122 lines
3.9 KiB
Python
122 lines
3.9 KiB
Python
import csv
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from collections import defaultdict
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def load_data(filepath: str) -> list[dict]:
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records = []
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with open(filepath, mode='r', encoding='utf-8') as f:
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reader = csv.reader(f)
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for row in reader:
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if not row: continue
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name, category, price, quantity, date = row
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records.append({
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"name": name.strip(),
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"category": category.strip(),
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"price": float(price),
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"quantity": int(quantity),
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"date": date.strip()
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})
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return records
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def clean_data(records: list[dict]) -> list[dict]:
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cleaned = []
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for r in records:
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if r['price'] >= 0 and r['quantity'] >= 0:
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r['category'] = r['category'].lower()
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cleaned.append(r)
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return cleaned
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def filter_by_category(records: list[dict], category: str) -> list[dict]:
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return [r for r in records if r['category'] == category.lower()]
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def filter_by_price_range(records: list[dict], min_price: float, max_price: float) -> list[dict]:
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return [r for r in records if min_price <= r['price'] <= max_price]
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def total_revenue(records: list[dict]) -> float:
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return sum(r['price'] * r['quantity'] for r in records)
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def category_revenue(records: list[dict]) -> dict[str, float]:
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rev_map = defaultdict(float)
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for r in records:
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rev_map[r['category']] += r['price'] * r['quantity']
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return dict(rev_map)
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def top_n_items(records: list[dict], n: int) -> list[tuple[str, int]]:
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counts = defaultdict(int)
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for r in records:
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counts[r['name']] += r['quantity']
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sorted_items = sorted(counts.items(), key=lambda x: x[1], reverse=True)
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return sorted_items[:n]
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def monthly_sales(records: list[dict]) -> dict[str, float]:
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monthly_rev = defaultdict(float)
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for r in records:
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month = r['date'][:7] # Извлекает YYYY-MM
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monthly_rev[month] += r['price'] * r['quantity']
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return dict(sorted(monthly_rev.items()))
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def best_selling_category(records: list[dict]) -> str:
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cat_rev = category_revenue(records)
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if not cat_rev: return ""
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return max(cat_rev, key=cat_rev.get)
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def export_summary(records: list[dict], output_path: str) -> None:
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rev = total_revenue(records)
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best_cat = best_selling_category(records)
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top3 = top_n_items(records, 3)
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monthly = monthly_sales(records)
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with open(output_path, 'w', encoding='utf-8') as f:
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f.write("СВОДНЫЙ ОТЧЕТ ПО ПРОДАЖАМ\n")
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f.write("=" * 30 + "\n")
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f.write(f"Общая выручка: {rev:.2f}\n")
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f.write(f"Лучшая категория: {best_cat}\n\n")
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f.write("Топ-3 товара (по количеству):\n")
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for name, qty in top3:
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f.write(f"- {name}: {qty} шт.\n")
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f.write("\nВыручка по месяцам:\n")
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for month, m_rev in monthly.items():
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f.write(f"- {month}: {m_rev:.2f}\n")
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def main() -> None:
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# 1. Загрузка
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data = load_data("data/sales.csv")
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# 2. Очистка
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data = clean_data(data)
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# 3. Фильтрация
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filtered = filter_by_price_range(data, 10, 500)
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# 4. Анализ
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rev = total_revenue(filtered)
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category_revenue(filtered)
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best_cat = best_selling_category(filtered)
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top3 = top_n_items(filtered, 3)
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monthly = monthly_sales(filtered)
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# 5. Вывод в консоль
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print(f"--- Результаты анализа (фильтр: 10-500 руб) ---")
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print(f"Общая выручка: {rev:.2f}")
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print(f"Лучшая категория: {best_cat.capitalize()}")
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print(f"Топ-3 товара: {top3}")
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print(f"Выручка по месяцам: {monthly}")
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# 6. Экспорт
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export_summary(filtered, "report.txt")
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print(f"\nОтчет успешно сохранен в report.txt")
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if __name__ == "__main__":
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main()
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