Added code samples for AI-Agents

services/data_analyzer.py

@@ -0,0 +1,156 @@
+"""Сервис анализа данных детей."""
+from datetime import datetime, timedelta
+from typing import Dict, List, Optional
+
+import pandas as pd
+
+
+class DataAnalyzer:
+    """Сервис для анализа прогресса детей."""
+
+    @staticmethod
+    def calculate_completion_rate(tasks: List[Dict]) -> float:
+        """
+        Рассчитать процент выполнения заданий.
+
+        Args:
+            tasks: Список заданий с полем 'completed'
+
+        Returns:
+            Процент выполнения (0.0 - 1.0)
+        """
+        if not tasks:
+            return 0.0
+
+        completed = sum(1 for task in tasks if task.get("completed", False))
+        return completed / len(tasks)
+
+    @staticmethod
+    def analyze_daily_progress(schedules: List[Dict]) -> Dict:
+        """
+        Проанализировать ежедневный прогресс.
+
+        Args:
+            schedules: Список расписаний с заданиями
+
+        Returns:
+            Словарь с аналитикой
+        """
+        if not schedules:
+            return {
+                "total_days": 0,
+                "average_completion": 0.0,
+                "total_tasks": 0,
+                "completed_tasks": 0,
+            }
+
+        total_tasks = 0
+        completed_tasks = 0
+        completion_rates = []
+
+        for schedule in schedules:
+            tasks = schedule.get("tasks", [])
+            total_tasks += len(tasks)
+            completed_tasks += sum(1 for task in tasks if task.get("completed", False))
+            rate = DataAnalyzer.calculate_completion_rate(tasks)
+            completion_rates.append(rate)
+
+        return {
+            "total_days": len(schedules),
+            "average_completion": sum(completion_rates) / len(completion_rates) if completion_rates else 0.0,
+            "total_tasks": total_tasks,
+            "completed_tasks": completed_tasks,
+            "completion_rate": completed_tasks / total_tasks if total_tasks > 0 else 0.0,
+        }
+
+    @staticmethod
+    def get_category_statistics(schedules: List[Dict]) -> Dict[str, Dict]:
+        """
+        Получить статистику по категориям заданий.
+
+        Args:
+            schedules: Список расписаний
+
+        Returns:
+            Словарь со статистикой по категориям
+        """
+        category_stats: Dict[str, Dict] = {}
+
+        for schedule in schedules:
+            for task in schedule.get("tasks", []):
+                category = task.get("category", "unknown")
+                if category not in category_stats:
+                    category_stats[category] = {
+                        "total": 0,
+                        "completed": 0,
+                        "average_duration": 0.0,
+                        "durations": [],
+                    }
+
+                stats = category_stats[category]
+                stats["total"] += 1
+                if task.get("completed", False):
+                    stats["completed"] += 1
+                if "duration_minutes" in task:
+                    stats["durations"].append(task["duration_minutes"])
+
+        # Вычисляем среднюю длительность
+        for category, stats in category_stats.items():
+            if stats["durations"]:
+                stats["average_duration"] = sum(stats["durations"]) / len(stats["durations"])
+            del stats["durations"]
+
+        return category_stats
+
+    @staticmethod
+    def get_weekly_trend(schedules: List[Dict], days: int = 7) -> List[Dict]:
+        """
+        Получить тренд за последние N дней.
+
+        Args:
+            schedules: Список расписаний
+            days: Количество дней
+
+        Returns:
+            Список словарей с данными по дням
+        """
+        end_date = datetime.now().date()
+        start_date = end_date - timedelta(days=days - 1)
+
+        # Группируем расписания по датам
+        daily_data: Dict[str, List[Dict]] = {}
+        for schedule in schedules:
+            schedule_date = schedule.get("date")
+            if isinstance(schedule_date, str):
+                schedule_date = datetime.fromisoformat(schedule_date).date()
+            elif isinstance(schedule_date, datetime):
+                schedule_date = schedule_date.date()
+
+            if start_date <= schedule_date <= end_date:
+                date_str = str(schedule_date)
+                if date_str not in daily_data:
+                    daily_data[date_str] = []
+                daily_data[date_str].append(schedule)
+
+        # Формируем тренд
+        trend = []
+        current_date = start_date
+        while current_date <= end_date:
+            date_str = str(current_date)
+            day_schedules = daily_data.get(date_str, [])
+            all_tasks = []
+            for sched in day_schedules:
+                all_tasks.extend(sched.get("tasks", []))
+
+            trend.append(
+                {
+                    "date": date_str,
+                    "completion_rate": DataAnalyzer.calculate_completion_rate(all_tasks),
+                    "total_tasks": len(all_tasks),
+                    "completed_tasks": sum(1 for task in all_tasks if task.get("completed", False)),
+                }
+            )
+            current_date += timedelta(days=1)
+
+        return trend
+