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Load Awin data to DuckDB

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

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

Awin is a performance marketing network that provides a REST API for accessing publisher and advertiser data. Everything needed to build a working Awin → 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 Awin 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 Awin 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 Awin 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.


Awin API at a glance

Base URLhttps://api.awin.com
Example endpointGET publishers/{publisherId}/transactions
Records found attransactions
Authenticationmost requests require an OAuth 2.0 Bearer token in the Authorization header — sent in the Authorization header, prefixed Bearer
PaginationPage-number
Incremental fieldtransaction_date
Record idid
API referencehttps://help.awin.com/apidocs/api-authentication

These values come from the Awin API reference — the authoritative source if anything here looks out of date.


How do I authenticate with the Awin API?

The Awin API primarily uses OAuth 2.0 Bearer token authentication, which requires an 'Authorization' header with the value format 'Bearer '. Some specific endpoints, such as the Create Transaction API, use an 'x-api-key' header instead.

1. Get your credentials

  1. Log in to your Awin account at https://ui.awin.com. 2. Click on your user profile icon (usually in the top right corner) and select 'API Credentials' from the dropdown menu. 3. You will be prompted to re-enter your Awin account password. 4. Click 'Show my API token' to display your personal API access token. 5. Copy the token to your clipboard for use in your API requests.

2. Add them to .dlt/secrets.toml

[sources.awin_source] awin_api_token = "your_token_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 Awin data can I load into DuckDB?

These are the Awin endpoints dlt can load into DuckDB:

ResourceEndpointMethodData selectorDescription
accounts/accountsGETReturns a list of accounts for a user
transactions/publishers/{publisherId}/transactionsGETtransactionsList of transaction records for a publisher
programmes/publishers/{publisherId}/programmesGETprogrammesProgrammes associated with a publisher
advertiser_performance/reports/advertiserGETAdvertiser performance report
transaction_queries/publisher/{publisherId}/transactionqueriesGETList of transaction enquiries

How do I load only new Awin records?

Awin exposes transaction_date on publishers/{publisherId}/transactions, 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.

{"name": "transactions", "endpoint": { "path": "publishers/{publisherId}/transactions", "data_selector": "transactions", "incremental": {"cursor_path": "transaction_date", "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 Awin pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading 'publisher-performance and get-list-of-transactions' from the Awin API into DuckDB:

import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def awin_source(access_token=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://api.awin.com", "auth": {"type": "bearer", "token": access_token}, }, "resources": [ {"name": "transactions", "endpoint": {"path": "publishers/{publisherId}/transactions", "data_selector": "transactions"}}, {"name": "reports", "endpoint": {"path": "reports/transactions", "data_selector": "results"}} ], } yield from rest_api_resources(config) def load_awin_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="awin_pipeline", destination="duckdb", dataset_name="awin_data", ) load_info = pipeline.run(awin_source()) print(load_info) if __name__ == "__main__": load_awin_to_duckdb()

Run it with python awin_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 Awin 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("awin_pipeline").dataset() df = data.transactions.df() print(df.head())

SQL:

SELECT * FROM awin_data.transactions LIMIT 10;

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


How do I deploy the Awin 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 Awin 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 Awin 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

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