WordPress VIP Python API Docs | dltHub

The WordPress REST API allows applications to interact with WordPress sites via JSON, enabling efficient content management and integration. VIP enhances its performance and security. VIP documentation provides detailed guidance on optimizing and using the API effectively. The REST API base URL is https://<your-custom-domain.com>/wp-json/ and The WordPress VIP REST API supports multiple authentication methods, including OAuth 2.0, Basic Auth, JWT, Cookies, and Application Passwords. OAuth 2.0 is generally recommended for secure programmatic access..

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 WordPress VIP data in under 10 minutes.

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What data can I load from WordPress VIP?

Here are some of the endpoints you can load from WordPress VIP:

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How do I authenticate with the WordPress VIP API?

Authentication for the WordPress VIP REST API can be handled via various methods, with OAuth 2.0 being a recommended approach. For OAuth 2.0, an access token is typically included in the Authorization header as a Bearer token.

1. Get your credentials

The method for obtaining API credentials varies by authentication type. For OAuth 2.0, you would typically register an application to receive a client ID and client secret, then use these to obtain an access token. For Application Passwords, these can be generated directly from your WordPress user profile. Consult the specific WordPress VIP documentation for detailed steps on your chosen authentication method.

2. Add them to .dlt/secrets.toml

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[sources.wordpress_vip_source]
access_token = "your_access_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 WordPress VIP 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 wordpress_vip_pipeline.py

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

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Pipeline wordpress_vip_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset wordpress_vip_data
The duckdb destination used duckdb:/wordpress_vip.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 wordpress_vip_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 pages from the WordPress VIP 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 wordpress_vip_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://<your-custom-domain.com>/wp-json/",
            "auth": {
                "type": "bearer",
                "token": access_token,
            },
        },
        "resources": [
            {"name": "posts", "endpoint": {"path": "wp/v2/posts"}},
            {"name": "pages", "endpoint": {"path": "wp/v2/pages"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="wordpress_vip_pipeline",
        destination="duckdb",
        dataset_name="wordpress_vip_data",
    )
    load_info = pipeline.run(wordpress_vip_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("wordpress_vip_pipeline").dataset()
sessions_df = data.posts.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM wordpress_vip_data.posts LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("wordpress_vip_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 WordPress VIP 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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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