Software Heritage Python API Docs | dltHub

Software Heritage API is a public REST API to query and retrieve archived software source code objects and archive bundles. The REST API base URL is https://archive.softwareheritage.org/api/1 and Most read endpoints are public and require no 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 Software Heritage data in under 10 minutes.

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What data can I load from Software Heritage?

Here are some of the endpoints you can load from Software Heritage:

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How do I authenticate with the Software Heritage API?

The Software Heritage public API supports unauthenticated GET requests for archive browsing and retrieval. No API key or bearer token is required for standard usage.

1. Get your credentials

No credentials required for public read API. If private or alternate services require auth, consult Software Heritage administrators or project docs.

2. Add them to .dlt/secrets.toml

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[sources.software_heritage_source]

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 Software Heritage 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 software_heritage_pipeline.py

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

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Pipeline software_heritage_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset software_heritage_data
The duckdb destination used duckdb:/software_heritage.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 software_heritage_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 origin and snapshot from the Software Heritage 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 software_heritage_source(=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://archive.softwareheritage.org/api/1",
            "auth": {
                "type": "none",
                "": ,
            },
        },
        "resources": [
            {"name": "origin", "endpoint": {"path": "origin/"}},
            {"name": "snapshot", "endpoint": {"path": "snapshot/", "data_selector": "branches"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="software_heritage_pipeline",
        destination="duckdb",
        dataset_name="software_heritage_data",
    )
    load_info = pipeline.run(software_heritage_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("software_heritage_pipeline").dataset()
sessions_df = data.origin.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM software_heritage_data.origin LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("software_heritage_pipeline").dataset()
data.origin.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 Software Heritage 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 and access

Most public GET endpoints do not require authentication. If you receive 401/403, verify you are calling the public archive base URL (https://archive.softwareheritage.org/api/1). For private or admin‑only endpoints contact Software Heritage staff.

Rate limiting and HTTP errors

The API returns standard HTTP status codes. Common responses:

• 200 OK: successful request
• 400 Bad Request: invalid identifier or malformed request (e.g., invalid SWHID)
• 404 Not Found: object not found or no cooking request exists for GET on vault endpoints
• 500+ Server Error: server‑side fault; retry after a backoff

Vault cooking quirks and pagination

• Vault cooking endpoints: POST creates a cooking task; GET on same endpoint returns task status. When status is 'done', use the provided fetch_url to download the raw archive. GET /vault/*/raw/ returns application/gzip binary.
• Directory and origin search endpoints may return top‑level arrays (no enclosing key). Snapshot objects contain a branches key with a list of revisions; directory responses are arrays of entries. No generic pagination key documented for these endpoints; some search/list endpoints return full arrays or may support query parameters — inspect endpoint docs for supported parameters.

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