PyFacts/fincal/core.py

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from __future__ import annotations
import datetime
import inspect
import warnings
from collections import UserList
from dataclasses import dataclass
from numbers import Number
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from typing import Any, Callable, Iterable, List, Literal, Mapping, Sequence, Type
from dateutil.relativedelta import relativedelta
from .utils import FincalOptions, _parse_date, _preprocess_timeseries
@dataclass(frozen=True)
class Frequency:
name: str
freq_type: str
value: int
days: int
symbol: str
def date_parser(*pos):
"""Decorator to parse dates in any function
Accepts the 0-indexed position of the parameter for which date parsing needs to be done.
Works even if function is used with keyword arguments while not maintaining parameter order.
Example:
--------
>>> @date_parser(2, 3)
>>> def calculate_difference(diff_units='days', return_type='int', date1, date2):
... diff = date2 - date1
... if return_type == 'int':
... return diff.days
... return diff
...
>>> calculate_difference(date1='2019-01-01', date2='2020-01-01')
datetime.timedelta(365)
Each of the dates is automatically parsed into a datetime.datetime object from string.
"""
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def parse_dates(func):
def wrapper_func(*args, **kwargs):
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date_format: str = kwargs.get("date_format", None)
args: list = list(args)
sig: inspect.Signature = inspect.signature(func)
params: list = [i[0] for i in sig.parameters.items()]
for j in pos:
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kwarg: str = params[j]
date = kwargs.get(kwarg, None)
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in_args: bool = False
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if date is None:
try:
date = args[j]
except IndexError:
pass
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in_args = True
if date is None:
continue
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parsed_date: datetime.datetime = _parse_date(date, date_format)
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if not in_args:
kwargs[kwarg] = parsed_date
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else:
args[j] = parsed_date
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return func(*args, **kwargs)
return wrapper_func
return parse_dates
class AllFrequencies:
D = Frequency("daily", "days", 1, 1, "D")
W = Frequency("weekly", "days", 7, 7, "W")
M = Frequency("monthly", "months", 1, 30, "M")
Q = Frequency("quarterly", "months", 3, 91, "Q")
H = Frequency("half-yearly", "months", 6, 182, "H")
Y = Frequency("annual", "years", 1, 365, "Y")
class _IndexSlicer:
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"""Class to create a slice using iloc in TimeSeriesCore"""
def __init__(self, parent_obj: object):
self.parent = parent_obj
def __getitem__(self, n):
if isinstance(n, int):
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keys: list = [self.parent.dates[n]]
else:
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keys: list = self.parent.dates[n]
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item = [(key, self.parent.data[key]) for key in keys]
if len(item) == 1:
return item[0]
return self.parent.__class__(item, self.parent.frequency.symbol)
def __setitem__(self, key, value):
raise NotImplementedError(
"iloc cannot be used for setting a value as value will always be inserted in order of date"
)
class Series(UserList):
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"""Container for a series of objects, all objects must be of the same type"""
def __init__(
self,
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data: Sequence,
dtype: Literal["date", "number", "bool"] = None,
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date_format: str = None,
):
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types_dict: dict = {
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"date": datetime.datetime,
"datetime": datetime.datetime,
"datetime.datetime": datetime.datetime,
"float": float,
"int": float,
"number": float,
"bool": bool,
"Decimal": bool,
}
if not isinstance(data, Sequence):
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raise TypeError("Series object can only be created using Sequence types")
if dtype is None:
if isinstance(data[0], (Number, datetime.datetime, datetime.date, bool)):
dtype = data[0].__class__.__name__.lower()
if dtype not in types_dict.keys():
raise ValueError("Unsupported value for data type")
if dtype in ["date", "datetime", "datetime.datetime"]:
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data = [_parse_date(i, date_format) for i in data]
else:
func: Callable = types_dict[dtype]
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data: list = [func(i) for i in data]
self.dtype: Type = types_dict[dtype]
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self.data: Sequence = data
def __repr__(self):
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return f"{self.__class__.__name__}({self.data}, data_type='{self.dtype.__name__}')"
def __getitem__(self, i):
if isinstance(i, slice):
return self.__class__(self.data[i], str(self.dtype.__name__))
else:
return self.data[i]
def _comparison_validator(self, other):
"""Validates other before making comparison"""
if isinstance(other, (str, datetime.datetime, datetime.date)):
other = _parse_date(other)
return other
if self.dtype == bool:
raise TypeError("Comparison operation not supported for boolean series")
elif isinstance(other, Series):
if len(self) != len(other):
raise ValueError("Length of Series must be same for comparison")
elif (self.dtype != float and isinstance(other, Number)) or not isinstance(other, self.dtype):
raise Exception(f"Cannot compare type {self.dtype.__name__} to {type(other).__name__}")
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return other
def __gt__(self, other):
other = self._comparison_validator(other)
if isinstance(other, Series):
return Series([j > other[i] for i, j in enumerate(self)], "bool")
return Series([i > other for i in self.data], "bool")
def __ge__(self, other):
other = self._comparison_validator(other)
if isinstance(other, Series):
return Series([j >= other[i] for i, j in enumerate(self)], "bool")
return Series([i >= other for i in self.data], "bool")
def __lt__(self, other):
other = self._comparison_validator(other)
if isinstance(other, Series):
return Series([j < other[i] for i, j in enumerate(self)], "bool")
return Series([i < other for i in self.data], "bool")
def __le__(self, other):
other = self._comparison_validator(other)
if isinstance(other, Series):
return Series([j <= other[i] for i, j in enumerate(self)], "bool")
return Series([i <= other for i in self.data], "bool")
def __eq__(self, other):
other = self._comparison_validator(other)
if isinstance(other, Series):
return Series([j == other[i] for i, j in enumerate(self)], "bool")
return Series([i == other for i in self.data], "bool")
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def __ne__(self, other):
other = self._comparison_validator(other)
if isinstance(other, Series):
return Series([j != other[i] for i, j in enumerate(self)], "bool")
return Series([i == other for i in self.data], "bool")
def _math_validator(self, other):
if not isinstance(other, (Series, Number, datetime.timedelta, relativedelta, datetime.datetime, datetime.date)):
return NotImplemented
if isinstance(other, Series):
if len(self) != len(other):
raise ValueError("Arithmatic operations cannot be performed on objects of different lengths.")
if self.dtype == bool or other.dtype == bool:
raise TypeError("Arithmatic operations cannot be performed on boolean series.")
if self.dtype == float and not other.dtype == float:
raise TypeError(
"Arithmatic operation cannot be performed between "
f"'{self.dtype.__name__}' and '{other.dtype.__name__}'"
)
if self.dtype == datetime.datetime:
raise TypeError(
"Arithmatic operation cannot be performed between '"
f"'{self.dtype.__name__}' and '{other.dtype.__name__}'"
)
return
elif self.dtype == float and not isinstance(other, Number):
raise TypeError(
f"Arithmatic operation cannot be performed between '{self.dtype}' and '{other.__class__.__name__}'"
)
elif self.dtype == datetime.datetime and not isinstance(other, (datetime.timedelta, relativedelta)):
raise TypeError(
f"Arithmatic operation cannot be performed between '{self.dtype.__name__}' and "
f"'{other.__class__.__name__}'\nHint: Try using timedelta or relativedelta objects."
)
return other
def __add__(self, other):
if self._math_validator(other) == NotImplemented:
return NotImplemented
if isinstance(other, Series):
return self.__class__([j + other[i] for i, j in enumerate(self)], self.dtype.__name__)
if isinstance(other, (Number, datetime.timedelta, relativedelta)):
return self.__class__([i + other for i in self], self.dtype.__name__)
@Mapping.register
class TimeSeriesCore:
"""Defines the core building blocks of a TimeSeries object"""
def __init__(
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self,
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ts_data: List[Iterable] | Mapping,
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frequency: Literal["D", "W", "M", "Q", "H", "Y"],
date_format: str = "%Y-%m-%d",
):
"""Instantiate a TimeSeriesCore object
Parameters
----------
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ts_data : List[Iterable] | Mapping
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Time Series data in the form of list of tuples or dictionary.
The first element of each tuple should be a date and second element should be a value.
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In case of dictionary, the key should be the date.
frequency : str
The frequency of the time series.
Valid values are {D, W, M, Q, H, Y}
date_format : str, optional, default "%Y-%m-%d"
Specify the format of the date
Required only if the first argument of tuples is a string. Otherwise ignored.
"""
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ts_data = _preprocess_timeseries(ts_data, date_format=date_format)
self.data = dict(ts_data)
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if len(self.data) != len(ts_data):
warnings.warn("The input data contains duplicate dates which have been ignored.")
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self.frequency: Frequency = getattr(AllFrequencies, frequency)
self.iter_num: int = -1
self._dates: list = None
self._values: list = None
self._start_date: datetime.datetime = None
self._end_date: datetime.datetime = None
@property
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def dates(self) -> Series:
"""Get a list of all the dates in the TimeSeries object"""
if self._dates is None or len(self._dates) != len(self.data):
self._dates = list(self.data.keys())
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return Series(self._dates, "date")
@property
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def values(self) -> Series:
"""Get a list of all the Values in the TimeSeries object"""
if self._values is None or len(self._values) != len(self.data):
self._values = list(self.data.values())
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return Series(self._values, "number")
@property
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def start_date(self) -> datetime.datetime:
"""The first date in the TimeSeries object"""
return self.dates[0]
@property
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def end_date(self) -> datetime.datetime:
"""The last date in the TimeSeries object"""
return self.dates[-1]
def _get_printable_slice(self, n: int):
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"""Helper function for __repr__ and __str__
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Returns a slice of the dataframe from beginning and end.
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"""
printable = {}
iter_f = iter(self.data)
first_n = [next(iter_f) for i in range(n // 2)]
iter_b = reversed(self.data)
last_n = [next(iter_b) for i in range(n // 2)]
last_n.sort()
printable["start"] = [str((i, self.data[i])) for i in first_n]
printable["end"] = [str((i, self.data[i])) for i in last_n]
return printable
def __repr__(self):
if len(self.data) > 6:
printable = self._get_printable_slice(6)
printable_str = "{}([{}\n\t ...\n\t {}], frequency={})".format(
self.__class__.__name__,
",\n\t ".join(printable["start"]),
",\n\t ".join(printable["end"]),
repr(self.frequency.symbol),
)
else:
printable_str = "{}([{}], frequency={})".format(
self.__class__.__name__,
",\n\t".join([str(i) for i in self.data.items()]),
repr(self.frequency.symbol),
)
return printable_str
def __str__(self):
if len(self.data) > 6:
printable = self._get_printable_slice(6)
printable_str = "[{}\n ...\n {}]".format(
",\n ".join(printable["start"]),
",\n ".join(printable["end"]),
)
else:
printable_str = "[{}]".format(",\n ".join([str(i) for i in self.data.items()]))
return printable_str
@date_parser(1)
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def _get_item_from_date(self, date: str | datetime.datetime):
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"""Helper function to retrieve item using a date"""
return self.get(date, raise_error=True)
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def _get_item_from_key(self, key: str | datetime.datetime):
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"""Helper function to implement special keys"""
if isinstance(key, int):
raise KeyError(f"{key}. \nHint: use .iloc[{key}] for index based slicing.")
if key in ["dates", "values"]:
return getattr(self, key)
return self._get_item_from_date(key)
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def _get_item_from_list(self, date_list: Sequence[str | datetime.datetime]):
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"""Helper function to retrieve items using a list"""
data_to_return = [self._get_item_from_key(key) for key in date_list]
return self.__class__(data_to_return, frequency=self.frequency.symbol)
def _get_item_from_series(self, series: Series):
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"""Helper function to retrieve item using a Series object
A Series of type bool of equal length to the time series can be used.
A Series of dates can be used to filter out a set of dates.
"""
if series.dtype == bool:
if len(series) != len(self.dates):
raise ValueError(f"Length of Series: {len(series)} did not match length of object: {len(self.dates)}")
dates_to_return = [self.dates[i] for i, j in enumerate(series) if j]
elif series.dtype == datetime.datetime:
dates_to_return = list(series)
else:
raise TypeError(f"Cannot slice {self.__class__.__name__} using a Series of {series.dtype.__name__}")
return self._get_item_from_list(dates_to_return)
def __getitem__(self, key):
if isinstance(key, (int, str, datetime.datetime, datetime.date)):
return self._get_item_from_key(key)
if isinstance(key, Series):
return self._get_item_from_series(key)
if isinstance(key, Sequence):
return self._get_item_from_list(key)
raise TypeError(f"Invalid type {repr(type(key).__name__)} for slicing.")
@date_parser(1)
def __setitem__(self, key: str | datetime.datetime, value: Number) -> None:
if not isinstance(value, Number):
raise TypeError("Only numerical values can be stored in TimeSeries")
if key in self.data:
self.data[key] = float(value)
else:
self.data.update({key: float(value)})
self.data = dict(sorted(self.data.items()))
@date_parser(1)
def __delitem__(self, key):
del self.data[key]
def _comparison_validator(self, other):
"""Validates the data before comparison is performed"""
if not isinstance(other, (Number, Series, TimeSeriesCore)):
raise TypeError(
f"Comparison cannot be performed between '{self.__class__.__name__}' and '{other.__class__.__name__}'"
)
if isinstance(other, TimeSeriesCore):
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if any(self.dates != other.dates):
raise ValueError(
"Only objects with same set of dates can be compared.\n"
"Hint: use TimeSeries.sync() method to sync dates of two TimeSeries objects."
)
if isinstance(other, Series):
if other.dtype != float:
raise TypeError("Only Series of type float can be used for comparison")
if len(self) != len(other):
raise ValueError("Length of series does not match length of object")
def __gt__(self, other):
self._comparison_validator(other)
if isinstance(other, Number):
data = {k: v > other for k, v in self.data.items()}
if isinstance(other, TimeSeriesCore):
data = {dt: val > other[dt][1] for dt, val in self.data.items()}
if isinstance(other, Series):
data = {dt: val > other[i] for i, (dt, val) in enumerate(self.data.items())}
return self.__class__(data, frequency=self.frequency.symbol)
def __ge__(self, other):
self._comparison_validator(other)
if isinstance(other, Number):
data = {k: v >= other for k, v in self.data.items()}
if isinstance(other, TimeSeriesCore):
data = {dt: val >= other[dt][1] for dt, val in self.data.items()}
if isinstance(other, Series):
data = {dt: val >= other[i] for i, (dt, val) in enumerate(self.data.items())}
return self.__class__(data, frequency=self.frequency.symbol)
def __lt__(self, other):
self._comparison_validator(other)
if isinstance(other, Number):
data = {k: v < other for k, v in self.data.items()}
if isinstance(other, TimeSeriesCore):
data = {dt: val < other[dt][1] for dt, val in self.data.items()}
if isinstance(other, Series):
data = {dt: val < other[i] for i, (dt, val) in enumerate(self.data.items())}
return self.__class__(data, frequency=self.frequency.symbol)
def __le__(self, other):
self._comparison_validator(other)
if isinstance(other, Number):
data = {k: v <= other for k, v in self.data.items()}
if isinstance(other, TimeSeriesCore):
data = {dt: val <= other[dt][1] for dt, val in self.data.items()}
if isinstance(other, Series):
data = {dt: val <= other[i] for i, (dt, val) in enumerate(self.data.items())}
return self.__class__(data, frequency=self.frequency.symbol)
def __eq__(self, other):
self._comparison_validator(other)
if isinstance(other, Number):
data = {k: v == other for k, v in self.data.items()}
if isinstance(other, TimeSeriesCore):
data = {dt: val == other[dt][1] for dt, val in self.data.items()}
if isinstance(other, Series):
data = {dt: val == other[i] for i, (dt, val) in enumerate(self.data.items())}
return self.__class__(data, frequency=self.frequency.symbol)
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def __ne__(self, other):
self._comparison_validator(other)
if isinstance(other, Number):
data = {k: v != other for k, v in self.data.items()}
if isinstance(other, TimeSeriesCore):
data = {dt: val != other[dt][1] for dt, val in self.data.items()}
if isinstance(other, Series):
data = {dt: val != other[i] for i, (dt, val) in enumerate(self.data.items())}
return self.__class__(data, frequency=self.frequency.symbol)
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def __iter__(self):
self.n = 0
return self
def __next__(self):
if self.n >= len(self.dates):
raise StopIteration
else:
key = self.dates[self.n]
self.n += 1
return key, self.data[key]
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def __len__(self):
return len(self.data)
@date_parser(1)
def __contains__(self, key: object) -> bool:
return key in self.data
def _arithmatic_validator(self, other):
"""Validates input data before performing math operatios"""
if not isinstance(other, (Number, Series, TimeSeriesCore)):
raise TypeError(
"Cannot perform mathematical operations between "
f"'{self.__class__.__name__}' and '{other.__class__.__name__}'"
)
if isinstance(other, TimeSeriesCore):
if len(other) != len(self):
raise ValueError("Can only perform mathematical operations between objects of same length.")
if any(self.dates != other.dates):
raise ValueError("Can only perform mathematical operations between objects having same dates.")
if isinstance(other, Series):
if other.dtype != float:
raise TypeError(
"Cannot perform mathematical operations with "
f"'{other.__class__.__name__}' of type '{other.dtype}'"
)
if len(other) != len(self):
raise ValueError("Can only perform mathematical operations between objects of same length.")
def __add__(self, other):
self._arithmatic_validator(other)
if isinstance(other, TimeSeriesCore):
other = other.values
if isinstance(other, Series):
data = {dt: val + other[i] for i, (dt, val) in enumerate(self.data.items())}
elif isinstance(other, Number):
data = {dt: val + other for dt, val in self.data.items()}
return self.__class__(data, self.frequency.symbol)
def __sub__(self, other):
self._arithmatic_validator(other)
if isinstance(other, TimeSeriesCore):
other = other.values
if isinstance(other, Series):
data = {dt: val - other[i] for i, (dt, val) in enumerate(self.data.items())}
elif isinstance(other, Number):
data = {dt: val - other for dt, val in self.data.items()}
return self.__class__(data, self.frequency.symbol)
def __truediv__(self, other):
self._arithmatic_validator(other)
if isinstance(other, TimeSeriesCore):
other = other.values
if isinstance(other, Series):
data = {dt: val / other[i] for i, (dt, val) in enumerate(self.data.items())}
elif isinstance(other, Number):
data = {dt: val / other for dt, val in self.data.items()}
return self.__class__(data, self.frequency.symbol)
def __floordiv__(self, other):
self._arithmatic_validator(other)
if isinstance(other, TimeSeriesCore):
other = other.values
if isinstance(other, Series):
data = {dt: val // other[i] for i, (dt, val) in enumerate(self.data.items())}
elif isinstance(other, Number):
data = {dt: val // other for dt, val in self.data.items()}
return self.__class__(data, self.frequency.symbol)
def __mul__(self, other):
self._arithmatic_validator(other)
if isinstance(other, TimeSeriesCore):
other = other.values
if isinstance(other, Series):
data = {dt: val * other[i] for i, (dt, val) in enumerate(self.data.items())}
elif isinstance(other, Number):
data = {dt: val * other for dt, val in self.data.items()}
return self.__class__(data, self.frequency.symbol)
def __mod__(self, other):
self._arithmatic_validator(other)
if isinstance(other, TimeSeriesCore):
other = other.values
if isinstance(other, Series):
data = {dt: val % other[i] for i, (dt, val) in enumerate(self.data.items())}
elif isinstance(other, Number):
data = {dt: val % other for dt, val in self.data.items()}
return self.__class__(data, self.frequency.symbol)
def __pow__(self, other):
self._arithmatic_validator(other)
if isinstance(other, TimeSeriesCore):
other = other.values
if isinstance(other, Series):
data = {dt: val ** other[i] for i, (dt, val) in enumerate(self.data.items())}
elif isinstance(other, Number):
data = {dt: val**other for dt, val in self.data.items()}
return self.__class__(data, self.frequency.symbol)
def __radd__(self, other):
self._arithmatic_validator(other)
if isinstance(other, TimeSeriesCore):
other = other.values
if isinstance(other, Series):
data = {dt: val + other[i] for i, (dt, val) in enumerate(self.data.items())}
elif isinstance(other, Number):
data = {dt: val + other for dt, val in self.data.items()}
return self.__class__(data, self.frequency.symbol)
def __rsub__(self, other):
self._arithmatic_validator(other)
if isinstance(other, TimeSeriesCore):
other = other.values
if isinstance(other, Series):
data = {dt: other[i] - val for i, (dt, val) in enumerate(self.data.items())}
elif isinstance(other, Number):
data = {dt: other - val for dt, val in self.data.items()}
return self.__class__(data, self.frequency.symbol)
def __rtruediv__(self, other):
self._arithmatic_validator(other)
if isinstance(other, TimeSeriesCore):
other = other.values
if isinstance(other, Series):
data = {dt: other[i] / val for i, (dt, val) in enumerate(self.data.items())}
elif isinstance(other, Number):
data = {dt: other / val for dt, val in self.data.items()}
return self.__class__(data, self.frequency.symbol)
def __rfloordiv__(self, other):
self._arithmatic_validator(other)
if isinstance(other, TimeSeriesCore):
other = other.values
if isinstance(other, Series):
data = {dt: other[i] // val for i, (dt, val) in enumerate(self.data.items())}
elif isinstance(other, Number):
data = {dt: other // val for dt, val in self.data.items()}
return self.__class__(data, self.frequency.symbol)
def __rmul__(self, other):
self._arithmatic_validator(other)
if isinstance(other, TimeSeriesCore):
other = other.values
if isinstance(other, Series):
data = {dt: val * other[i] for i, (dt, val) in enumerate(self.data.items())}
elif isinstance(other, Number):
data = {dt: val * other for dt, val in self.data.items()}
return self.__class__(data, self.frequency.symbol)
def __rpow__(self, _):
raise NotImplementedError("This operation is not supported.")
@date_parser(1)
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def get(
self,
date: str | datetime.datetime,
default: Any = None,
closest: Literal["previous", "next"] = None,
limit: int = 1000,
raise_error: bool = False,
) -> tuple | Any:
"""Get a value for a particular key. Return a default value on KeyError
Parameters
----------
date:
Date for which the value needs to be fetched.
default: Optional, Default None
Default value to be returned in case the date is not found. Default None.
closest:
Look for previous or next value when date is not found.
If not specified, the value set in FincalOptions is used
limit:
Maximum number of days to look for the closest available date.
If exceeded without finding a date, default value will be returned.
raise_error : bool, optional
Whether to raise an error and ignore the default value.
Meant for use with __getitem__.
Returns
-------
tuple | Any
_description_
Raises
------
ValueError
If the argument for closest is not valid.
KeyError
if raise_error is true and date is not found
"""
if closest is None:
closest = FincalOptions.get_closest
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time_delta_dict = {"exact": 0, "previous": -1, "next": 1}
if closest not in time_delta_dict:
raise ValueError(f"Invalid argument from closest {closest!r}")
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delta = relativedelta(days=time_delta_dict[closest])
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for _ in range(limit):
try:
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return date, self.data[date]
except KeyError:
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if not delta:
break
date += delta
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if raise_error:
raise KeyError(date)
return default
@property
def iloc(self) -> Mapping:
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"""Returns an item or a set of items based on index
supports slicing using numerical index.
Accepts integers or Python slice objects
Usage
-----
>>> ts = TimeSeries(data, frequency='D')
>>> ts.iloc[0] # get the first value
>>> ts.iloc[-1] # get the last value
>>> ts.iloc[:3] # get the first 3 values
>>> ts.illoc[-3:] # get the last 3 values
>>> ts.iloc[5:10] # get five values starting from the fifth value
>>> ts.iloc[::2] # get every alternate date
"""
return _IndexSlicer(self)
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def head(self, n: int = 6) -> TimeSeriesCore:
"""Returns the first n items of the TimeSeries object"""
return self.iloc[:n]
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def tail(self, n: int = 6) -> TimeSeriesCore:
"""Returns the last n items of the TimeSeries object"""
return self.iloc[-n:]
def items(self):
return self.data.items()
def update(self, items: dict):
for k, v in items.items():
self[k] = v