Workflow Orchestration for Iron Ore Financing Daily Reports

Data sources for iron ore financing daily reports include the public market interface of the Dalian Commodity Exchange, the daily inventory reporting

What the data for this category looks like

Data sources for iron ore financing daily reports include the public market interface of the Dalian Commodity Exchange, the daily inventory reporting system of major domestic ports, and steel plant procurement tracking data from industry information institutions. Data updates are completed within 1 hour after daily market close. The document structure primarily uses structured tables, including core fields such as origin classification, daily spot average price, port inventory, and financing position. Units are yuan/ton, ten thousand tons, and yuan respectively. Some entries include a note on daily trading activity.

What constraints these characteristics impose on workflow orchestration

The requirement for fixed daily updates requires the workflow to be configured with precise scheduled trigger nodes. The trigger window must cover the period after data updates, to avoid pulling outdated, unupdated data. Structured data from multiple sources has inconsistent field names. A field mapping node must be configured to align field identifiers across different data sources, preventing unit confusion or missing fields. Financing position data is sensitive financial information. A permission verification node must be configured to restrict access scope and ensure data compliance. Data has strong timeliness requirements. A timeout retry node must be configured to handle temporary interface fluctuations, ensuring the daily report is generated on time.

How to set configurations

Configuration ItemRecommended ValueRationale
trigger_cron0 15 20 * * ?Matches the update window within 1 hour after Dalian Commodity Exchange market close, triggers 15 minutes early to ensure latest data is pulled
field_mapping_rule{"现货均价":"price", "港口库存":"stock", "融资持仓":"margin"}Unifies field names across multiple data sources, prevents field matching errors during subsequent processing
http_request_timeout30 secondsAdapts to the stable response duration of iron ore data sources, avoids interrupting the daily report generation process due to timeouts
data_validation_schema{"price":{"type":"number", "unit":"yuan/ton"}, "stock":{"type":"number", "unit":"ten thousand tons"}}Validates field types and units of pulled data, filters abnormal values and format errors
retry_count2 timesAddresses temporary fluctuations in data source interfaces, reduces the risk of process interruption from a single failed request
permission_scopeRestricted to internal financial node accessMeets sensitive information security requirements for financing position data, restricts unauthorized access

The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.

Three common errors

  • Issue: The financing position field pulled in the workflow is empty, with a 200 status code returned but missing data fields. Cause: The data_validation_schema verification rule is not configured, and data source field names are not aligned, resulting in incorrectly matched mapped fields.
  • Issue: Base64-encoded image data returned in the workflow cannot be displayed normally in the daily report, with broken icons appearing during preview. Cause: The base64_to_image node is not configured, and no image rendering size parameters are specified, resulting in the front end being unable to correctly parse the base64 string.
  • Issue: The generated daily report text format is chaotic when processing array<object> format data returned from Google Search. Cause: No json_to_text node is used to configure field extraction rules, and no display field order is specified, resulting in unordered data concatenation.

How to confirm the configuration is complete

  • Manually trigger the workflow once, check if the pulled data includes core fields such as daily iron ore spot average price and port inventory, and verify that field units meet expectations.
  • Check if the scheduled trigger configuration time covers the window after data source updates, confirm that the trigger time matches the data update cycle.
  • Review the workflow run logs, confirm there are no abnormal messages such as missing fields, timeouts, or permission errors, and verify that retry counts are executed as configured.
  • Export the generated daily report file, check if the arrangement order of structured fields conforms to the preset mapping rules, and confirm that sensitive data is not accessed by unauthorized nodes.

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.