What This Category’s Data Looks Like
Data sources for duty-free yield rate and market trend daily reports include official operating ledgers of offshore duty-free business entities, the General Administration of Customs offshore duty-free supervision system, and third-party duty-free commodity market monitoring platforms. Data is fully updated for the previous day between 2:00 AM and 4:00 AM daily. Each data entry includes store code, product SKU code, product category, dutiable purchase price, duty-free selling price, daily sales quantity, daily return quantity, and exchange rate benchmark value. Unit specifications: Dutiable purchase price uses CNY, duty-free selling price uses CNY, sales quantity uses units, and exchange rate benchmark value uses CNY per foreign currency unit.
What Constraints Do These Data Characteristics Impose on Workflow Orchestration
Three core constraints come from the data characteristics of duty-free categories. First, data updates follow a fixed schedule. Align workflow trigger nodes with the 5:00 AM daily window to avoid pulling incomplete same-day data. Second, data includes multi-dimensional cross-source fields. Preconfigure field mapping rules to unify field names across different systems. Downstream judgment nodes cannot identify valid fields without this configuration. Third, data scale increases with the number of stores and SKUs. Set reasonable batch pull parameters to prevent timeouts caused by exceeding interface load thresholds during a single pull. For calculations involving exchange rate fields, add a verification node in the workflow to ensure the correct daily benchmark value is used.
How to Configure Parameters
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
trigger_cron | 0 5 * * * | Aligns with the post-update pull window for duty-free data to avoid pulling incomplete same-day data |
batch_fetch_size | 500 items per request | Balances pull efficiency and interface load, adapts to the dataset scale of duty-free categories with multiple SKUs |
field_mapping_rule | purchase_price: duty-paid purchase price, tax_free_price: tax-free selling price, exchange_rate: benchmark exchange rate | Unifies field names across cross-source data, ensures downstream nodes can read data normally |
retry_max_attempts | 3 attempts | Addresses temporary fluctuations in customs supervision interfaces, reduces the probability of full task interruption caused by a single exception |
error_capture_trigger | When a node execution fails | Captures abnormal events in the workflow, such as missing fields or interface timeouts |
code_dependency_install_dir | /app/.local/lib/python3.10/site-packages | Specifies the dependency installation path for code execution modules, matches the Python environment of the FastGPT container |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Symptom: Setting
trigger_cronto real-time triggering, with downstream judgment nodes always showing false. Cause: Duty-free data is updated only once daily. Real-time triggering pulls an empty dataset, causing the judgment tool to fail to match valid fields. - Symptom: After connecting a knowledge base module in the workflow, duty-free commodity market trend data cannot be referenced. Cause: The imported knowledge base documents do not match the field structure of duty-free data, and the field mapping switch is not enabled.
- Symptom: The code execution module fails to call a custom library, with a module not found prompt. Cause: The dependency installation path is not configured to the Python environment directory of the FastGPT container, so the installed library cannot be identified during runtime.
How to Verify a Successful Configuration
- Manually trigger the workflow once, check if the pulled dataset includes all configured fields.
- Check the logs of the error capture node to confirm there are no abnormal records such as missing fields or interface timeouts.
- Run the code execution module to verify that the custom dependency library can be imported and executed normally.
- Compare the yield rate calculation results output by the workflow with the officially announced same-day data to confirm the calculation logic meets expectations.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.