7shifts Python API Docs | dltHub

7shifts is a workforce management platform for restaurants that provides scheduling, time & attendance, labor forecasting and sales/labor integrations via a REST API. The REST API base URL is https://api.7shifts.com/v2 and all requests require an OAuth2 bearer token and an x-company-guid 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 7shifts data in under 10 minutes.

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What data can I load from 7shifts?

Here are some of the endpoints you can load from 7shifts:

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How do I authenticate with the 7shifts API?

7shifts uses OAuth 2.0 client_credentials to issue Bearer access tokens (expires after 1 hour). Requests must include Authorization: Bearer {token} and x-company-guid: {COMPANY_GUID} headers.

1. Get your credentials

1. Contact 7shifts partner onboarding (partners@7shifts.com) to request an OAuth client. 2) Provide technical contact info, company name, logo and a callback URL. 3) 7shifts will provide a client_id and client_secret. 4) Direct customers to https://app.7shifts.com/generate_token?client_id={CLIENT_ID} to obtain a company grant GUID. 5) Exchange client_id and client_secret for an access token via POST https://app.7shifts.com/oauth2/token using grant_type=client_credentials and desired scopes.

2. Add them to .dlt/secrets.toml

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[sources.seven_shifts_source]
client_id = "your_client_id_here"
client_secret = "your_client_secret_here"
company_guid = "your_company_guid_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 7shifts 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 seven_shifts_pipeline.py

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

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Pipeline seven_shifts_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset seven_shifts_data
The duckdb destination used duckdb:/seven_shifts.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 seven_shifts_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 users and receipts from the 7shifts 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 seven_shifts_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.7shifts.com/v2",
            "auth": {
                "type": "bearer",
                "token": access_token,
            },
        },
        "resources": [
            {"name": "users", "endpoint": {"path": "users"}},
            {"name": "receipts", "endpoint": {"path": "receipts"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="seven_shifts_pipeline",
        destination="duckdb",
        dataset_name="seven_shifts_data",
    )
    load_info = pipeline.run(seven_shifts_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("seven_shifts_pipeline").dataset()
sessions_df = data.users.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM seven_shifts_data.users LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("seven_shifts_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.

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What destinations can I load 7shifts 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 receive 401 Unauthorized: ensure you have a valid Bearer token (tokens expire after 1 hour) and include the x-company-guid header. Create a new token via POST https://app.7shifts.com/oauth2/token with grant_type=client_credentials, client_id and client_secret.

Rate limits

7shifts enforces a limit of 10 requests per second per Access Token (or per partner for partner-level limits). Throttle requests and implement exponential backoff on 429 responses.

Pagination

Many list endpoints are paginated; check response for pagination fields (e.g. links, meta) and follow next-page parameters. Use limit/offset or page parameters as documented in the API reference.

Revoked grants

If a company revokes your integration the token will no longer authorize requests for that company; subscribe to authorization.revoked webhook to be notified of revocations.

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