Svix Python API Docs | dltHub

Svix is a webhook sending infrastructure as a service that reliably delivers and manages webhooks for applications and customers. The REST API base URL is https://api.svix.com/api/v1 and All requests require a Bearer token 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 Svix data in under 10 minutes.

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What data can I load from Svix?

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

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How do I authenticate with the Svix API?

Requests must include an Authorization header with a Bearer token (Authorization: Bearer <AUTH_TOKEN>). SDK examples also accept the token when constructing client instances.

1. Get your credentials

1. Sign in to your Svix dashboard at https://dashboard.svix.com. 2) Open 'API Access' (or 'API keys') in the dashboard. 3) Create a new API key / AuthToken and copy the generated token. 4) Use this token as the Bearer token in the Authorization header for API calls.

2. Add them to .dlt/secrets.toml

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[sources.svix_integration_source]
token = "your_svix_auth_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 Svix 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 svix_integration_pipeline.py

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

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Pipeline svix_integration_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset svix_integration_data
The duckdb destination used duckdb:/svix_integration.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 svix_integration_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 applications and endpoints from the Svix 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 svix_integration_source(auth_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.svix.com/api/v1",
            "auth": {
                "type": "bearer",
                "token": auth_token,
            },
        },
        "resources": [
            {"name": "applications", "endpoint": {"path": "api/v1/app"}},
            {"name": "endpoints", "endpoint": {"path": "api/v1/app/{app_id}/endpoint"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="svix_integration_pipeline",
        destination="duckdb",
        dataset_name="svix_integration_data",
    )
    load_info = pipeline.run(svix_integration_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("svix_integration_pipeline").dataset()
sessions_df = data.applications.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM svix_integration_data.applications LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("svix_integration_pipeline").dataset()
data.applications.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 Svix 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, verify that the Authorization header is present and uses a valid Bearer token (Authorization: Bearer <AUTH_TOKEN>). Regenerate the token from the dashboard if needed.

Rate limits and 429 responses

The API reference lists 429 Too Many Requests as a possible response. If you receive 429, back off and retry after a delay; implement exponential backoff.

Common HTTP errors

• 400 Bad Request: malformed request or validation error.
• 403 Forbidden: token lacks required permissions.
• 404 Not Found: resource not found (check IDs/UIDs).
• 409 Conflict: duplicate resource or conflict on create.
• 422 Validation Error: payload failed schema validation.

Pagination and listing notes

The API reference exposes standard list endpoints (GET /api/v1/app, GET /api/v1/event-type, GET /api/v1/app/{app_id}/msg, GET /api/v1/app/{app_id}/endpoint). Refer to the OpenAPI docs for query parameters (limit/offset or cursor) supported by each list endpoint; use the documented parameters for paging large result sets.

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