quantlab.dataset.massive.permaticker_bars.PermatickerTradeBarDataset#

class quantlab.dataset.massive.permaticker_bars.PermatickerTradeBarDataset(config, ticker_map=None)[source]#

Bases: PermatickerDataset

The one-minute Trade bars on the permaticker axis; see the module docstring.

Parameters:

configPermatickerTradeBarsConfig or MassiveTradeBarDataset: The config, or the Trade bar dataset with ticker_map beside it.
ticker_mapTickerMap, optional: The Ticker map, when config is the Trade bar dataset.

Examples

>>> bars = PermatickerTradeBarDataset(trade_bars, ticker_map)
>>> bars.panel("2024-11-27", "2024-11-30")["symbol"].values.tolist()
[101, 202, 303, 404, 505]

DEFAULT_RESAMPLE_HOW = {'buy_volume': 'sum', 'close': 'last', 'close_auction_price': 'last', 'close_auction_volume': 'sum', 'dollar_volume': 'sum', 'high': 'max', 'low': 'min', 'n_trades': 'sum', 'oddlot_volume': 'sum', 'offexchange_volume': 'sum', 'open': 'first', 'open_auction_price': 'first', 'open_auction_volume': 'sum', 'sell_volume': 'sum', 'volume': 'sum'}#: resample(freq) aggregates each variable as the Trade bars do.

SOURCE_CLS#: alias of MassiveTradeBarDataset

SOURCE_FIELD = 'trade_bars'#: The config field holding the dataset on the Massive ticker axis.

config_cls#

The config class used to rebuild this dataset from a saved config.

alias of PermatickerTradeBarsConfig

stored_through()[source]#

Return the last day the Trade bar store has converted, None without one.

Examples

With trade_bars the Trade bar store and ticker_map the Ticker map:

PermatickerTradeBarDataset(trade_bars, ticker_map).stored_through()
# datetime.date(2024, 11, 29)

property trade_bars#

The Trade bar dataset on the Massive ticker axis.

Examples

>>> PermatickerTradeBarDataset(trade_bars, ticker_map).trade_bars is trade_bars
True