timeseries storage
This commit is contained in:
Dobromir Popov
parent
c1ad6cddd6
commit
4aefca2d6c
299
realtime.py
299
realtime.py
@ -52,16 +52,38 @@ class TradeTickStorage:
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def get_ticks_as_df(self) -> pd.DataFrame:
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"""Return ticks as a DataFrame"""
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if not self.ticks:
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logger.warning("No ticks available for DataFrame conversion")
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return pd.DataFrame()
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df = pd.DataFrame(self.ticks)
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if not df.empty:
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df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
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logger.debug(f"Converting timestamps for {len(df)} ticks")
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# Ensure timestamp column exists
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if 'timestamp' not in df.columns:
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logger.error("Tick data missing timestamp column")
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return pd.DataFrame()
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# Check timestamp datatype before conversion
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sample_ts = df['timestamp'].iloc[0] if len(df) > 0 else None
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logger.debug(f"Sample timestamp before conversion: {sample_ts}, type: {type(sample_ts)}")
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# Convert timestamps to datetime
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try:
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df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
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logger.debug(f"Timestamps converted to datetime successfully")
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if len(df) > 0:
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logger.debug(f"Sample converted timestamp: {df['timestamp'].iloc[0]}")
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except Exception as e:
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logger.error(f"Error converting timestamps: {str(e)}")
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import traceback
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logger.error(traceback.format_exc())
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return pd.DataFrame()
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return df
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def get_candles(self, interval_seconds: int = 1) -> pd.DataFrame:
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"""Convert ticks to OHLCV candles at specified interval"""
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if not self.ticks:
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logger.warning("No ticks available for candle formation")
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return pd.DataFrame()
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# Ensure ticks are up to date
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@ -70,28 +92,52 @@ class TradeTickStorage:
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# Convert to DataFrame
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df = self.get_ticks_as_df()
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if df.empty:
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logger.warning("Tick DataFrame is empty after conversion")
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return pd.DataFrame()
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# Use timestamp column for resampling
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df = df.set_index('timestamp')
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logger.info(f"Preparing to create candles from {len(df)} ticks")
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# Create interval string for resampling
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interval_str = f'{interval_seconds}S'
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# Resample to create OHLCV candles
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candles = df.resample(interval_str).agg({
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'price': ['first', 'max', 'min', 'last'],
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'volume': 'sum'
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})
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# Flatten MultiIndex columns
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candles.columns = ['open', 'high', 'low', 'close', 'volume']
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# Reset index to get timestamp as column
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candles = candles.reset_index()
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logger.debug(f"Generated {len(candles)} candles from {len(self.ticks)} ticks")
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return candles
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try:
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# Use timestamp column for resampling
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df = df.set_index('timestamp')
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# Create interval string for resampling - use 's' instead of deprecated 'S'
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interval_str = f'{interval_seconds}s'
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# Resample to create OHLCV candles
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logger.debug(f"Resampling with interval: {interval_str}")
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candles = df.resample(interval_str).agg({
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'price': ['first', 'max', 'min', 'last'],
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'volume': 'sum'
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})
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# Check if resampling produced any data
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if candles.empty:
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logger.warning("Resampling produced empty dataframe - check timestamp distribution")
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# Show timestamp ranges to diagnose potential resampling issues
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if not df.empty:
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min_time = df.index.min()
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max_time = df.index.max()
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logger.info(f"Tick timestamp range: {min_time} to {max_time}")
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return pd.DataFrame()
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# Flatten MultiIndex columns
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candles.columns = ['open', 'high', 'low', 'close', 'volume']
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# Reset index to get timestamp as column
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candles = candles.reset_index()
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# Ensure no NaN values
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candles = candles.dropna()
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logger.debug(f"Generated {len(candles)} candles from {len(self.ticks)} ticks")
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return candles
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except Exception as e:
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logger.error(f"Error in candle formation: {str(e)}")
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import traceback
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logger.error(traceback.format_exc())
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return pd.DataFrame()
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class CandlestickData:
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def __init__(self, max_length: int = 300):
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@ -508,51 +554,59 @@ class RealTimeChart:
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Input('interval-store', 'data')]
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)
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def update_chart(n, interval_data):
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interval = interval_data.get('interval', 1)
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fig = make_subplots(
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rows=2, cols=1,
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shared_xaxis=True,
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vertical_spacing=0.03,
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subplot_titles=(f'{self.symbol} Price ({interval}s)', 'Volume'),
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row_heights=[0.7, 0.3]
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)
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try:
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interval = interval_data.get('interval', 1)
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logger.info(f"Updating chart for {self.symbol} with interval {interval}s")
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fig = make_subplots(
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rows=2, cols=1,
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shared_xaxis=True,
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vertical_spacing=0.03,
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subplot_titles=(f'{self.symbol} Price ({interval}s)', 'Volume'),
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row_heights=[0.7, 0.3]
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)
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# Get candlesticks from tick storage
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df = self.tick_storage.get_candles(interval_seconds=interval)
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if not df.empty:
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# Add candlestick chart
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fig.add_trace(
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go.Candlestick(
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x=df['timestamp'],
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open=df['open'],
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high=df['high'],
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low=df['low'],
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close=df['close'],
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name='Price',
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increasing_line_color='#33CC33', # Green
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decreasing_line_color='#FF4136' # Red
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),
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row=1, col=1
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)
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# Get candlesticks from tick storage
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df = self.tick_storage.get_candles(interval_seconds=interval)
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# Add volume bars
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colors = ['#33CC33' if close >= open else '#FF4136'
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for close, open in zip(df['close'], df['open'])]
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# Debug information about the dataframe
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logger.info(f"Candles dataframe empty: {df.empty}, tick count: {len(self.tick_storage.ticks)}")
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fig.add_trace(
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go.Bar(
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x=df['timestamp'],
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y=df['volume'],
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name='Volume',
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marker_color=colors
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),
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row=2, col=1
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)
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# Add latest price line
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if len(df) > 0:
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if not df.empty and len(df) > 0:
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logger.info(f"Candles dataframe shape: {df.shape}")
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logger.info(f"Candles dataframe columns: {df.columns.tolist()}")
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logger.info(f"Candles dataframe first row: {df.iloc[0].to_dict() if len(df) > 0 else 'No rows'}")
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# Add candlestick chart
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fig.add_trace(
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go.Candlestick(
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x=df['timestamp'],
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open=df['open'],
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high=df['high'],
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low=df['low'],
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close=df['close'],
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name='Price',
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increasing_line_color='#33CC33', # Green
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decreasing_line_color='#FF4136' # Red
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),
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row=1, col=1
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)
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# Add volume bars
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colors = ['#33CC33' if close >= open else '#FF4136'
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for close, open in zip(df['close'], df['open'])]
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fig.add_trace(
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go.Bar(
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x=df['timestamp'],
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y=df['volume'],
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name='Volume',
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marker_color=colors
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),
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row=2, col=1
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)
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# Add latest price line and annotation
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latest_price = df['close'].iloc[-1]
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fig.add_shape(
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type="line",
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@ -564,7 +618,6 @@ class RealTimeChart:
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row=1, col=1
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)
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# Add price label
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fig.add_annotation(
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x=df['timestamp'].max(),
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y=latest_price,
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@ -574,31 +627,67 @@ class RealTimeChart:
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xshift=50,
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row=1, col=1
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)
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else:
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# If no data, add a text annotation to the chart
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logger.warning(f"No data to display for {self.symbol} - tick count: {len(self.tick_storage.ticks)}")
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if self.tick_storage.ticks:
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logger.info(f"Sample tick: {self.tick_storage.ticks[0]}")
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# Add a message to the empty chart
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fig.add_annotation(
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x=0.5, y=0.5,
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text=f"Waiting for {self.symbol} data...",
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showarrow=False,
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font=dict(size=20, color="white"),
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xref="paper", yref="paper"
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)
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# Update layout with improved styling
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fig.update_layout(
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title_text=f"{self.symbol} Real-Time Data ({interval}s candles)",
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title_x=0.5, # Center the title
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xaxis_rangeslider_visible=False,
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height=800,
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template='plotly_dark',
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paper_bgcolor='rgba(0,0,0,0)',
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plot_bgcolor='rgba(0,0,0,0)',
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font=dict(family="Arial, sans-serif", size=12, color="#2c3e50"),
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showlegend=True,
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legend=dict(
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yanchor="top",
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y=0.99,
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xanchor="left",
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x=0.01
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# Update layout with improved styling
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fig.update_layout(
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title_text=f"{self.symbol} Real-Time Data ({interval}s candles)",
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title_x=0.5, # Center the title
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xaxis_rangeslider_visible=False,
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height=800,
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template='plotly_dark',
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paper_bgcolor='rgba(0,0,0,0)',
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plot_bgcolor='rgba(0,0,0,0)',
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font=dict(family="Arial, sans-serif", size=12, color="#2c3e50"),
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showlegend=True,
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legend=dict(
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yanchor="top",
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y=0.99,
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xanchor="left",
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x=0.01
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)
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)
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)
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# Update axes styling
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fig.update_xaxes(showgrid=True, gridwidth=1, gridcolor='rgba(128,128,128,0.2)')
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fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='rgba(128,128,128,0.2)')
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# Update axes styling
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fig.update_xaxes(showgrid=True, gridwidth=1, gridcolor='rgba(128,128,128,0.2)')
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fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='rgba(128,128,128,0.2)')
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return fig
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return fig
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except Exception as e:
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logger.error(f"Error updating chart: {str(e)}")
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import traceback
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logger.error(traceback.format_exc())
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# Create a minimal figure with error message
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fig = go.Figure()
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fig.add_annotation(
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x=0.5, y=0.5,
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text=f"Error updating chart: {str(e)}",
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showarrow=False,
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font=dict(size=14, color="red"),
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xref="paper", yref="paper"
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)
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fig.update_layout(
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height=800,
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template='plotly_dark',
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paper_bgcolor='rgba(0,0,0,0)',
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plot_bgcolor='rgba(0,0,0,0)'
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)
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return fig
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async def start_websocket(self):
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ws = ExchangeWebSocket(self.symbol)
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@ -610,6 +699,10 @@ class RealTimeChart:
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continue
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try:
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logger.info(f"WebSocket connected for {self.symbol}, beginning data collection")
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tick_count = 0
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last_tick_count_log = time.time()
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while True:
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if not ws.running:
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logger.warning("WebSocket not running, breaking loop")
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@ -627,6 +720,7 @@ class RealTimeChart:
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'high': data['high'],
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'low': data['low']
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}
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logger.debug(f"Received kline data: {data}")
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else:
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# Use trade data
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trade_data = {
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@ -634,13 +728,25 @@ class RealTimeChart:
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'price': data['price'],
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'volume': data['volume']
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}
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logger.debug(f"Updating candlestick with data: {trade_data}")
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# Store raw tick in the tick storage
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self.tick_storage.add_tick(trade_data)
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tick_count += 1
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# Also update the old candlestick data for backward compatibility
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self.candlestick_data.update_from_trade(trade_data)
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# Log tick counts periodically
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current_time = time.time()
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if current_time - last_tick_count_log >= 10: # Log every 10 seconds
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logger.info(f"{self.symbol}: Collected {tick_count} ticks in last {current_time - last_tick_count_log:.1f}s, total: {len(self.tick_storage.ticks)}")
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last_tick_count_log = current_time
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tick_count = 0
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# Check if ticks are being converted to candles
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if len(self.tick_storage.ticks) > 0:
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sample_df = self.tick_storage.get_candles(interval_seconds=1)
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logger.info(f"{self.symbol}: Sample candle count: {len(sample_df)}")
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await asyncio.sleep(0.01)
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except Exception as e:
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@ -652,8 +758,23 @@ class RealTimeChart:
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await asyncio.sleep(5)
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def run(self, host='localhost', port=8050):
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logger.info(f"Starting Dash server on {host}:{port}")
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self.app.run(debug=False, host=host, port=port)
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try:
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logger.info(f"Starting Dash server for {self.symbol} on {host}:{port}")
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self.app.run(debug=False, host=host, port=port)
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except Exception as e:
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logger.error(f"Error running Dash server on port {port}: {str(e)}")
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# Try an alternative port if the primary one is in use
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if "Address already in use" in str(e):
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alt_port = port + 100
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logger.warning(f"Port {port} is busy, trying alternative port {alt_port}")
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try:
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self.app.run(debug=False, host=host, port=alt_port)
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except Exception as alt_e:
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logger.error(f"Error running Dash server on alternative port {alt_port}: {str(alt_e)}")
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else:
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# Re-raise other exceptions
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raise
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async def main():
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symbols = ["ETH/USDT", "BTC/USDT"]
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@ -672,10 +793,12 @@ async def main():
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server_threads = []
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for i, chart in enumerate(charts):
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port = 8050 + i # Use different ports for each chart
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thread = Thread(target=lambda c=chart, p=8050+i: c.run(port=p)) # Fix lambda capture
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logger.info(f"Starting chart for {chart.symbol} on port {port}")
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thread = Thread(target=lambda c=chart, p=port: c.run(port=p)) # Ensure correct port is passed
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thread.daemon = True
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thread.start()
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server_threads.append(thread)
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logger.info(f"Thread started for {chart.symbol} on port {port}")
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try:
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# Keep the main task running
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