Load HL Gaming Free Fire Redeem Codes data to DuckDB
Build a HL Gaming Free Fire Redeem Codes to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the HL Gaming Free Fire Redeem Codes API base URL, auth, endpoints, and incremental loading.
HL Gaming provides an API for accessing Free Fire redeem codes and player account information. Everything needed to build a working HL Gaming Free Fire Redeem Codes → 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 HL Gaming Free Fire Redeem Codes to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from HL Gaming Free Fire Redeem Codes 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 HL Gaming Free Fire Redeem Codes 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.
HL Gaming Free Fire Redeem Codes API at a glance
| Base URL | https://proapis.hlgamingofficial.com/main/games/freefire/reward/api |
| Example endpoint | GET reward/api?sectionName=redeemCode&type=fetch |
| Records found at | result.found_articles |
| Authentication | All requests require a useruid and a secret API key passed as query parameters |
| Pagination | Not paginated |
| API reference | https://www.hlgamingofficial.com/p/free-fire-api-data-documentation.html |
These values come from the HL Gaming Free Fire Redeem Codes API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the HL Gaming Free Fire Redeem Codes API?
Authentication is performed by passing 'useruid' and 'api' as query parameters in every request; headers are not used for authentication.
1. Get your credentials
To obtain your API credentials for the HL Gaming Free Fire API, navigate to the official developer portal at https://www.hlgamingofficial.com/p/api.html. Follow the on-screen instructions to register or log in, then use the dashboard to generate your unique developer 'useruid' and 'api' (secret API key). These credentials are required for all authenticated API requests.
2. Add them to .dlt/secrets.toml
[sources.hl_gaming_free_fire_redeem_codes_source] api_key = "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 HL Gaming Free Fire Redeem Codes data can I load into DuckDB?
These are the HL Gaming Free Fire Redeem Codes endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| redeem_codes | reward/api?sectionName=redeemCode&type=fetch | GET | result.found_articles | Fetch live redeem code articles |
| redeem_codes_by_date | reward/api?sectionName=redeemCode&type=fetch&subSec={date} | GET | result.found_articles | Fetch redeem code articles for a specific date |
| generate_redeem_code | reward/api?sectionName=redeemCode&type=generate | GET | result | Generate a new redeem code |
| account_info | account/api?sectionName=AccountInfo | GET | Fetch player account details | |
| ff_leaderboard | leaderboard/api?sectionName=ff_leaderboard | GET | Fetch Free Fire leaderboard data |
How do I load only new HL Gaming Free Fire Redeem Codes records?
The HL Gaming Free Fire Redeem Codes 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.
{"name": "redeem_codes", "endpoint": { "path": "reward/api?sectionName=redeemCode&type=fetch", # 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.
What does the generated HL Gaming Free Fire Redeem Codes pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading 'reward/api?sectionName=redeemCode&type=fetch' and 'reward/api?sectionName=redeemCode&type=generate' from the HL Gaming Free Fire Redeem Codes API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def hl_gaming_free_fire_redeem_codes_source(api_key=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://proapis.hlgamingofficial.com/main/games/freefire/reward/api", "auth": {"type": "api_key", "api_key": api_key, "name": "api"}, }, "resources": [ {"name": "redeem_codes", "endpoint": {"path": "reward/api?sectionName=redeemCode&type=fetch", "data_selector": "result.found_articles"}}, {"name": "redeem_codes_by_date", "endpoint": {"path": "reward/api?sectionName=redeemCode&type=fetch&subSec={date}", "data_selector": "result.found_articles"}} ], } yield from rest_api_resources(config) def load_hl_gaming_free_fire_redeem_codes_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="hl_gaming_free_fire_redeem_codes_pipeline", destination="duckdb", dataset_name="hl_gaming_free_fire_redeem_codes_data", ) load_info = pipeline.run(hl_gaming_free_fire_redeem_codes_source()) print(load_info) if __name__ == "__main__": load_hl_gaming_free_fire_redeem_codes_to_duckdb()
Run it with python hl_gaming_free_fire_redeem_codes_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 HL Gaming Free Fire Redeem Codes 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("hl_gaming_free_fire_redeem_codes_pipeline").dataset() df = data.redeem_codes.df() print(df.head())
SQL:
SELECT * FROM hl_gaming_free_fire_redeem_codes_data.redeem_codes LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the HL Gaming Free Fire Redeem Codes 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 HL Gaming Free Fire Redeem Codes 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 HL Gaming Free Fire Redeem Codes 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
Was this page helpful?
Community Hub
Need more dlt context for HL Gaming Free Fire Redeem Codes to DuckDB?
Request dlt skills, commands, AGENT.md files, and AI-native context.