WorkRamp Python API Docs | dltHub

WorkRamp is an enterprise learning platform (LMS) that exposes a REST API for programmatic access to academy data (users, trainings, registrations, certifications, paths, etc.). The REST API base URL is https://api.workramp.com and All requests require an API token (admin API key) 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 WorkRamp data in under 10 minutes.

---

What data can I load from WorkRamp?

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

---

How do I authenticate with the WorkRamp API?

WorkRamp uses API tokens issued to Admin users. Tokens are presented as API credentials per the docs. The API is private and requires contacting support to enable access.

1. Get your credentials

1. Log into WorkRamp as an Admin. 2. Go to Settings → API Key Management (or follow the help article "API key management"). 3. Generate a new API token (only Admin users may create tokens). 4. Record the token (tokens are only invalidated on request). 5. If needed, request External API access from support@workramp.com or sales@workramp.com for enterprise provisioning.

2. Add them to .dlt/secrets.toml

Copy
[sources.workramp_source]
api_key = "your_api_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.

---

How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

Copy
uv venv && source .venv/bin/activate
uv pip install "dlt[workspace]"

1. Install the dlt AI Workbench:

Copy
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:

Copy
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 WorkRamp 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:

Copy
python workramp_pipeline.py

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

Copy
Pipeline workramp_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset workramp_data
The duckdb destination used duckdb:/workramp.duckdb location to store data
Load package 1749667187.541553 is LOADED and contains no failed jobs

Inspect your pipeline and data:

Copy
dlt pipeline workramp_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.

---

Python pipeline example

This example loads users and trainings from the WorkRamp API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

Copy
import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def workramp_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.workramp.com",
            "auth": {
                "type": "api_key",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "users", "endpoint": {"path": "v1/users", "data_selector": "users"}},
            {"name": "trainings", "endpoint": {"path": "v1/trainings", "data_selector": "trainings"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="workramp_pipeline",
        destination="duckdb",
        dataset_name="workramp_data",
    )
    load_info = pipeline.run(workramp_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.

---

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):

Copy
import dlt

data = dlt.pipeline("workramp_pipeline").dataset()
sessions_df = data.users.df()
print(sessions_df.head())

SQL (DuckDB example):

Copy
SELECT * FROM workramp_data.users LIMIT 10;

In a marimo or Jupyter notebook:

Copy
import dlt

data = dlt.pipeline("workramp_pipeline").dataset()
data.users.df().head()

See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.

---

What destinations can I load WorkRamp 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.

---

Troubleshooting

Authentication failures

If your API token is invalid or the associated user is not an active Admin, API calls will fail. API tokens can only be generated by Admin users; if the Admin user is deactivated or removed, calls using that token will stop working. Contact support@workramp.com to reissue or invalidate tokens.

Rate limits

Burst rates up to 13,000 API calls/hour; sustained hourly rate up to 3,000 API calls/hour for External API endpoints. Respect these limits to avoid throttling.

EU region

Use app.eu.workramp.com for EU-hosted academies (replace app.workramp.com in all URLs).

Common errors: 401 Unauthorized (invalid token or non-admin), 403 Forbidden (insufficient access), 429 Too Many Requests (rate limit exceeded), 500 series (server errors) — consult WorkRamp status page.

Ensure that the API key is valid to avoid 401 Unauthorized errors. Also, verify endpoint paths and parameters to avoid 404 Not Found errors.

---

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.

Copy
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