks"databricks"
Filesystem (S3, GCS, Azure)"filesystem"

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.


Next steps

Was this page helpful?

Community Hub

Need more dlt context for VWO to DuckDB?

Request dlt skills, commands, AGENT.md files, and AI-native context.