Chrome Developer Documentation Python API Docs | dltHub

Chrome Web Store API is a Google-provided REST API to programmatically manage Chrome Web Store items (upload, publish, fetch status) and associated developer workflows. (Also references Chrome Management API which provides administrative device and app management for Chrome OS and Chrome Browser.) The REST API base URL is https://chromewebstore.googleapis.com and All requests require OAuth2 (Bearer) access tokens (Google API OAuth 2.0)..

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 Chrome Developer Documentation data in under 10 minutes.

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What data can I load from Chrome Developer Documentation?

Here are some of the endpoints you can load from Chrome Developer Documentation:

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How do I authenticate with the Chrome Developer Documentation API?

The APIs use Google OAuth 2.0. Obtain client ID/secret, request user consent for the scope https://www.googleapis.com/auth/chromewebstore, exchange auth code or refresh token for an access_token, then send Authorization: Bearer <access_token> header on requests.

1. Get your credentials

1. Create/choose a Google Cloud project. 2) Enable the Chrome Web Store API. 3) Configure OAuth consent screen. 4) In APIs & Services > Credentials, Create Credentials > OAuth client ID (Web application). 5) Save client ID and client secret. 6) Use OAuth Playground or your flow with scope https://www.googleapis.com/auth/chromewebstore to get refresh/access tokens.

2. Add them to .dlt/secrets.toml

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[sources.chrome_dev_docs_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.

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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 Chrome Developer Documentation 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 chrome_dev_docs_pipeline.py

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

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Pipeline chrome_dev_docs_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset chrome_dev_docs_data
The duckdb destination used duckdb:/chrome_dev_docs.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 chrome_dev_docs_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 publishers_items and media_upload from the Chrome Developer Documentation 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 chrome_dev_docs_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://chromewebstore.googleapis.com",
            "auth": {
                "type": "bearer",
                "token": access_token,
            },
        },
        "resources": [
            {"name": "publishers_items", "endpoint": {"path": "v2/{name=publishers/*/items/*}:fetchStatus"}},
            {"name": "media_upload", "endpoint": {"path": "upload/v2/{name=publishers/*/items/*}:upload"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="chrome_dev_docs_pipeline",
        destination="duckdb",
        dataset_name="chrome_dev_docs_data",
    )
    load_info = pipeline.run(chrome_dev_docs_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("chrome_dev_docs_pipeline").dataset()
sessions_df = data.publishers_items.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM chrome_dev_docs_data.publishers_items LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("chrome_dev_docs_pipeline").dataset()
data.publishers_items.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 Chrome Developer Documentation 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 your OAuth access token is valid and included in Authorization: Bearer . Refresh tokens can be exchanged at https://oauth2.googleapis.com/token.

Rate limits and quotas

Google APIs enforce per-project quotas; exceedance results in 429 errors. Use exponential backoff on 429 and 5xx responses.

Upload and long-running operations

Uploads use multipart or resumable endpoints (upload/...). Use returned status endpoints (fetchStatus) to poll status.

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