Sharetribe Python API Docs | dltHub

Sharetribe is a marketplace platform that provides HTTP APIs (Marketplace API, Integration API, Authentication API and Asset Delivery API) to programmatically manage marketplace data (listings, users, transactions, messages, assets). The REST API base URL is https://flex-api.sharetribe.com/v1/api and All requests require a Bearer access token provided 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 Sharetribe data in under 10 minutes.

---

What data can I load from Sharetribe?

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

---

How do I authenticate with the Sharetribe API?

Sharetribe uses an OAuth2-based Authentication API to obtain access tokens. Include the token in each request as: Authorization: bearer ACCESS_TOKEN. SDKs can be used to obtain and refresh tokens.

1. Get your credentials

1. In Sharetribe Console / Admin (or developer dashboard) create/register an API client / integration (client id/secret or integration token). 2) Use the Authentication API (OAuth2) to exchange credentials for an access token (client credentials, authorization code or password grant as supported). 3) Alternatively, use Sharetribe SDK (recommended) which handles authentication flows and tokens. 4) Store the returned access token in your dlt secrets (access_token = "...").

2. Add them to .dlt/secrets.toml

Copy
[sources.sharetribe_source]
access_token = "your_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 Sharetribe 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 sharetribe_pipeline.py

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

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

Inspect your pipeline and data:

Copy
dlt pipeline sharetribe_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 listings and transactions from the Sharetribe 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 sharetribe_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://flex-api.sharetribe.com/v1/api",
            "auth": {
                "type": "bearer",
                "access_token": access_token,
            },
        },
        "resources": [
            {"name": "listings", "endpoint": {"path": "v1/api/listings/query", "data_selector": "data"}},
            {"name": "transactions", "endpoint": {"path": "v1/api/transactions/query", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="sharetribe_pipeline",
        destination="duckdb",
        dataset_name="sharetribe_data",
    )
    load_info = pipeline.run(sharetribe_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("sharetribe_pipeline").dataset()
sessions_df = data.listings.df()
print(sessions_df.head())

SQL (DuckDB example):

Copy
SELECT * FROM sharetribe_data.listings LIMIT 10;

In a marimo or Jupyter notebook:

Copy
import dlt

data = dlt.pipeline("sharetribe_pipeline").dataset()
data.listings.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 Sharetribe 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 (401/403)

If Authorization header is missing or the token is invalid/expired the API returns 401/403. Ensure you use: Authorization: bearer ACCESS_TOKEN. Use the Authentication API or SDK to obtain/refresh tokens.

Rate limits (429)

The Marketplace and Integration APIs enforce rate and concurrency limits. Requests rejected due to rate limits return HTTP 429. Implement exponential backoff and respect per-environment limits (dev/test often 1 req/sec for GET endpoints as documented).

Pagination and data selectors

List endpoints return a JSON envelope with top-level "data" key containing an array of resources and a "meta" object with pagination (totalItems, totalPages, page, perPage). For single-resource endpoints the "data" key is an object. Always read the top-level "data" key as the record(s) selector.

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