CandleFeed

tradingstrategy.direct_feed.candle_feed.CandleFeed Python class in Trading Strategy framework.

class CandleFeed

Bases: object

Create candles for certain time frame for multiple pairs.

• Takes TradeFeed as input

• Generates candles based on this feed

• Can only generate candles of one timeframe

• May contain multiple pairs in one candle feed

__init__(pairs, timeframe)

Parameters:

• pairs (List[str]) –

  List of pairs this address contains.

  Symbolic names or addresses.

• freq – Pandas frequency string e.g. “1H”, “min”

• candle_offset –

• timeframe (Timeframe) –

Methods

__init__(pairs, timeframe)	param pairs:
apply_delta(delta[, initial_load, label_candles])	Add new candle data generated from the latest blockchain input.
get_candles_by_pair(pair)
get_last_block_number()	Get overall last block number for which we have valid data.
iterate_pairs()	Get candles for all pairs we are tracking.

__init__(pairs, timeframe)

Parameters:

• pairs (List[str]) –

  List of pairs this address contains.

  Symbolic names or addresses.

• freq – Pandas frequency string e.g. “1H”, “min”

• candle_offset –

• timeframe (Timeframe) –

apply_delta(delta, initial_load=False, label_candles=True)

Add new candle data generated from the latest blockchain input.

Parameters:

• delta (TradeDelta) – New trades coming in

• initial_load –

  This is not an incremental snapshot, but initial buffer fill.

  Ignore delta.start_ts and fill the candle buffer as long as we get data.

• label_candles –

  Create and update label column.

  Label column contains tooltips for the visual candle viewer. This must be done before candle data is grouped by pairs.

get_last_block_number()

Get overall last block number for which we have valid data.

Returns:

block number (inclusive)

Return type:

int

iterate_pairs()

Get candles for all pairs we are tracking.

Return type:

Iterable[DataFrame]