What this category’s data looks like
Financial report data for the construction machinery industry comes primarily from periodic public disclosures issued by listed companies, including quarterly, semi-annual, and annual reports. Some enterprises also release monthly operational and sales data for their core equipment. Document structures include consolidated financial statements (balance sheet, income statement, cash flow statement), management discussion and analysis sections, and segmented business revenue breakdowns such as revenue shares for models like excavators, loaders, and cranes. Core fields cover main business revenue, segmented business revenue, accounts receivable, inventory, equipment sales volume, and similar metrics. Common units include RMB yuan, ten thousand yuan, units, and others. Data update cycles align with disclosure requirements: periodic reports are updated on a quarterly, semi-annual, or annual schedule, while monthly operational data is updated each month.
Constraints imposed on HTTP interfaces and external systems
Construction machinery financial reports have multiple segmented business dimensions, mix structured report data and unstructured analysis text, and have varied update cycles. These characteristics create multiple constraints for the interface and external system workflow. First, there are many segmented business fields. Interfaces must support filtering parameters based on business segments to avoid returning redundant data. Second, data sources include corporate financial reports and public industry data. Field units may differ across data sources, so the interface layer must perform unit standardization conversions. Third, update cycles cover monthly, quarterly, and annual frequencies. Multiple scheduled pull rules must be configured to match the different update rhythms of each data type. Finally, financial report documents are lengthy. Interface calls and parsing must reserve sufficient time to prevent timeout interruptions.
Configuration settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Construction machinery financial report PDFs typically include multiple pages of financial statements and business analysis content, resulting in long parsing times |
HTTP_REQUEST_TIMEOUT | 60 seconds | External financial report data source interfaces have measurable response delays; reserve sufficient request duration |
RETRY_MAX_TIMES | 2 times | Address temporary network fluctuations or interface rate limiting scenarios, preventing task interruptions caused by single request failures |
DATA_UNIT_NORMALIZATION | Enabled | Different data sources return currency units such as yuan and ten thousand yuan; standardizing units simplifies subsequent analysis logic |
SCHEDULE_CRON_EXPR | 0 0 2 * * * (monthly data), 0 0 3 1-15 * * (quarterly/annual data) | Match the disclosure and update rhythm of construction machinery financial reports, avoiding repeated pulls or missed updates |
STRUCTURED_FIELD_MAPPING | Map using construction machinery financial report standard fields | Adapt to the unique segmented business fields of construction machinery financial reports, ensuring pulled data aligns with analysis requirements |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three common configuration mistakes
- Phenomenon: Calling an external financial report data source interface returns
400 Bad Request. Cause: TheSTRUCTURED_FIELD_MAPPINGparameter is not configured correctly. Request fields do not match the data source requirements, leading to an incorrect interface return format. - Phenomenon: Internally deployed FastGPT nodes fail to access the management page or call external interfaces with
net::ERR_INCOMPLETE_RESPONSE. Cause: Cross-origin allowed external data source domains are not configured. The browser blocks cross-origin requests. - Phenomenon: Scheduled pull tasks repeatedly trigger financial report data for the same cycle. Cause: The
SCHEDULE_CRON_EXPRtrigger frequency does not match the data update cycle. For example, using a daily pull schedule for annual financial report data that only updates quarterly.
How to confirm correct configuration
- Initiate a single structured data pull request, compare the returned fields with the preset construction machinery financial report standard fields to confirm consistency.
- Manually upload a publicly available construction machinery enterprise financial report PDF, verify that the parsed text covers core financial statements and business analysis content.
- View system interface call logs, confirm that the return status codes of the last three external data source requests are
200 OK. - Check the scheduled task management interface, confirm that the task trigger cycle matches the financial report disclosure rhythm.
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.