Implement new export statistics module that aggregates monthly export data by region, including total volume, revenue, and top product categories. The update introduces a scheduled task to refresh statistics daily from the raw export logs table, with support for historical data backfill.
Implement a new statistics module that records export operations per month, including total revenue, item count, and average order value. The module aggregates data from the orders table and stores precomputed summaries in a dedicated export_stats collection for faster dashboard queries.
Implement a new aggregation pipeline in the statistics module that groups export events by month, calculates total exports per user, and stores the results in a dedicated `monthly_export_stats` collection. This enables efficient generation of user activity reports without scanning the full export log.
The user lookup function previously iterated over the entire user list sequentially,
causing O(n) latency for each request. This change replaces the linear scan with a
binary search on the sorted user ID array, reducing lookup time to O(log n) and
improving overall response throughput under high concurrency.
Implement a new statistics module that records and aggregates export operations per user on a monthly basis. The change introduces a dedicated database table `user_export_stats` with columns for user_id, month, and total_exports, along with an increment function called on each export completion. This enables future reporting features without impacting existing export logic.
Implement a new aggregation pipeline in the statistics module that groups export events by month and user ID, enabling generation of monthly activity reports for the admin dashboard. The pipeline filters events from the last 12 months, computes per-user export counts, and stores results in a dedicated statistics collection for efficient querying.
The change introduces a new aggregation pipeline in the statistics module that computes monthly export counts grouped by file format and user role. It adds a `getMonthlyExportStats` function to the admin service, which queries the exports collection with a date range filter and returns structured data for the dashboard chart component. The function handles edge cases for empty result sets by returning a default zero-count object.
The user lookup endpoint previously used a linear scan over the user list,
which degraded performance under high concurrency. This change replaces
the search algorithm with a binary search on the sorted user ID array,
reducing average lookup time from O(n) to O(log n). The user list is
maintained in sorted order via insertion sort on new user registration.
Implement a new statistics module that records daily export counts, file sizes, and user activity metrics. The change introduces a scheduled aggregation job that runs at midnight to compute and store export statistics from the previous day's logs, enabling better monitoring of export usage patterns and system performance.
Implement a new aggregation pipeline in the statistics module that groups export events by month and user ID, enabling generation of monthly activity reports for the admin dashboard. The pipeline filters events from the last 12 months, computes per-user export counts, and stores results in a dedicated statistics collection.
Implement a new aggregation pipeline in the statistics module that groups export events by month and user ID, enabling generation of monthly activity reports for administrators. The change includes a new `getMonthlyExportStats` function that queries the exports collection with a date range filter and returns aggregated counts per user.
Implement a new aggregation pipeline in the statistics module that groups export events by month and user ID, computing total exports per user per month. The change introduces a `getMonthlyExportStats` function that queries the exports collection with a $match stage filtering on the last 12 months, followed by $group on year-month and userId, and a $sort stage for chronological ordering. This enables the dashboard to display per-user export volume trends over time.
- Implemented a new statistics module to track export operations
- Added counters for total exports, unique users, and export types
- Integrated statistics logging into the existing export handler
The README now includes a high-level description of the project's purpose, a prerequisites section listing required tools, and step-by-step installation and configuration commands for new contributors.
The README now includes a high-level description of the project's purpose, a prerequisites section listing required tools, and step-by-step installation commands for cloning, dependency setup, and running the application locally.
Adds a new BotManager class that maintains a mutable list of active bots, allowing bots to be added or removed at runtime without restarting the application. Includes thread-safe operations for concurrent access and a new API endpoint to query the current bot roster.
The algorithm analyzes user interaction patterns to identify anomalous behavior, flagging accounts with irregular login times, rapid-fire actions, or unusual data access sequences. It integrates with the existing monitoring pipeline to generate alerts for security review.
The polling interval for the metrics collection service has been adjusted from 30 seconds to 60 seconds to reduce system load and network traffic while maintaining adequate monitoring granularity.
Implement a new aggregation pipeline that computes total export volume per month, grouped by product category and destination region. The change introduces a `monthly_export_stats` collection updated via a scheduled cron job, with indexes on `year_month` and `category` for efficient querying. The statistics module now exposes a `/api/stats/exports/monthly` endpoint returning paginated results sorted by descending volume.
- Implemented a new statistics module to record and monitor export operations
- Added tracking for export timestamps, file sizes, and user identifiers
- Updated export handler to log each completed export with relevant metadata
The README now includes a brief overview of the project's purpose and
step-by-step guidance for local development setup, including
prerequisites and installation commands.
Implement a new export statistics module that records and aggregates metrics for user data export operations, including timestamps, file sizes, and export types. This enables monitoring of export frequency and data volume across the platform.
The export statistics module now includes a new monthly aggregation function that calculates user activity metrics such as total exports, unique users, and average export size per month. This data is stored in a dedicated statistics table and exposed via a new API endpoint for the admin dashboard.
Implement a new aggregation pipeline in the statistics module that groups export events by month and user ID, enabling generation of monthly activity reports for the admin dashboard. The change includes a new `getMonthlyExportStats` function that queries the exports collection with a date range filter and returns aggregated counts per user.
The commit introduces a new image file intended for use as a default avatar when a user has not uploaded a custom profile picture. This ensures visual consistency across the user interface by providing a generic fallback graphic.
The previous thread pool implementation caused GIL contention under heavy CPU workloads. This change swaps concurrent.futures.ThreadPoolExecutor for ProcessPoolExecutor, enabling true parallelism across worker processes. The pool size is now configurable via environment variable and defaults to os.cpu_count(). Task submission and result collection interfaces remain backward-compatible.
Implement a new export statistics module that aggregates monthly export data including total revenue, shipment counts, and per-category breakdowns. The module introduces a scheduled task that runs on the 1st of each month to compute and store statistics from the orders and shipments tables, enabling historical trend analysis and reporting.
Implement a new statistics module that aggregates and stores monthly export counts per user, enabling detailed activity reporting and usage monitoring. The change introduces a dedicated database table for export statistics, a background job to compute monthly aggregates from the exports log, and an API endpoint to retrieve per-user export statistics for the past 12 months.
The profiles table previously lacked an index on the user_id column, causing slow query performance when filtering by user. This change adds a B-tree index on user_id to optimize read operations in the user profile retrieval endpoint.
Implement a new statistics module that aggregates and stores monthly export counts per user, enabling detailed activity reporting and usage monitoring. The module includes a background job that runs on the 1st of each month to finalize previous month's data, and exposes an API endpoint for querying export statistics by user ID and date range.
Implement a new statistics module that aggregates and stores monthly export counts per user, enabling detailed activity reports and usage monitoring. The module includes a background job that runs on the 1st of each month to compute and persist the previous month's export metrics, along with a new database table for storing the aggregated data.
Implement a new aggregation pipeline in the statistics module that groups export events by month and user ID, enabling generation of monthly activity reports for administrators. The change introduces a `getMonthlyExportStats` function that queries the exports collection, filters by the last 12 months, and returns aggregated counts per user per month.
Implement a new monthly export statistics feature that records and aggregates export activity data. The change introduces a dedicated statistics collection mechanism within the analytics module, enabling tracking of export volumes, success rates, and user engagement metrics on a monthly basis. This enhancement provides administrators with granular visibility into export patterns and system utilization over time.
Implement a new statistics module that records and aggregates export operations, including timestamps, file sizes, and user identifiers. This enables monitoring of export frequency and data volume for compliance and analytics purposes.
- Implemented a new statistics module to record and monitor export operations
- Added tracking for export timestamps, file sizes, and user identifiers
- Updated export handler to log each completed export with relevant metadata
Implement a new content validation module that scans comment text for potentially harmful or inappropriate patterns before submission. The checker uses regex-based pattern matching to flag common spam, abuse, and prohibited content, returning a boolean result for downstream moderation handling.
The change introduces a new aggregation pipeline in the statistics module that groups export events by month, calculates total exports per user, and stores the results in a dedicated collection for efficient report generation.
Implement a new aggregation pipeline in the statistics module that groups export events by month and user ID, enabling generation of monthly activity reports for administrators. The change adds a `getMonthlyExportStats` function that queries the exports collection with a $match stage filtering on the last 12 months, followed by $group on year-month and userId, and a $sort stage for chronological ordering. This provides the backend support for the upcoming admin dashboard export statistics widget.
- Implemented a new statistics module to record export events
- Added database migration for export_logs table with user_id and timestamp
- Updated export handler to increment counter on successful completion
Implement a new statistics module that records export operations per month,
including total revenue, item count, and average order value. The module
aggregates data from the orders and shipments tables, grouping results by
calendar month for reporting purposes.
The export statistics module now supports quarterly data aggregation and regional filtering parameters. The `ExportStats` class has been extended with new methods `getQuarterlyBreakdown()` and `filterByRegion()`. The database schema migration adds a `region` column to the `export_stats` table. The API endpoint `/api/export-stats` now accepts optional `quarter` and `region` query parameters.
- Implemented a new statistics module to record and monitor user export activities
- Added database schema changes to store export timestamps and file sizes
- Updated export controller to log each export event with relevant metadata
- Created API endpoint for retrieving aggregated export statistics
Implement a new export statistics module that aggregates monthly export data including total revenue, shipment counts, and per-category breakdowns. The module introduces a scheduled task that runs on the 1st of each month to compute and store statistics from the orders and shipments tables, enabling historical trend analysis and reporting.
The change introduces a new aggregation pipeline in the statistics module that computes monthly export counts grouped by product category. It adds a dedicated `ExportStatistic` model with fields for period, category, and total exports, and wires the aggregation into the existing admin statistics endpoint. The implementation uses MongoDB's `$group` and `$project` stages to transform raw export logs into the required summary format, ensuring the dashboard can display per-category trends over time.
The change introduces a new aggregation pipeline in the statistics module that groups export records by month, computing total exports per user and average file size. This data is stored in a dedicated `monthly_export_stats` collection to support the upcoming analytics dashboard feature.
Implement a new aggregation pipeline in the statistics module that groups export events by month and user ID, computing total exports per user per month. The change introduces a `getMonthlyExportStats` function that queries the exports collection with a `$group` stage on `userId` and `month` fields, returning sorted results by month descending. This enables the dashboard to display per-user export volume trends over time.
Implement a new export statistics module that records and aggregates metrics on user data export operations. The change introduces a dedicated statistics service that tracks export frequency, data volume, and user engagement patterns. This enables administrators to monitor export activity and optimize system performance based on usage trends.
Implement a new statistics module that records export operations per month,
including total revenue, item count, and average order value. The module
aggregates data from the orders and shipments tables, grouping results by
calendar month for reporting purposes.
Implement a new logging utility with configurable verbosity levels and integrate a rant_history data structure to persist user interaction records across sessions. The logging module includes timestamped entries with severity tags, while rant_history stores chronological entries with metadata for future analysis and replay features.
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