Dropbox sign Python API Docs | dltHub

Dropbox Sign is an eSignature API platform (formerly HelloSign) that lets applications create, send, embed, and manage signature requests and templates. The REST API base URL is https://api.hellosign.com/v3 and Requests use HTTP Basic with an API key or Bearer OAuth tokens 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 Dropbox sign data in under 10 minutes.

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What data can I load from Dropbox sign?

Here are some of the endpoints you can load from Dropbox sign:

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How do I authenticate with the Dropbox sign API?

You can authenticate with an API key by sending HTTP Basic auth with the API key as the username and an empty password. Alternatively, use OAuth access tokens in the Authorization header as Bearer tokens.

1. Get your credentials

1. Sign in at https://app.hellosign.com (sign.dropbox.com).
2. Open API Settings / API tab.
3. Reveal or Create an API Key.
4. (Optional) Create an API App to obtain a client_id for embedded flows / OAuth apps.

2. Add them to .dlt/secrets.toml

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[sources.dropbox_sign_source]
api_key = "YOUR_API_KEY"

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 Dropbox sign 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 dropbox_sign_pipeline.py

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

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Pipeline dropbox_sign_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset dropbox_sign_data
The duckdb destination used duckdb:/dropbox_sign.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 dropbox_sign_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 signature_requests and templates from the Dropbox sign 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 dropbox_sign_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.hellosign.com/v3",
            "auth": {
                "type": "http_basic",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "signature_requests", "endpoint": {"path": "signature_request/list", "data_selector": "signature_requests"}},
            {"name": "templates", "endpoint": {"path": "template/list", "data_selector": "templates"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="dropbox_sign_pipeline",
        destination="duckdb",
        dataset_name="dropbox_sign_data",
    )
    load_info = pipeline.run(dropbox_sign_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("dropbox_sign_pipeline").dataset()
sessions_df = data.signature_requests.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM dropbox_sign_data.signature_requests LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("dropbox_sign_pipeline").dataset()
data.signature_requests.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 Dropbox sign 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 see 401 Unauthorized, verify you are using the API key as the HTTP Basic username with an empty password, or a valid Bearer token in the Authorization header. For API keys, ensure the key is active and not rotated/deleted. For OAuth tokens, refresh expired access tokens.

Rate limits

Dropbox Sign enforces rate limits; if you receive 429 Too Many Requests, implement exponential backoff and retry. Monitor Retry-After header when provided.

Pagination and list keys

List endpoints return results wrapped in an object (not a bare array). Use the documented list response key (e.g. "signature_requests", "templates", "bulk_send_jobs") as the data selector. Confirm by inspecting the response JSON from the endpoint in the API reference.

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