Paperform Python API Docs | dltHub

Paperform is an online form and survey platform exposing a REST API to programmatically list and manage forms, form fields, submissions (full and partial), webhooks, spaces, products, coupons and related resources. The REST API base URL is https://api.paperform.co/v1 and all requests require a Bearer token in the Authorization header.

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 Paperform data in under 10 minutes.

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What data can I load from Paperform?

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

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How do I authenticate with the Paperform API?

Provide your API token as a Bearer token in the Authorization header: "Authorization: Bearer {YOUR_API_TOKEN}". Requests require an account with API access (Standard or Business plan features vary).

1. Get your credentials

1. Sign into your Paperform account. 2) Navigate to Settings or Account > Integrations & Webhooks or the Developer/API section. 3) If required, enable the Developer/Standard API (or upgrade to a Business/Enterprise plan for Business API endpoints). 4) Create/generate an API token and copy it for use in Authorization header.

2. Add them to .dlt/secrets.toml

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[sources.paperform_source]
api_key = "your_paperform_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.

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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 Paperform 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 paperform_pipeline.py

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

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Pipeline paperform_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset paperform_data
The duckdb destination used duckdb:/paperform.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 paperform_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 forms and submissions from the Paperform 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 paperform_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.paperform.co/v1",
            "auth": {
                "type": "bearer",
                "token": api_key,
            },
        },
        "resources": [
            {"name": "forms", "endpoint": {"path": "forms"}},
            {"name": "submissions", "endpoint": {"path": "forms/{slug_or_id}/submissions"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="paperform_pipeline",
        destination="duckdb",
        dataset_name="paperform_data",
    )
    load_info = pipeline.run(paperform_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("paperform_pipeline").dataset()
sessions_df = data.submissions.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM paperform_data.submissions LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("paperform_pipeline").dataset()
data.submissions.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 Paperform 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 errors

If you receive 401 Unauthorized, verify your Authorization header is exactly: "Authorization: Bearer {YOUR_API_TOKEN}" and that the token has not been revoked. Confirm your plan includes API access (Standard or Business as required).

Rate limiting and 429 responses

Paperform may enforce rate limits. If you receive 429 Too Many Requests, implement exponential backoff and retry after the time indicated in Retry-After response header.

Missing resource / 404

A 404 indicates the form, submission, or resource id does not exist or your token does not have access. Confirm the correct slug_or_id and that the authenticating user has access to the resource.

Pagination

List endpoints may be paginated. Check the API responses for pagination fields (e.g. page, per_page, next or links) and follow them to iterate all records.

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