What the data for this category looks like
Data related to steel trade profitability comes from public industry data sources for domestic bulk commodity spot trading. Updates follow a fixed daily schedule, with full datasets for the previous trading day released at set times. The data document uses a structured JSON array format. Each entry includes trading variety code, variety name, daily transaction average price, upstream raw material cost average price, daily sales and purchase gross profit, and covered trade area scope. Transaction average price and cost average price use yuan/ton as their unit. Gross profit uses yuan/ton as its unit. The area field is divided based on major domestic steel trade distribution hubs. This data does not include real-time market quotes. Historical statistical results may only be retrieved by calendar day.
What constraints these characteristics impose on HTTP interfaces and external systems
Since data is released as full daily updated historical statistics, interfaces do not need to support real-time incremental pulling. Scheduled batch pulling tasks are suitable, and only fixed-time calls are required. Since data includes segmented fields for multiple varieties and regions, interfaces must support parameters for filtering by variety code and trade area to narrow returned data scope. Since data units are uniformly yuan/ton, numerical fields returned by interfaces do not need extra conversion. Legality of numerical values must still be verified. Full data has a large single return volume. Interfaces must support pagination or batch pulling parameters to avoid excessive request load.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
external_api_request_timeout | 600 seconds | Full data pulling for the steel trade category includes multiple varieties and regions, leading to relatively long interface response times. This value must match the maximum pulling duration |
external_api_batch_size | 50 items/request | Excessive data returned in a single request can trigger timeouts. Split requests based on the conventional number of varieties for the category to balance load and efficiency |
api_rate_limit_quota | 10 requests/hour | Data updates only once per day. This quota covers scheduled pulling requirements while avoiding triggers of external data source rate limiting rules |
external_api_response_schema_check | Enabled | Steel trade data uses fixed-format fields. Enabling verification filters returned results with abnormal formats and prevents errors in subsequent processing flows |
cache_expire_time | 22 hours | Set slightly shorter than the data update cycle to ensure the latest daily statistical data is retrieved each time pulling runs |
api_error_retry_max_times | 3 times | This configuration is a newly added retry control item in version V4.9.7. External data sources may experience temporary fluctuations. Limited retries reduce pulling failure probability while avoiding duplicate requests consuming resources |
The parameter values provided on this page are all conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on relevant samples before finalizing the configuration.
Three Common Configuration Mistakes
- Phenomenon: Interfaces return a 429 Too Many Requests status code, or return an error message stating "request frequency exceeded limit". Cause: A reasonable call quota was not configured based on data update frequency, and frequent pulling requests trigger external data source rate limiting rules.
- Phenomenon: The
sales and purchase gross profitfield in pulled data is empty or has an abnormal format. Cause: Theexternal_api_response_schema_checkconfiguration was not enabled, and returned field legality was not verified, leading to erroneous data entering subsequent processing flows. - Phenomenon: Identical old data is pulled for multiple consecutive days, and latest same-day updated market quotes are not obtained. Cause: Cache duration is set to more than 24 hours, which does not match the daily data update cycle, leading to delayed cache refresh.
How to Confirm Proper Configuration
- Initiate a single pulling request. Check if returned fields include preset trading varieties, transaction average prices, trade areas and other required information. Verify that field units meet category requirements.
- Configure a scheduled pulling task. Wait for one full data update cycle, then compare two pulling results to confirm data has been updated.
- Initiate more than 3 concurrent requests. Check if rate limiting errors are triggered, and confirm call quotas meet actual usage needs.
- View system logs. Confirm interface requests automatically trigger retry logic when temporary failures occur, with no manual intervention required.
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.