leads.data_persistence.analyzer.processor

Module Contents

Classes

Processor

API

class leads.data_persistence.analyzer.processor.Processor(dataset: leads.data_persistence.core.CSVDataset)

Bases: object

Initialization

dataset() → leads.data_persistence.core.CSVDataset

bake() → None

Prepare the prerequisites for process().

static _hide_others(seq: Sequence[Any], limit: int) → str

baking_results() → tuple[str, str, str, str, str, str, str, str, str, str, str, str, str, str]

Get the results of the baking process. :return: the results in sentences

erase_unit_cache() → None

foreach(do: Callable[[dict[str, Any], int], None], skip_invalid_rows: bool = True, skip_gps_invalid_rows: bool = False) → None

process(lap_time_assertions: Sequence[float] | None = None, vehicle_hit_box: float = 3, min_lap_time: float = 30) → None

Split the laps. :param lap_time_assertions: the manually timed laps in seconds :param vehicle_hit_box: the vehicle hit box in meters :param min_lap_time: the minimum lap time in seconds :return:

suggest_on_lap(lap_index: int) → tuple[str, str]

num_laps() → int

results() → tuple[str, str]

Get the results of the processor. :return: the results in sentences

close() → None

draw_lap(lap_index: int = -1) → None

draw_comparison_of_laps(width: float = 0.3) → None