450 lines
15 KiB
Python
450 lines
15 KiB
Python
from __future__ import annotations
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import datetime
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import inspect
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from collections import UserList
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from dataclasses import dataclass
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from numbers import Number
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from typing import Callable, Iterable, List, Literal, Mapping, Sequence, Type
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from .utils import FincalOptions, _parse_date, _preprocess_timeseries
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@dataclass(frozen=True)
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class Frequency:
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name: str
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freq_type: str
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value: int
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days: int
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symbol: str
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def date_parser(*pos):
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"""Decorator to parse dates in any function
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Accepts the 0-indexed position of the parameter for which date parsing needs to be done.
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Works even if function is used with keyword arguments while not maintaining parameter order.
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Example:
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--------
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>>> @date_parser(2, 3)
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>>> def calculate_difference(diff_units='days', return_type='int', date1, date2):
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... diff = date2 - date1
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... if return_type == 'int':
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... return diff.days
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... return diff
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...
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>>> calculate_difference(date1='2019-01-01', date2='2020-01-01')
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datetime.timedelta(365)
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Each of the dates is automatically parsed into a datetime.datetime object from string.
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"""
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def parse_dates(func):
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def wrapper_func(*args, **kwargs):
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date_format: str = kwargs.get("date_format", None)
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args: list = list(args)
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sig: inspect.Signature = inspect.signature(func)
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params: list = [i[0] for i in sig.parameters.items()]
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for j in pos:
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kwarg: str = params[j]
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date = kwargs.get(kwarg, None)
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in_args: bool = False
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if date is None:
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try:
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date = args[j]
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except IndexError:
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pass
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in_args = True
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if date is None:
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continue
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parsed_date: datetime.datetime = _parse_date(date, date_format)
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if not in_args:
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kwargs[kwarg] = parsed_date
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else:
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args[j] = parsed_date
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return func(*args, **kwargs)
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return wrapper_func
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return parse_dates
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class AllFrequencies:
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D = Frequency("daily", "days", 1, 1, "D")
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W = Frequency("weekly", "days", 7, 7, "W")
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M = Frequency("monthly", "months", 1, 30, "M")
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Q = Frequency("quarterly", "months", 3, 91, "Q")
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H = Frequency("half-yearly", "months", 6, 182, "H")
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Y = Frequency("annual", "years", 1, 365, "Y")
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class _IndexSlicer:
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"""Class to create a slice using iloc in TimeSeriesCore"""
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def __init__(self, parent_obj: object):
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self.parent = parent_obj
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def __getitem__(self, n):
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if isinstance(n, int):
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keys: list = [self.parent.dates[n]]
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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]
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if len(item) == 1:
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return item[0]
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return self.parent.__class__(item, self.parent.frequency.symbol)
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class Series(UserList):
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"""Container for a series of objects, all objects must be of the same type"""
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def __init__(
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self,
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data: Sequence,
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data_type: Literal["date", "number", "bool"],
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date_format: str = None,
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):
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types_dict: dict = {
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"date": datetime.datetime,
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"datetime": datetime.datetime,
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"datetime.datetime": datetime.datetime,
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"float": float,
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"int": float,
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"number": float,
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"bool": bool,
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}
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if data_type not in types_dict.keys():
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raise ValueError("Unsupported value for data type")
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if not isinstance(data, Sequence):
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raise TypeError("Series object can only be created using Sequence types")
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if data_type in ["date", "datetime", "datetime.datetime"]:
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data = [_parse_date(i, date_format) for i in data]
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else:
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func: Callable = types_dict[data_type]
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data: list = [func(i) for i in data]
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self.dtype: Type = types_dict[data_type]
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self.data: Sequence = data
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def __repr__(self):
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return f"{self.__class__.__name__}({self.data}, data_type='{self.dtype.__name__}')"
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def __getitem__(self, i):
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if isinstance(i, slice):
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return self.__class__(self.data[i], str(self.dtype.__name__))
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else:
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return self.data[i]
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def __gt__(self, other):
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if self.dtype == bool:
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raise TypeError("> not supported for boolean series")
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if isinstance(other, (str, datetime.datetime, datetime.date)):
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other = _parse_date(other)
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if self.dtype == float and isinstance(other, Number) or isinstance(other, self.dtype):
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gt = Series([i > other for i in self.data], "bool")
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else:
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raise Exception(f"Cannot compare type {self.dtype.__name__} to {type(other).__name__}")
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return gt
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def __ge__(self, other):
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if self.dtype == bool:
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raise TypeError(">= not supported for boolean series")
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if isinstance(other, (str, datetime.datetime, datetime.date)):
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other = _parse_date(other)
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if self.dtype == float and isinstance(other, Number) or isinstance(other, self.dtype):
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ge = Series([i >= other for i in self.data], "bool")
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else:
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raise Exception(f"Cannot compare type {self.dtype.__name__} to {type(other).__name__}")
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return ge
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def __lt__(self, other):
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if self.dtype == bool:
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raise TypeError("< not supported for boolean series")
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if isinstance(other, (str, datetime.datetime, datetime.date)):
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other = _parse_date(other)
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if self.dtype == float and isinstance(other, Number) or isinstance(other, self.dtype):
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lt = Series([i < other for i in self.data], "bool")
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else:
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raise Exception(f"Cannot compare type {self.dtype.__name__} to {type(other).__name__}")
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return lt
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def __le__(self, other):
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if self.dtype == bool:
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raise TypeError("<= not supported for boolean series")
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if isinstance(other, (str, datetime.datetime, datetime.date)):
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other = _parse_date(other)
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if self.dtype == float and isinstance(other, Number) or isinstance(other, self.dtype):
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le = Series([i <= other for i in self.data], "bool")
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else:
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raise Exception(f"Cannot compare type {self.dtype.__name__} to {type(other).__name__}")
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return le
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def __eq__(self, other):
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if isinstance(other, (str, datetime.datetime, datetime.date)):
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other = _parse_date(other)
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if self.dtype == float and isinstance(other, Number) or isinstance(other, self.dtype):
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eq = Series([i == other for i in self.data], "bool")
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else:
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raise Exception(f"Cannot compare type {self.dtype.__name__} to {type(other).__name__}")
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return eq
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class TimeSeriesCore:
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"""Defines the core building blocks of a TimeSeries object"""
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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"],
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date_format: str = "%Y-%m-%d",
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):
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"""Instantiate a TimeSeriesCore object
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Parameters
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----------
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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.
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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.
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frequency : str
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The frequency of the time series.
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Valid values are {D, W, M, Q, H, Y}
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date_format : str, optional, default "%Y-%m-%d"
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Specify the format of the date
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Required only if the first argument of tuples is a string. Otherwise ignored.
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"""
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ts_data = _preprocess_timeseries(ts_data, date_format=date_format)
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self.data = dict(ts_data)
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if len(self.data) != len(ts_data):
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print("Warning: The input data contains duplicate dates which have been ignored.")
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self.frequency: Frequency = getattr(AllFrequencies, frequency)
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self.iter_num: int = -1
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self._dates: list = None
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self._values: list = None
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self._start_date: datetime.datetime = None
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self._end_date: datetime.datetime = None
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@property
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def dates(self) -> Series:
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"""Get a list of all the dates in the TimeSeries object"""
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if self._dates is None or len(self._dates) != len(self.data):
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self._dates = list(self.data.keys())
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return Series(self._dates, "date")
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@property
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def values(self) -> Series:
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"""Get a list of all the Values in the TimeSeries object"""
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if self._values is None or len(self._values) != len(self.data):
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self._values = list(self.data.values())
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return Series(self._values, "number")
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@property
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def start_date(self) -> datetime.datetime:
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"""The first date in the TimeSeries object"""
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return self.dates[0]
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@property
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def end_date(self) -> datetime.datetime:
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"""The last date in the TimeSeries object"""
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return self.dates[-1]
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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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"""
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printable = {}
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iter_f = iter(self.data)
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first_n = [next(iter_f) for i in range(n // 2)]
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iter_b = reversed(self.data)
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last_n = [next(iter_b) for i in range(n // 2)]
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last_n.sort()
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printable["start"] = [str((i, self.data[i])) for i in first_n]
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printable["end"] = [str((i, self.data[i])) for i in last_n]
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return printable
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def __repr__(self):
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if len(self.data) > 6:
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printable = self._get_printable_slice(6)
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printable_str = "{}([{}\n\t ...\n\t {}], frequency={})".format(
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self.__class__.__name__,
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",\n\t ".join(printable["start"]),
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",\n\t ".join(printable["end"]),
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repr(self.frequency.symbol),
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)
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else:
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printable_str = "{}([{}], frequency={})".format(
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self.__class__.__name__,
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",\n\t".join([str(i) for i in self.data.items()]),
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repr(self.frequency.symbol),
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)
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return printable_str
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def __str__(self):
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if len(self.data) > 6:
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printable = self._get_printable_slice(6)
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printable_str = "[{}\n ...\n {}]".format(
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",\n ".join(printable["start"]),
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",\n ".join(printable["end"]),
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)
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else:
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printable_str = "[{}]".format(",\n ".join([str(i) for i in self.data.items()]))
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return printable_str
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@date_parser(1)
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def _get_item_from_date(self, date: str | datetime.datetime):
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return date, self.data[date]
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def _get_item_from_key(self, key: str | datetime.datetime):
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if isinstance(key, int):
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raise KeyError(f"{key}. \nHint: use .iloc[{key}] for index based slicing.")
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if key in ["dates", "values"]:
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return getattr(self, key)
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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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data_to_return = [self._get_item_from_key(key) for key in date_list]
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return self.__class__(data_to_return, frequency=self.frequency.symbol)
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def _get_item_from_series(self, series: Series):
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if series.dtype == bool:
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if len(series) != len(self.dates):
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raise ValueError(f"Length of Series: {len(series)} did not match length of object: {len(self.dates)}")
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dates_to_return = [self.dates[i] for i, j in enumerate(series) if j]
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elif series.dtype == datetime.datetime:
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dates_to_return = list(series)
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else:
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raise TypeError(f"Cannot slice {self.__class__.__name__} using a Series of {series.dtype.__name__}")
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return self._get_item_from_list(dates_to_return)
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def __getitem__(self, key):
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if isinstance(key, (int, str, datetime.datetime, datetime.date)):
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return self._get_item_from_key(key)
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if isinstance(key, Series):
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return self._get_item_from_series(key)
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if isinstance(key, Sequence):
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return self._get_item_from_list(key)
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raise TypeError(f"Invalid type {repr(type(key).__name__)} for slicing.")
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def __setitem__(self, key: str | datetime.datetime, value: Number) -> None:
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key = _parse_date(key)
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self.data.update({key: value})
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self.data = dict(sorted(self.data.items()))
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def __iter__(self):
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self.n = 0
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return self
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def __next__(self):
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if self.n >= len(self.dates):
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raise StopIteration
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else:
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key = self.dates[self.n]
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self.n += 1
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return key, self.data[key]
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def __len__(self):
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return len(self.data)
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@date_parser(1)
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def __contains__(self, key: object) -> bool:
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return key in self.data
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@date_parser(1)
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def get(self, date: str | datetime.datetime, default=None, closest=None):
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if closest is None:
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closest = FincalOptions.get_closest
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if closest == "exact":
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try:
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item = self._get_item_from_date(date)
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return item
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except KeyError:
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return default
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if closest == "previous":
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delta = datetime.timedelta(-1)
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elif closest == "next":
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delta = datetime.timedelta(1)
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else:
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raise ValueError(f"Invalid argument from closest {closest!r}")
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while True:
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try:
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item = self._get_item_from_date(date)
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return item
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except KeyError:
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date += delta
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@property
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def iloc(self) -> Mapping:
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"""Returns an item or a set of items based on index
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supports slicing using numerical index.
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Accepts integers or Python slice objects
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Usage
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-----
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>>> ts = TimeSeries(data, frequency='D')
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>>> ts.iloc[0] # get the first value
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>>> ts.iloc[-1] # get the last value
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>>> ts.iloc[:3] # get the first 3 values
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>>> ts.illoc[-3:] # get the last 3 values
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>>> ts.iloc[5:10] # get five values starting from the fifth value
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>>> ts.iloc[::2] # get every alternate date
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"""
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return _IndexSlicer(self)
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def head(self, n: int = 6) -> TimeSeriesCore:
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"""Returns the first n items of the TimeSeries object"""
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return self.iloc[:n]
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def tail(self, n: int = 6) -> TimeSeriesCore:
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"""Returns the last n items of the TimeSeries object"""
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return self.iloc[-n:]
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def items(self):
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return self.data.items()
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