What the data for this category looks like
Market and yield data for the apparel and home textile category is primarily sourced from public securities trading APIs and industry information disclosure platforms. Data updates are completed before 17:00 each trading day after market close. No data synchronization occurs on non-trading days. Each data document uses structured JSON or CSV format. Each line corresponds to daily market information for one sub-sector stock. Fields include: 6-digit string security code, security short name (Chinese), sub-sector tag fixed as Apparel and Home Textile, daily closing price (unit: CNY), daily price change value (unit: CNY), daily trading volume (unit: shares), daily trading amount (unit: CNY), and other related fields.
What constraints do these characteristics impose on deployment and upgrade
These data characteristics impose three core constraints on deployment and upgrade workflows. First, data sources must connect to third-party market APIs or upload bulk structured files. During deployment, configure API access permissions or file storage paths, and support importing data sources in different formats. Second, the update schedule is tied to trading calendars. Scheduled tasks must only run on trading days to avoid resource waste from non-trading day execution. Third, single batch data contains a large number of stock entries. Adjust concurrency and timeout parameters during batch parsing to prevent memory overflow or task timeouts. When upgrading versions, retain compatibility logic for old data sources to ensure previously imported apparel and home textile data loads correctly.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Bulk market data files for the apparel and home textile sub-sector typically contain hundreds of stock records, leading to longer parsing times |
UPLOAD_FILE_MAX_SIZE | 2000 MB | CSV files for bulk stock market data tend to have large file sizes, so upload limits need to be relaxed |
CRON_EXPRESSION | 0 18 * * 1-5 | Matches the update schedule of completing data updates before 18:00 on trading days, triggering tasks only at 18:00 on Monday through Friday |
RECALL_TOP_N | Top 10 entries | The number of stocks in the apparel and home textile sub-sector is limited, so a moderate number of recalls can cover core reporting needs without excess |
SIMILARITY_THRESHOLD | 0.75–0.85 | Market data fields have strong correlation, so a reasonable threshold is needed to filter redundant results with low matching scores |
MAX_CONTEXT | 8000 characters | The context length of daily reports typically does not exceed this range, ensuring content coherence |
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 mistakes
- The symptom is a
500 Internal Server Errorreturned during local source code deployment, with logs showingdatabase connection failed. The cause is failure to correctly configure API keys or access whitelists for third-party market data sources, preventing retrieval of apparel and home textile market data. - The symptom is a
401 Unauthorizederror returned when executing the data synchronizationcurlcommand, appearing the first time the task is triggered after an upgrade. The cause is failure to synchronously update authentication tokens for third-party market data sources during the upgrade process, resulting in denied access. - The symptom is missing stock price data in the generated daily report. Checking parsing logs reveals that the
close_pricefield was not mapped correctly. The cause is binding the target field to an incorrect placeholder during configuration field mapping, with no alignment to the actual fields in the data source.
How to confirm the configuration is complete
- Navigate to the FastGPT data source management page, check the connection status of the apparel and home textile market data source, confirm it shows a normal connection status, and adjust connection test parameters based on the data source type.
- Manually trigger a data parsing task, check the parsing logs for missing fields or timeout errors, and adjust the corresponding configuration items based on log prompts.
- Generate a test daily report, verify that the broadcast content includes complete market data fields for apparel and home textile stocks, and supplement or adjust recall and field mapping configurations based on the report content.
- Wait for a scheduled task to run automatically on a trading day, confirm that the daily report file generated after task completion has the correct format, with no redundant or missing content.
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.