TimelyApp Python API Docs | dltHub

TimelyApp is a time‑tracking platform that provides a REST API for accounts, users, projects, events, clients, labels and reporting data. The REST API base URL is https://api.timelyapp.com/1.1 and All requests require an OAuth2 Bearer token..

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 TimelyApp data in under 10 minutes.

---

What data can I load from TimelyApp?

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

---

How do I authenticate with the TimelyApp API?

Timely uses OAuth2 authorization code grant. Obtain an access token via POST https://api.timelyapp.com/1.1/oauth/token and include it in the Authorization header as "Bearer <access_token>".

1. Get your credentials

1. Log in to the Timely web app as an admin. 2) Navigate to Settings → Integrations → OAuth Applications (or visit https://app.timelyapp.com/:account_id/oauth_applications). 3) Create a new OAuth application and note the client ID and client secret. 4) Use the client ID and secret in the OAuth token exchange flow to obtain an access token.

2. Add them to .dlt/secrets.toml

Copy
[sources.timely_app_source]
access_token = "your_timely_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.

---

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 TimelyApp 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 timely_app_pipeline.py

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

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

Inspect your pipeline and data:

Copy
dlt pipeline timely_app_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 events and projects from the TimelyApp 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 timely_app_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.timelyapp.com/1.1",
            "auth": {
                "type": "bearer",
                "token": access_token,
            },
        },
        "resources": [
            {"name": "events", "endpoint": {"path": "1.1/:account_id/events"}},
            {"name": "projects", "endpoint": {"path": "1.1/:account_id/projects"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="timely_app_pipeline",
        destination="duckdb",
        dataset_name="timely_app_data",
    )
    load_info = pipeline.run(timely_app_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("timely_app_pipeline").dataset()
sessions_df = data.events.df()
print(sessions_df.head())

SQL (DuckDB example):

Copy
SELECT * FROM timely_app_data.events LIMIT 10;

In a marimo or Jupyter notebook:

Copy
import dlt

data = dlt.pipeline("timely_app_pipeline").dataset()
data.events.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 TimelyApp 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 you receive a 401 Unauthorized response, verify that the Authorization header is correctly set to Bearer <access_token> and that the token has not expired. Refresh the token using the OAuth refresh flow or repeat the authorization code exchange.

Rate limits and server errors

The API follows standard HTTP status codes. For 5xx responses, retry with exponential backoff. If a 429 Too Many Requests is returned, wait for the period indicated in the Retry-After header before retrying.

Pagination

List endpoints support limit and offset query parameters. Use these to page through large result sets.

Validation errors

A 422 Unprocessable Entity response includes an errors object detailing validation problems. Other 4xx errors return an errors object with a message field.

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