Load LeetCode Contest API data to DuckDB

LeetCode Contest API is a public service that provides access to contestant data for LeetCode contests. Everything needed to build a working LeetCode Contest API → DuckDB pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.

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Build your LeetCode Contest API to DuckDB pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

PromptCopy prompt
Run uvx dlthub-init@latest to build a pipeline from LeetCode Contest API to DuckDB and run it on dltHub

That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the LeetCode Contest API API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →

Prefer to write it yourself? Every fact the agent uses is below.

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LeetCode Contest API API at a glance

These values come from the LeetCode Contest API API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the LeetCode Contest API API?

The LeetCode Contest API does not require authentication; no credentials or headers are needed for access.

1. Get your credentials

LeetCode does not provide an official REST API with traditional API key credentials. To access authenticated LeetCode endpoints or user-specific data, you must extract session cookies from your web browser: 1. Log in to your LeetCode account in a browser. 2. Open Developer Tools (F12 or Ctrl+Shift+I) and navigate to the Application or Storage tab. 3. Under the Cookies section for https://leetcode.com, locate and copy the values for 'LEETCODE_SESSION' and 'csrftoken'. These values are used in place of traditional API keys.

2. Add them to .dlt/secrets.toml

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[sources.leetcode_contest_api_source]
leetcode_session = "your_session_cookie_here"
leetcode_csrftoken = "your_csrf_token_here"

dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.

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What LeetCode Contest API data can I load into DuckDB?

These are the LeetCode Contest API endpoints dlt can load into DuckDB:

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How do I load only new LeetCode Contest API records?

The LeetCode Contest API API reference does not document a timestamp or sequence field for these endpoints, so there is nothing to advertise here as verified. Pick a field from the endpoints table above that increases with every write, then set it as the cursor_path.

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{"name": "contest_contestants", "endpoint": {
    "path": "contest/{contest_type}/{contest_number}/{last_page}",
    # Replace with a field that increases on every write.
    "incremental": {"cursor_path": "REPLACE_ME", "initial_value": "2024-01-01T00:00:00Z"},
}}

On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.

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What does the generated LeetCode Contest API pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading contest and user_profile from the LeetCode Contest API API into DuckDB:

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import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def leetcode_contest_api_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "http://leetcode-contest-api.fronte.io",
            "auth": {"type": "api_key", "api_key": api_key, "name": "token", "location": "header"},
        },
        "resources": [
            {"name": "contest_contestants", "endpoint": {"path": "contest/{contest_type}/{contest_number}/{last_page}"}}
        ],
    }
    yield from rest_api_resources(config)


def load_leetcode_contest_api_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="leetcode_contest_api_pipeline",
        destination="duckdb",
        dataset_name="leetcode_contest_api_data",
    )
    load_info = pipeline.run(leetcode_contest_api_source())
    print(load_info)


if __name__ == "__main__":
    load_leetcode_contest_api_to_duckdb()

Run it with python leetcode_contest_api_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.

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How do I query LeetCode Contest API data in DuckDB?

dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("leetcode_contest_api_pipeline").dataset()
df = data.contest_contestants.df()
print(df.head())

SQL:

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SELECT * FROM leetcode_contest_api_data.contest_contestants LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.

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How do I deploy the LeetCode Contest API to DuckDB pipeline in production?

The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.

• Deploy & schedule — run the pipeline as a managed job with automatic retries.
• Monitor — observable job queues, alerting, and load metrics for every run.
• Transform — promote raw LeetCode Contest API loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

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What other destinations can I load LeetCode Contest API data to?

dlt loads into any of these — only the destination argument changes:

Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.

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Next steps

• Ready for production? Book a demo of the dltHub platform →
• dlt LLM-native workflow docs
• REST API source reference
• Join the dlt community on Slack