Load TikTok data to DuckDB
Build a TikTok to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the TikTok API base URL, auth, endpoints, and incremental loading.
TikTok for Developers provides REST API access to platform data including Content Posting and Research APIs for authorized partners and researchers. Everything needed to build a working TikTok → 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.
Build your TikTok to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from TikTok 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 TikTok 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.
TikTok API at a glance
| Base URL | https://open.tiktokapis.com |
| Example endpoint | POST v2/video/list/ |
| Records found at | videos |
| Authentication | All requests require a Bearer token in the Authorization header — sent in the Authorization header, prefixed Bearer |
| Pagination | Cursor-based via cursor, page size via max_count (or page_size) (default 10, max 100). TikTok APIs utilize two distinct pagination patterns. Content/Research APIs typically use cursor-based pagination with 'cursor' and 'max_count' (or 'count') parameters, where 'cursor' is a numerical index or timestamp. Business/Marketing APIs typically use page-number-based pagination with 'page' and 'page_size' parameters. Check specific endpoint documentation as parameter names ('max_count' vs 'count' vs 'page_size') and behavior vary by product line. |
| Incremental field | cursor |
| API reference | https://developers.tiktok.com/doc/tiktok-api-v2-introduction |
These values come from the TikTok API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the TikTok API?
The API uses OAuth 2.0; requests must include an Authorization header with the value 'Bearer <access_token>'.
1. Get your credentials
- Create a developer account at the TikTok for Developers portal (developers.tiktok.com) and log in with your TikTok or TikTok for Business credentials. 2. Create a new application under 'Manage apps' → 'Connect a new app'. 3. Fill in the required application details, including name, description, website URL, and redirect URIs. 4. Select the specific products (e.g., Marketing API, Research API) and permission scopes your application requires. 5. Once the application is created, navigate to the application dashboard to view the generated 'Client key' and 'Client secret'. 6. Note that for production environments, you may need to submit your application for review and pass data-security compliance checks.
2. Add them to .dlt/secrets.toml
[sources.tiktok_source] access_token = "REPLACE_ME"
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.
What TikTok data can I load into DuckDB?
These are the TikTok endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| user_info | v2/user/info/ | GET | Get user profile information | |
| video_list | v2/video/list/ | POST | videos | Get a list of user's public videos |
| video_query | v2/video/query/ | POST | videos | Get detailed information for specific videos |
| research_video_query | v2/research/video/query/ | POST | videos | Query videos using search parameters |
| research_user_followers | v2/research/user/followers/ | POST | Query user followers | |
| research_user_following | v2/research/user/following/ | POST | Query users the user follows | |
| research_video_comments | v2/research/video/comment/list/ | POST | Query comments on a video |
How do I load only new TikTok records?
TikTok exposes cursor on v2/video/list/, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.
{"name": "video_list", "endpoint": { "path": "v2/video/list/", "data_selector": "videos", "incremental": {"cursor_path": "cursor", "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.
What does the generated TikTok pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading https://open.tiktokapis.com/v2/oauth/token/ and https://open.tiktokapis.com/v2/research/video/query/ from the TikTok API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def tiktok_source(access_token=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://open.tiktokapis.com", "auth": {"type": "bearer", "token": access_token}, }, "resources": [ {"name": "video_list", "endpoint": {"path": "v2/video/list/", "data_selector": "videos"}}, {"name": "research_video_query", "endpoint": {"path": "v2/research/video/query/", "data_selector": "videos"}} ], } yield from rest_api_resources(config) def load_tiktok_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="tiktok_pipeline", destination="duckdb", dataset_name="tiktok_data", ) load_info = pipeline.run(tiktok_source()) print(load_info) if __name__ == "__main__": load_tiktok_to_duckdb()
Run it with python tiktok_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.
How do I query TikTok 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):
import dlt data = dlt.pipeline("tiktok_pipeline").dataset() df = data.video_list.df() print(df.head())
SQL:
SELECT * FROM tiktok_data.video_list LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the TikTok 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 TikTok loads into governed, documented models.
- Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.
What other destinations can I load TikTok data to?
dlt loads into any of these — only the destination argument changes:
| Destination | Example value |
|---|---|
| PostgreSQL | "postgres" |
| BigQuery | "bigquery" |
| Snowflake | "snowflake" |
| Redshift | "redshift" |
| Databricks | "databricks" |
| Filesystem (S3, GCS, Azure) | "filesystem" |
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.
Next steps
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