Wp-all-import Python API Docs | dltHub

WP All Import is a WordPress plugin that enables importing content into WordPress via CSV/XML and provides developer hooks and add‑on APIs. The REST API base URL is `` and WP All Import does not define a standard API authentication mechanism; access is managed through WordPress login or custom site‑specific protections..

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 Wp-all-import data in under 10 minutes.

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What data can I load from Wp-all-import?

Here are some of the endpoints you can load from Wp-all-import:

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How do I authenticate with the Wp-all-import API?

Authentication is handled by WordPress (cookies, logged‑in user session) for any custom callbacks; the plugin itself does not require an API key or bearer token.

1. Get your credentials

Not applicable – WP All Import does not issue API credentials; access is managed through the WordPress admin dashboard.

2. Add them to .dlt/secrets.toml

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[sources.wp_all_import_source]

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 Wp-all-import 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 wp_all_import_pipeline.py

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

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Pipeline wp_all_import_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset wp_all_import_data
The duckdb destination used duckdb:/wp_all_import.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 wp_all_import_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 from the Wp-all-import 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 wp_all_import_source(=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "",
            "auth": {
                "type": "",
                "": ,
            },
        },
        "resources": [
            
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="wp_all_import_pipeline",
        destination="duckdb",
        dataset_name="wp_all_import_data",
    )
    load_info = pipeline.run(wp_all_import_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("wp_all_import_pipeline").dataset()
sessions_df = data..df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM wp_all_import_data. LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("wp_all_import_pipeline").dataset()
data..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 Wp-all-import 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

Import failures

Common causes include malformed CSV/XML files, mismatched column headers, and server timeout errors. The documentation advises verifying file format and reducing file size.

Plugin or theme conflicts

Errors may arise when other plugins interfere with WP All Import’s hooks. The guide recommends disabling conflicting plugins and testing on a default theme.

Version and dependency issues

Using an outdated version of WP All Import or incompatible WordPress core can cause fatal errors. Updating both the plugin and WordPress to the latest stable releases is recommended.

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