Clockodo Python API Docs | dltHub

Clockodo is a time‑tracking and workforce‑management SaaS with a REST API for accessing time entries, customers, projects, services, and more. The REST API base URL is https://my.clockodo.com/api and All requests require an API key passed in the X-ClockodoApiUser and X-ClockodoApiKey headers or basic 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 Clockodo data in under 10 minutes.

---

What data can I load from Clockodo?

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

---

How do I authenticate with the Clockodo API?

Authentication is performed by sending the X-ClockodoApiUser header with the account email and the X-ClockodoApiKey header with the API key. Basic HTTP authentication (email as user, API key as password) is also supported.

1. Get your credentials

1. Log in to your Clockodo account at https://my.clockodo.com.
2. Open the user menu and select "Settings".
3. In the Settings navigation, choose "API".
4. Click "Generate new API key" (or copy the existing key).
5. Copy the displayed API key and note the email address associated with the account; these two values are required for authentication.

2. Add them to .dlt/secrets.toml

Copy
[sources.clockodo_source]
api_key = "your_api_key_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 Clockodo 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 clockodo_pipeline.py

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

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

Inspect your pipeline and data:

Copy
dlt pipeline clockodo_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 entries and services from the Clockodo 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 clockodo_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://my.clockodo.com/api",
            "auth": {
                "type": "api_key",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "entries", "endpoint": {"path": "api/v2/entries", "data_selector": "entries"}},
            {"name": "services", "endpoint": {"path": "api/v2/services", "data_selector": "services"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="clockodo_pipeline",
        destination="duckdb",
        dataset_name="clockodo_data",
    )
    load_info = pipeline.run(clockodo_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("clockodo_pipeline").dataset()
sessions_df = data.entries.df()
print(sessions_df.head())

SQL (DuckDB example):

Copy
SELECT * FROM clockodo_data.entries LIMIT 10;

In a marimo or Jupyter notebook:

Copy
import dlt

data = dlt.pipeline("clockodo_pipeline").dataset()
data.entries.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 Clockodo 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 errors

• 401 Unauthorized – Invalid or missing API key. Ensure the X-ClockodoApiUser and X-ClockodoApiKey headers contain the correct email and key.
• 403 Forbidden – The API key does not have permission for the requested resource.

Rate limiting

• 429 Too Many Requests – The API enforces a request limit. Implement exponential back‑off and respect the Retry-After header if provided.

Pagination

• Clockodo only supports paging for the resources entries, entriesTexts, customers, and projects. The response includes a paging object with page, limit, total, and navigation URLs. Loop through pages until no further next link is present.

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