250 lines
7.8 KiB
Markdown
250 lines
7.8 KiB
Markdown
# Reddit データ取得期間の対話形式ヒアリング設計
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## 対話フロー例
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### 1. 基本的な対話フロー
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```python
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def interactive_date_range_prompt():
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"""
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ユーザーと対話してデータ取得期間を決定する
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"""
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print("Reddit Historical Data Fetcher")
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print("="*40)
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# Step 1: 取得目的の確認
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print("\nWhat is the purpose of this data fetch?")
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print("1. Backtesting preparation")
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print("2. Historical analysis")
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print("3. Initial data setup")
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print("4. Gap filling (missing dates)")
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purpose = input("Select purpose (1-4): ")
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# Step 2: 期間の提案
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if purpose == "1": # Backtesting
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print("\nFor backtesting, we recommend:")
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print("- Short-term: Last 3 months")
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print("- Medium-term: Last 6 months")
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print("- Long-term: Last 1 year")
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elif purpose == "2": # Historical analysis
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print("\nFor historical analysis:")
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print("- Recent events: Last 1 month")
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print("- Quarterly analysis: Last 3 months")
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print("- Annual trends: Last 1 year")
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# Step 3: 期間選択
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print("\nHow would you like to specify the date range?")
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print("1. Use predefined period (1 week/1 month/3 months/6 months/1 year)")
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print("2. Specify exact dates")
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print("3. Relative dates (e.g., 'last 30 days')")
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choice = input("Select option (1-3): ")
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if choice == "1":
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return handle_predefined_period()
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elif choice == "2":
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return handle_exact_dates()
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else:
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return handle_relative_dates()
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```
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### 2. Reddit API制限を考慮した警告表示
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```python
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def validate_date_range(start_date, end_date):
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"""
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選択された期間の妥当性を確認し、必要に応じて警告
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"""
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days_diff = (end_date - start_date).days
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# 警告レベルの判定
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if days_diff > 365:
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print(f"\n⚠️ WARNING: Large date range ({days_diff} days)")
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print("This will result in:")
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print(f"- Approximately {days_diff * 5} API calls")
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print(f"- Estimated time: {days_diff * 0.5:.1f} minutes")
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print("- Reddit API may not return complete historical data beyond 1000 posts per subreddit")
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if not confirm("Do you want to continue with this large range?"):
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return False
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elif days_diff > 180:
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print(f"\n📊 Date range: {days_diff} days")
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print(f"- Estimated time: {days_diff * 0.5:.1f} minutes")
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print("- This is a reasonable range for comprehensive analysis")
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return True
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```
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### 3. 段階的な期間設定（推奨実装）
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```python
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def smart_date_range_selector():
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"""
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ユーザーの経験レベルに応じた期間設定
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"""
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print("\nLet's determine the best date range for your needs.")
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# Step 1: データ利用頻度の確認
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print("\nHow often will you run backtests?")
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print("1. Daily (active trading)")
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print("2. Weekly (regular monitoring)")
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print("3. Monthly (periodic review)")
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print("4. One-time analysis")
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frequency = input("Select frequency (1-4): ")
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# Step 2: 推奨期間の提示
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recommendations = {
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"1": {
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"initial": "1 month",
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"update": "daily",
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"reason": "Recent data is most relevant for active trading"
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},
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"2": {
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"initial": "3 months",
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"update": "weekly",
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"reason": "Balanced between data volume and relevance"
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},
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"3": {
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"initial": "6 months",
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"update": "monthly",
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"reason": "Good for trend analysis and strategy validation"
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},
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"4": {
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"initial": "1 year",
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"update": "as needed",
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"reason": "Comprehensive historical data for research"
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}
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}
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rec = recommendations[frequency]
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print(f"\n💡 Recommendation based on your usage:")
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print(f"- Initial fetch: {rec['initial']} of historical data")
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print(f"- Update schedule: {rec['update']}")
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print(f"- Reason: {rec['reason']}")
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# Step 3: カスタマイズオプション
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print("\nWould you like to:")
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print("1. Accept recommendation")
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print("2. Modify the period")
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print("3. See data availability preview")
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return handle_user_choice()
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```
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### 4. データ可用性のプレビュー
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```python
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def preview_data_availability(start_date, end_date, tickers=None):
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"""
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指定期間のデータ可用性をプレビュー表示
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"""
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print("\n📈 Data Availability Preview")
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print("="*50)
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# Reddit API制限の説明
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print("\nReddit API Limitations:")
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print("- Posts older than 6 months may be incomplete")
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print("- Maximum 1000 posts per subreddit search")
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print("- Rate limit: 60 requests per minute")
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# 期間別の推定データ量
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days = (end_date - start_date).days
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print(f"\nEstimated data volume for {days} days:")
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print(f"- Global news: ~{days * 100} posts from 5 subreddits")
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if tickers:
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print(f"- Company news for {len(tickers)} tickers:")
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for ticker in tickers[:5]: # 最初の5つを表示
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print(f" - {ticker}: ~{days * 20} posts")
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if len(tickers) > 5:
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print(f" - ... and {len(tickers)-5} more tickers")
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# 取得時間の見積もり
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total_requests = estimate_api_requests(days, tickers)
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estimated_time = (total_requests / 60) * 1.2 # 20%のバッファ
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print(f"\n⏱️ Estimated fetch time: {estimated_time:.1f} minutes")
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print(f"📊 Total API requests: ~{total_requests}")
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return True
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```
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### 5. 実装例：CLI統合
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```python
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# cli/commands/reddit.py
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@click.command()
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@click.option('--interactive/--no-interactive', default=True,
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help='Use interactive mode for date selection')
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def fetch_historical(interactive):
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"""Fetch historical Reddit data with smart date selection"""
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if interactive:
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# 対話形式で期間を決定
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date_range = smart_date_range_selector()
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# プレビュー表示
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if preview_data_availability(date_range.start, date_range.end):
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if click.confirm("Proceed with data fetch?"):
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fetch_reddit_data(date_range)
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else:
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# 非対話形式（自動実行用）
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fetch_reddit_data(get_default_date_range())
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```
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## 使用例
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### 初回セットアップ時
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```
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$ python -m cli.main reddit fetch-historical
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Reddit Historical Data Fetcher
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========================================
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What is the purpose of this data fetch?
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1. Backtesting preparation
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2. Historical analysis
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3. Initial data setup
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4. Gap filling (missing dates)
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Select purpose (1-4): 3
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For initial setup, we recommend starting with recent data.
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How much historical data do you need?
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1. Last 1 month (recommended for testing)
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2. Last 3 months (good for short-term analysis)
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3. Last 6 months (balanced approach)
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4. Last 1 year (comprehensive but time-consuming)
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5. Custom range
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Select option (1-5): 2
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📊 You selected: Last 3 months (2024-01-01 to 2024-03-31)
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Which tickers would you like to track?
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1. Top 10 most discussed (TSLA, AAPL, GME, AMC, NVDA, ...)
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2. S&P 500 leaders
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3. Custom list
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4. All available (not recommended)
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Select option (1-4): 1
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📈 Data Availability Preview
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==================================================
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Period: 2024-01-01 to 2024-03-31 (90 days)
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Tickers: TSLA, AAPL, GME, AMC, NVDA, MSFT, AMZN, META, GOOGL, SPY
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Estimated data volume:
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- Global news: ~9,000 posts from 5 subreddits
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- Company news: ~18,000 posts for 10 tickers
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⏱️ Estimated fetch time: 15.0 minutes
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📊 Total API requests: ~750
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Proceed with data fetch? [y/N]: y
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```
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この設計により、ユーザーは自分のニーズに合った期間を選択でき、同時にAPI制限やデータ量についても理解した上で実行できます。 |