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# Market Data Access
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Historical and real-time market data for stocks and cryptocurrencies including bars, trades, quotes, snapshots, and news. Supports multiple data feeds and provides pandas DataFrame integration for analysis workflows.
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## Capabilities
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### Historical Bars
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Retrieve historical price bars (OHLCV data) with customizable time frames and data feeds.
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```python { .api }
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def get_bars(
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    symbol: Union[str, List[str]],
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    timeframe: TimeFrame,
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    start: str,
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    end: str,
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    adjustment: str = "raw",
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    limit: int = None,
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    feed: str = None,
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    asof: str = None,
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    sort: Sort = None
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) -> BarsV2:
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    """Get historical bars for a symbol."""
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def get_bars_iter(
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    symbol: Union[str, List[str]],
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    timeframe: TimeFrame,
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    start: str,
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    end: str,
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    adjustment: str = "raw",
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    limit: int = None,
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    feed: str = None,
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    asof: str = None,
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    sort: Sort = None,
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    raw: bool = False
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) -> Iterator[Union[BarV2, dict]]:
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    """Get historical bars as an iterator."""
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```
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**Usage Examples:**
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```python
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from alpaca_trade_api import TimeFrame
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# Get daily bars for the last month
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bars = api.get_bars(
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    'AAPL', 
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    TimeFrame.Day,
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    '2023-01-01',
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    '2023-01-31'
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)
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# Convert to pandas DataFrame
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df = bars.df
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print(f"Retrieved {len(df)} bars")
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print(df.head())
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# Get minute bars with iterator for large datasets
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for bar in api.get_bars_iter('TSLA', TimeFrame.Minute, '2023-01-01', '2023-01-02'):
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    print(f"{bar.timestamp}: O={bar.open}, H={bar.high}, L={bar.low}, C={bar.close}, V={bar.volume}")
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```
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### Historical Trades
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Access individual trade execution data with detailed trade information.
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```python { .api }
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def get_trades(
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    symbol: Union[str, List[str]],
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    start: str,
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    end: str,
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    limit: int = None,
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    feed: str = None,
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    asof: str = None,
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    sort: Sort = None
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) -> TradesV2:
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    """Get historical trades for a symbol."""
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def get_trades_iter(
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    symbol: Union[str, List[str]],
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    start: str,
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    end: str,
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    limit: int = None,
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    feed: str = None,
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    asof: str = None,
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    sort: Sort = None,
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    raw: bool = False
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) -> Iterator[Union[TradeV2, dict]]:
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    """Get historical trades as an iterator."""
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```
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**Usage Examples:**
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```python
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# Get trades for a specific day
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trades = api.get_trades('AAPL', '2023-01-15', '2023-01-16')
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df = trades.df
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print(f"Total trades: {len(df)}")
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print(f"Volume weighted average price: {(df['price'] * df['size']).sum() / df['size'].sum()}")
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# Process trades with iterator
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total_volume = 0
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for trade in api.get_trades_iter('TSLA', '2023-01-15T09:30:00', '2023-01-15T16:00:00'):
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    total_volume += trade.size
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    if trade.price > 200:
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        print(f"Large trade: {trade.size} shares at ${trade.price}")
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```
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### Historical Quotes
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Retrieve bid/ask quote data for market analysis and spread calculations.
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```python { .api }
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def get_quotes(
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    symbol: Union[str, List[str]],
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    start: str,
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    end: str,
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    limit: int = None,
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    feed: str = None,
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    asof: str = None,
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    sort: Sort = None
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) -> QuotesV2:
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    """Get historical quotes for a symbol."""
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def get_quotes_iter(
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    symbol: Union[str, List[str]],
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    start: str,
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    end: str,
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    limit: int = None,
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    feed: str = None,
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    asof: str = None,
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    sort: Sort = None,
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    raw: bool = False
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) -> Iterator[Union[QuoteV2, dict]]:
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    """Get historical quotes as an iterator."""
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```
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**Usage Examples:**
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```python
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# Get quotes and analyze bid-ask spreads
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quotes = api.get_quotes('AAPL', '2023-01-15T09:30:00', '2023-01-15T16:00:00')
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df = quotes.df
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df['spread'] = df['ask_price'] - df['bid_price']
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df['spread_bps'] = (df['spread'] / df['bid_price']) * 10000
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print(f"Average spread: {df['spread_bps'].mean():.2f} basis points")
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```
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### Latest Market Data
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Get the most recent market data for real-time analysis and decision making.
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```python { .api }
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def get_latest_bar(symbol: str, feed: str = None) -> BarV2:
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    """Get the latest bar for a symbol."""
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def get_latest_bars(symbols: List[str], feed: str = None) -> LatestBarsV2:
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    """Get latest bars for multiple symbols."""
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def get_latest_trade(symbol: str, feed: str = None) -> TradeV2:
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    """Get the latest trade for a symbol."""  
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def get_latest_trades(symbols: List[str], feed: str = None) -> LatestTradesV2:
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    """Get latest trades for multiple symbols."""
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def get_latest_quote(symbol: str, feed: str = None) -> QuoteV2:
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    """Get the latest quote for a symbol."""
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def get_latest_quotes(symbols: List[str], feed: str = None) -> LatestQuotesV2:
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    """Get latest quotes for multiple symbols."""
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```
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**Usage Examples:**
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```python
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# Get latest data for multiple symbols
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symbols = ['AAPL', 'TSLA', 'GOOGL', 'MSFT']
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latest_bars = api.get_latest_bars(symbols)
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for symbol, bar in latest_bars.items():
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    print(f"{symbol}: ${bar.close} (Volume: {bar.volume:,})")
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# Get current quote data
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quote = api.get_latest_quote('AAPL')
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print(f"AAPL Bid: ${quote.bid_price} x {quote.bid_size}")
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print(f"AAPL Ask: ${quote.ask_price} x {quote.ask_size}")
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print(f"Spread: ${quote.ask_price - quote.bid_price:.2f}")
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```
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### Market Snapshots
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Comprehensive market snapshots containing latest trade, quote, and bar data in a single request.
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```python { .api }
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def get_snapshot(symbol: str, feed: str = None) -> SnapshotV2:
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    """Get a market snapshot for a symbol."""
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def get_snapshots(symbols: List[str], feed: str = None) -> SnapshotsV2:
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    """Get market snapshots for multiple symbols."""
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```
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**Usage Examples:**
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```python
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# Get comprehensive market data
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snapshot = api.get_snapshot('AAPL')
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print(f"Latest Trade: ${snapshot.latest_trade.price} at {snapshot.latest_trade.timestamp}")
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print(f"Latest Quote: ${snapshot.latest_quote.bid_price} x ${snapshot.latest_quote.ask_price}")
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print(f"Daily Bar: O=${snapshot.daily_bar.open} H=${snapshot.daily_bar.high} L=${snapshot.daily_bar.low} C=${snapshot.daily_bar.close}")
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# Get snapshots for portfolio monitoring
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portfolio_symbols = ['AAPL', 'TSLA', 'GOOGL']
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snapshots = api.get_snapshots(portfolio_symbols)
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for symbol, snapshot in snapshots.items():
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    day_change = snapshot.daily_bar.close - snapshot.prev_daily_bar.close
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    day_change_pct = (day_change / snapshot.prev_daily_bar.close) * 100
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    print(f"{symbol}: ${snapshot.daily_bar.close} ({day_change_pct:+.2f}%)")
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```
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### News Data
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Access financial news articles with symbol filtering and content options.
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```python { .api }
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def get_news(
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    symbol: Union[str, List[str]] = None,
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    start: str = None,
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    end: str = None,
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    limit: int = 10,
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    sort: Sort = Sort.Desc,
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    include_content: bool = False,
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    exclude_contentless: bool = False
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) -> NewsListV2:
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    """Get news articles."""
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def get_news_iter(
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    symbol: Union[str, List[str]] = None,
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    start: str = None,
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    end: str = None,
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    limit: int = 10,
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    sort: Sort = Sort.Desc,
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    include_content: bool = False,
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    exclude_contentless: bool = False,
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    raw: bool = False
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) -> Iterator[Union[NewsV2, dict]]:
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    """Get news articles as an iterator."""
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```
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**Usage Examples:**
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```python
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# Get recent news for a symbol
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news = api.get_news('AAPL', limit=10)
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for article in news:
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    print(f"{article.created_at}: {article.headline}")
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    print(f"Summary: {article.summary}")
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    print(f"URL: {article.url}")
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    print("---")
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# Get market-wide news
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general_news = api.get_news(limit=20, sort='desc')
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for article in general_news:
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    print(f"{article.headline} (Symbols: {', '.join(article.symbols)})")
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```
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### Market Calendar and Clock
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Access market schedule information and current market status.
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```python { .api }
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def get_clock() -> Clock:
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    """Get current market clock information."""
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def get_calendar(start: str = None, end: str = None) -> List[Calendar]:
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    """Get market calendar information."""
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```
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**Usage Examples:**
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```python
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# Check market status
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clock = api.get_clock()
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print(f"Market is {'open' if clock.is_open else 'closed'}")
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print(f"Next open: {clock.next_open}")
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print(f"Next close: {clock.next_close}")
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# Get market schedule
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calendar = api.get_calendar('2023-01-01', '2023-01-31')
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for day in calendar:
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    print(f"{day.date}: Open={day.open}, Close={day.close}")
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```
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## Types
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```python { .api }
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class BarV2:
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    @property
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    def symbol(self) -> str: ...
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    @property
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    def timestamp(self) -> pd.Timestamp: ...
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    @property
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    def open(self) -> float: ...
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    @property
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    def high(self) -> float: ...
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    @property
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    def low(self) -> float: ...
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    @property
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    def close(self) -> float: ...
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    @property
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    def volume(self) -> int: ...
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    @property
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    def trade_count(self) -> int: ...
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    @property
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    def vwap(self) -> float: ...
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class BarsV2:
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    @property
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    def df(self) -> pd.DataFrame: ...
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    def __iter__(self): ...
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    def __len__(self) -> int: ...
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class TradesV2:
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    @property
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    def df(self) -> pd.DataFrame: ...
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    def __iter__(self): ...
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    def __len__(self) -> int: ...
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class QuotesV2:
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    @property
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    def df(self) -> pd.DataFrame: ...
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    def __iter__(self): ...
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    def __len__(self) -> int: ...
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class NewsListV2:
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    def __iter__(self): ...
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    def __len__(self) -> int: ...
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class LatestBarsV2:
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    def items(self): ...
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    def __getitem__(self, symbol: str) -> BarV2: ...
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class LatestTradesV2:
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    def items(self): ...
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    def __getitem__(self, symbol: str) -> TradeV2: ...
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class LatestQuotesV2:
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    def items(self): ...
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    def __getitem__(self, symbol: str) -> QuoteV2: ...
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class SnapshotsV2:
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    def items(self): ...
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    def __getitem__(self, symbol: str) -> SnapshotV2: ...
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class TradeV2:
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    @property
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    def symbol(self) -> str: ...
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    @property
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    def timestamp(self) -> pd.Timestamp: ...
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    @property
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    def price(self) -> float: ...
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    @property
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    def size(self) -> int: ...
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    @property
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    def exchange(self) -> str: ...
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    @property
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    def conditions(self) -> List[str]: ...
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class QuoteV2:
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    @property
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    def symbol(self) -> str: ...
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    @property
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    def timestamp(self) -> pd.Timestamp: ...
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    @property
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    def bid_price(self) -> float: ...
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    @property
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    def bid_size(self) -> int: ...
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    @property
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    def ask_price(self) -> float: ...
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    @property
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    def ask_size(self) -> int: ...
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    @property
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    def bid_exchange(self) -> str: ...
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    @property
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    def ask_exchange(self) -> str: ...
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class SnapshotV2:
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    @property
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    def symbol(self) -> str: ...
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    @property
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    def latest_trade(self) -> TradeV2: ...
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    @property
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    def latest_quote(self) -> QuoteV2: ...
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    @property
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    def minute_bar(self) -> BarV2: ...
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    @property
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    def daily_bar(self) -> BarV2: ...
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    @property
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    def prev_daily_bar(self) -> BarV2: ...
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class NewsV2:
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    @property
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    def id(self) -> str: ...
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    @property
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    def headline(self) -> str: ...
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    @property
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    def summary(self) -> str: ...
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    @property
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    def content(self) -> str: ...
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    @property
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    def created_at(self) -> pd.Timestamp: ...
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    @property
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    def updated_at(self) -> pd.Timestamp: ...
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    @property
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    def author(self) -> str: ...
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    @property
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    def symbols(self) -> List[str]: ...
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    @property
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    def url(self) -> str: ...
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class Clock:
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    @property
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    def timestamp(self) -> pd.Timestamp: ...
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    @property
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    def is_open(self) -> bool: ...
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    @property
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    def next_open(self) -> pd.Timestamp: ...
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    @property
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    def next_close(self) -> pd.Timestamp: ...
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class Calendar:
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    @property
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    def date(self) -> str: ...
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    @property
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    def open(self) -> str: ...
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    @property
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    def close(self) -> str: ...
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```