Feedblitz Python API Docs | dltHub

FeedBlitz is an email syndication and newsletter platform exposing a REST API (XML responses) to manage feeds, subscribers, subscriptions, lists (syndications), mailings and related reporting. The REST API base URL is https://www.feedblitz.com/f.api and All requests require an API key supplied as the 'key' query parameter..

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 Feedblitz data in under 10 minutes.

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What data can I load from Feedblitz?

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

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How do I authenticate with the Feedblitz API?

Authentication uses an account API key passed as a query parameter named 'key' on API requests.

1. Get your credentials

1. Log in to your FeedBlitz account. 2) Open Account Management → API Keys (available from the account management menu). 3) Create a new key or copy an existing one. 4) Use that key as the 'key' query parameter on all API calls. If partner/OEM access is required, contact FeedBlitz support.

2. Add them to .dlt/secrets.toml

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[sources.feedblitz_source]
api_key = "your_api_key_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 Feedblitz 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 feedblitz_pipeline.py

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

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Pipeline feedblitz_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset feedblitz_data
The duckdb destination used duckdb:/feedblitz.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 feedblitz_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 feeds and subscribers from the Feedblitz 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 feedblitz_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://www.feedblitz.com/f.api",
            "auth": {
                "type": "api_key",
                "key": api_key,
            },
        },
        "resources": [
            {"name": "feeds", "endpoint": {"path": "feeds", "data_selector": "feeds"}},
            {"name": "subscribers", "endpoint": {"path": "subscribers", "data_selector": "subscribers"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="feedblitz_pipeline",
        destination="duckdb",
        dataset_name="feedblitz_data",
    )
    load_info = pipeline.run(feedblitz_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("feedblitz_pipeline").dataset()
sessions_df = data.feeds.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM feedblitz_data.feeds LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("feedblitz_pipeline").dataset()
data.feeds.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 Feedblitz 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 requests return an error or fail authorization, ensure the account API key is correct and passed as the key query parameter (e.g. https://www.feedblitz.com/f.api/user?key=<your_api_key>). Contact FeedBlitz support if your account does not have API access.

Pagination and large result sets

Use limitstart and limitcount query parameters to page results (limitstart sets offset, limitcount sets page size). Use summary=1 on syndications to reduce payload size.

Missing resources / empty results

When a requested resource or record does not exist the API returns an empty container tag (for example an empty <subscription/> or an empty parent container). Check for empty container elements and treat them as "not found"/no results rather than an HTTP error.

Response format and parsing

The API returns XML wrapped in a <feedblitzapi> root. Records are enclosed in resource‑named containers (e.g. <feeds>, <subscriptions>, <subscribers>, <syndications>, <stats>). Parse XML accordingly — there is no JSON output documented.

Rate limits and partner/OEM access

No public rate limits are documented in the developer docs; if you need higher throughput or OEM/white‑label capabilities, contact FeedBlitz support for partner API access and limits.

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