HTTP Interfaces and External Systems for Professional Services Yield

Data for professional services yield and market daily reports comes from official APIs of licensed financial information service providers, and

What the data for this category looks like

Data for professional services yield and market daily reports comes from official APIs of licensed financial information service providers, and on-exchange and off-exchange transaction settlement databases. Data updates follow trading day schedules. Full data updates run only at fixed post-close nodes each day. Some intraday reference fields support minute-level refresh. Documents use a standardized structured format. A single record corresponds to one service target. The record includes two types of fields: metadata and revenue accounting. Metadata fields include target identifier, category, and release timestamp. Revenue accounting fields include daily calculated value and cumulative benchmark comparison value. All fields follow official specifications from the data source, with no redundant content. Numeric fields use a unified accounting standard.

What constraints these characteristics impose on HTTP interfaces and external systems

Fixed daily update schedules require HTTP calls to match the data source’s update nodes. This avoids pulling incomplete temporary data, so precise scheduled trigger rules must be configured. The need to transfer bulk multi-target data requires the API to support pagination or bulk pull parameters. Without these, single requests will time out due to excessive data volume. Standardized but version-differentiated field formats require specifying API version parameters. This prevents field incompatibility from data source upgrades. Strict call frequency limits require configuring reasonable request intervals. This prevents triggering the data source’s rate limiting rules, which would result in rejected calls. Compatibility requirements for external system integration mandate fixed returned data fields. Configure field whitelists to only return necessary content.

How to set configurations

Configuration ItemRecommended ValueRationale
http_request_timeout120 secondsAdapt to response time for bulk pulling multi-category yield data, avoid mid-request interruptions
return_field_whitelistproduct_code, product_name, daily_yield, benchmark_diffOnly retain fields required for professional service broadcasts, reduce transmission volume
api_versionv3Match the current stable API version of the data source, avoid risks from field format changes
request_cron0 19 * * 1-5Match the 19:00 post-close update node on trading days, ensure pulling complete daily data
retry_max_attempts3 attemptsHandle temporary API fluctuations, reduce broadcast delays from single failed calls
auth_typeapi_keyAdapt to standard authentication methods for licensed data sources, ensure valid API call legitimacy

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 individual analysis. Testing on local samples is recommended before finalizing settings.

Three common configuration mistakes

  • A 502 Bad Gateway error occurs, and direct API calls operate normally. The cause is that FastGPT's HTTP plugin has incorrectly configured request headers or proxy parameters, leading to requests being blocked by intermediate nodes.
  • Some fields in pulled data are empty. The cause is that return_field_whitelist is not configured, and unopened fields from the data source are pulled, resulting in null values for corresponding fields in returned results.
  • No valid daily data is pulled after a scheduled task runs. The cause is that the time set in request_cron is earlier than the data source's update node, resulting in pulled incomplete temporary data or empty datasets.

How to confirm correct configuration

  • Manually trigger an HTTP request, check if the returned JSON data includes expected fields such as product_code, daily_yield, publish_time.
  • Review scheduled task execution logs, confirm that data pulling completed successfully after the specified time on trading days, and that the publish_time field in returned data matches the current day's date.
  • Send a test request with an incorrect authentication key, confirm that a 401 Unauthorized error is returned, proving that the authentication configuration is effective.
  • Adjust request_cron to a test time, trigger a pull, verify that the number of pulled records matches the expected target coverage range.

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.