Source code for tradeexecutor.utils.summarydataframe

"""Summary table dataframe helpers.

You can annotate the format of different values.
import datetime
import enum
from dataclasses import dataclass

import pandas as pd

[docs]class Format(enum.Enum): """Format different summary value cells.""" integer = "int" percent = "percent" dollar = "dollar" duration_days_hours = "duration_days_hours" duration_hours_minutes = "duration_hours_minutes" num_bars = "num_bars" decimal = "decimal" #: Value cannot be calculated, e.g division by zero missing = "missing"
FORMATTERS = { Format.integer: "{v:.0f}", Format.percent: "{v:.2%}", Format.dollar: "${v:,.2f}", Format.duration_days_hours: "{days} days {hours} hours", Format.duration_hours_minutes: "{hours} hours {minutes} minutes", Format.num_bars: "{v:.0f} bars", Format.missing: "-", Format.decimal: "{v:.2f}" }
[docs]@dataclass(slots=True) class Value: v: object format: Format def __str__(self): return format_value(self)
[docs]def as_dollar(v) -> Value: """Format value as US dollars""" return Value(v, Format.dollar)
[docs]def as_integer(v)-> Value: """Format value as an integer""" return Value(v, Format.integer)
[docs]def as_percent(v) -> Value: """Format value as a percent""" return Value(v, Format.percent)
[docs]def as_duration(v: datetime.timedelta) -> Value: """Format value as a duration""" if v.days > 0: return Value(v, Format.duration_days_hours) else: return Value(v, Format.duration_hours_minutes)
[docs]def as_bars(v: float) -> Value: """Format value as number of bars. Rounds down so we only use the number of fully completed bars.""" v = int(v) return Value(v, Format.num_bars)
[docs]def as_missing() -> Value: """Format a missing value e.g. because of division by zero""" return Value(None, Format.missing)
[docs]def as_decimal(v: float) -> Value: """Format a decimal value""" return Value(v, Format.decimal)
[docs]def format_value(v_instance: Value) -> str: """Format a single value :param v_instance: A :py:class:`Value` instance :return: A formatted string """ assert isinstance(v_instance, Value), f"Expected Value instance, got {v_instance}" formatter = FORMATTERS[v_instance.format] if v_instance.v is not None: # TODO: Remove the hack if v_instance.format == Format.num_bars: return formatter.format(v=v_instance.v) if isinstance(v_instance.v, datetime.timedelta): return formatter.format(days=v_instance.v.days, hours=v_instance.v.seconds // 3600, minutes=(v_instance.v.seconds // 60) % 60) else: return formatter.format(v=float(v_instance.v)) else: # missing values return FORMATTERS[Format.missing].format(v=v_instance.v)
[docs]def format_values(values: list[Value]) -> list[str]: """Format a list of values :param values: A list of :py:class:`Value` instances :return: A list of formatted strings """ return [format_value(v) for v in values]
[docs]def create_summary_table(data: dict, column_names: list[str] | str | None = None, index_name: str | None = None) -> pd.DataFrame: """Create a summary table from a human readable data. * Keys are human readable labels * Values are instances of :py:class:`Value` TODO: If column_names is not provided, we get column header "zero" that needs to be hidden. :param data: Human readable data in the form of a dict :param column_names: Column names for the dataframe. If None, no column names are used. :param index_name: Name of the index column. If None, no index name is used. :return: A styled pandas dataframe """ formatted_data = {} counter = 0 list_length = 0 for k, v in data.items(): if isinstance(v, Value): formatted_data[k] = format_value(v) elif isinstance(v, list): if counter == 0: list_length = len(v) else: assert len(v) == list_length, f"If one value in the dict is a list, all values must be lists of the same length. Expected list of length {list_length}, got {v}" formatted_data[k] = format_values(v) counter += 1 df = pd.DataFrame.from_dict(formatted_data, orient="index") if column_names is not None: if isinstance(column_names, str): column_names = [column_names] df.columns = column_names if index_name is not None: = index_name #"index", names=True)"columns", names=False) #[ {'selector': 'thead', 'props': [('display', 'none')]} ]) return df