Joomla Python API Docs | dltHub

Joomla REST API is a web service for Joomla 4.x that allows external applications to interact with Joomla's content and user management. The REST API base URL is https://<your-joomla-host>/api/index.php/v1 and All requests require a Bearer token for authentication..

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 Joomla data in under 10 minutes.

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What data can I load from Joomla?

Here are some of the endpoints you can load from Joomla:

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How do I authenticate with the Joomla API?

Authentication uses a Bearer token, which is HMAC-based and stored per-user. The token must be included in the 'Authorization' header as 'Bearer '.

1. Get your credentials

To obtain API credentials, enable the "User - Joomla API Token" and "API Authentication - Web Services Joomla Token" plugins. Then, generate the token either in the user profile or through the admin tools.

2. Add them to .dlt/secrets.toml

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[sources.joomla_source]
api_token = "your_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 Joomla 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 joomla_pipeline.py

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

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Pipeline joomla_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset joomla_data
The duckdb destination used duckdb:/joomla.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 joomla_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 articles and users from the Joomla 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 joomla_source(api_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://<your-joomla-host>/api/index.php/v1",
            "auth": {
                "type": "bearer",
                "token": api_token,
            },
        },
        "resources": [
            {"name": "articles", "endpoint": {"path": "content/articles", "data_selector": "data"}},
            {"name": "users", "endpoint": {"path": "users", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="joomla_pipeline",
        destination="duckdb",
        dataset_name="joomla_data",
    )
    load_info = pipeline.run(joomla_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("joomla_pipeline").dataset()
sessions_df = data.articles.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM joomla_data.articles LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("joomla_pipeline").dataset()
data.articles.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 Joomla 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

Authentication Failures

If you encounter a 401 Unauthorized error, it indicates an invalid or missing authentication token. Ensure your Bearer token is correctly included in the Authorization header.

Permission Errors

A 403 Forbidden error suggests that the authenticated user lacks the necessary ACL (Access Control List) permissions to access the requested resource. Verify the user's group permissions within Joomla.

Invalid Requests

404 Not Found errors typically occur when an invalid resource ID is provided. A 400 Bad Request error usually points to validation issues with the request payload.

Rate Limiting

A 429 Too Many Requests error indicates that you have exceeded the API's rate limits. This is often managed via plugins or configuration within Joomla.

Pagination

Joomla's API uses JSON API pagination links and meta fields. Look for top-level links and meta objects in the response to handle pagination. Ensure Accept: application/json is set for proper content negotiation.

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