What the data for this category looks like
Data for aquaculture financing daily reports comes from financing application ledgers submitted by aquaculture entities, aquaculture special subsidy declaration systems of local agricultural and rural authorities, and loan transaction records from partner banks. Full data for the previous day is updated every early morning.
Each daily report document is grouped by aquaculture category, and includes the following fields: unified social credit code of the aquaculture entity, aquaculture water area (unit: mu), applied financing amount (unit: CNY), approval status, actual loan amount (unit: CNY), subsidy matching tier, as well as the number of new financing transactions on the day and cumulative financing quota.
Constraints on HTTP interfaces and external systems
The daily full data update requirement means the interface must support precise data retrieval by date range to avoid redundant duplicate synchronization. The requirement for multiple fields with standardized units means the interface must strictly match units such as mu and CNY during request and response processing, and must not perform unauthorized conversions. The document structure grouped by aquaculture category means the interface must support category filtering parameter configuration to allow external systems to aggregate data by category. Data sourced from multiple external systems means the interface must include cross-system data validation rules to ensure logical compliance such as actual loan amounts not exceeding applied financing amounts. The unified social credit code of the aquaculture entity as the unique identifier means the interface must support querying by this field to meet precise reconciliation requirements.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
HTTP_REQUEST_TIMEOUT | 600 seconds | Aquaculture financing daily report data involves aggregation across multiple systems, and full data retrieval takes a long time. 600 seconds covers most synchronization scenarios |
BATCH_PULL_SIZE | 1000 records per request | Daily data volume is moderate. Pulling 1000 records per request balances interface load and synchronization efficiency |
REQUIRED_FIELDS | ["unified social credit code", "aquaculture water area", "applied financing amount", "actual loan amount"] | These are the core identification and accounting fields for financing daily reports. Missing them makes daily report statistics impossible |
DATE_FILTER_PARAM | start_date,end_date | Daily reports are updated daily. Using date parameters allows precise retrieval of data for a specified period, avoiding redundancy from full data pulls |
DATA_VALIDATION_RULE | actual loan amount ≤ applied financing amount | Financing loan amounts cannot exceed applied amounts, ensuring data compliance |
RESPONSE_UNIT_CONVERT | Disabled | Existing data already uses mu and CNY as standard units, no additional conversion is needed to avoid errors |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by data format, volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on local samples before finalizing settings.
Three Common Mistakes
- Calling the interface returns
422 Unprocessable Entitywith a prompt indicating invalid field format. Cause: Theapplied financing amountrequest parameter was passed as a string type instead of a numeric type, and data was not transmitted in accordance with the configured field format requirements. - Duplicate aquaculture entity financing records appear after daily synchronization. Cause: The
DATE_FILTER_PARAMparameter was not configured, and full data was pulled each time without date filtering, leading to duplicate writes. - Timeout occurs when calling the partner bank's loan data interface. Cause:
HTTP_REQUEST_TIMEOUTwas configured to30 seconds, which does not adapt to the time required for cross-system data retrieval.
How to Confirm Proper Configuration
- Initiate a single interface request with date filtering, check that the returned fields include the mandatory fields specified in the configuration, and that units match the preset requirements.
- Simulate a batch pull request, check that the number of returned data entries matches the configured batch pull size, and that there are no duplicate aquaculture entity records.
- Pass test data that does not comply with validation rules, check that the interface returns the corresponding error prompt to confirm that the data validation rule is active.
- View interface call logs, confirm that the date filtering fields in the request parameters are correctly parsed, and that the pulled data period matches the request parameters.
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.