gourav/PyFacts
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

type hints and docs

Browse Source
This commit is contained in:
Gourav Kumar 2022-07-24 08:46:45 +05:30
parent b1305ca89d
commit 583ca98e51
1 changed files with 14 additions and 14 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

28
pyfacts/pyfacts.py
View File

@ -262,7 +262,7 @@ class TimeSeries(TimeSeriesCore):
return_period_unit: Literal["years", "months", "days"] = "years", return_period_unit: Literal["years", "months", "days"] = "years",
return_period_value: int = 1, return_period_value: int = 1,
date_format: str = None, date_format: str = None,
) -> float: ) -> Tuple[datetime.datetime, float]:
"""Method to calculate returns for a certain time-period as on a particular date """Method to calculate returns for a certain time-period as on a particular date
Parameters Parameters
@ -295,7 +295,7 @@ class TimeSeries(TimeSeriesCore):
* fail: Raise a ValueError * fail: Raise a ValueError
* nan: Return nan as the value * nan: Return nan as the value
compounding : bool, optional annual_compounded_returns : bool, optional
Whether the return should be compounded annually. Whether the return should be compounded annually.
return_period_unit : 'years', 'months', 'days' return_period_unit : 'years', 'months', 'days'
@ -321,14 +321,14 @@ class TimeSeries(TimeSeriesCore):
Example Example
-------- --------
>>> calculate_returns(datetime.date(2020, 1, 1), years=1) >>> ts.calculate_returns(datetime.date(2020, 1, 1), years=1)
(datetime.datetime(2020, 1, 1, 0, 0), .0567) (datetime.datetime(2020, 1, 1, 0, 0), .0567)
""" """
as_on_delta, prior_delta = _preprocess_match_options(as_on_match, prior_match, closest) as_on_delta, prior_delta = _preprocess_match_options(as_on_match, prior_match, closest)
prev_date = as_on - relativedelta(**{return_period_unit: return_period_value})
current = _find_closest_date(self.data, as_on, closest_max_days, as_on_delta, if_not_found) current = _find_closest_date(self.data, as_on, closest_max_days, as_on_delta, if_not_found)
prev_date = as_on - relativedelta(**{return_period_unit: return_period_value})
if current[1] != str("nan"): if current[1] != str("nan"):
previous = _find_closest_date(self.data, prev_date, closest_max_days, prior_delta, if_not_found) previous = _find_closest_date(self.data, prev_date, closest_max_days, prior_delta, if_not_found)
@ -368,16 +368,16 @@ class TimeSeries(TimeSeriesCore):
End date for the returns calculation. End date for the returns calculation.
frequency : str, optional frequency : str, optional
Frequency at which the returns should be calcualated. Frequency at which the returns should be calculated.
Valid values are {D, W, M, Q, H, Y} Valid values are {D, W, M, Q, H, Y}
as_on_match : str, optional as_on_match : str, optional
The match mode to be used for the as on date. The match mode to be used for the as on date.
If not specified, the value for the closes parameter will be used. If not specified, the value for the closest parameter will be used.
prior_match : str, optional prior_match : str, optional
The match mode to be used for the prior date, i.e., the date against which the return will be calculated. The match mode to be used for the prior date, i.e., the date against which the return will be calculated.
If not specified, the value for the closes parameter will be used. If not specified, the value for the closest parameter will be used.
closest : previous | next | exact closest : previous | next | exact
The default match mode for dates. The default match mode for dates.
@ -395,7 +395,7 @@ class TimeSeries(TimeSeriesCore):
For instance, if the input date is before the starting of the first date of the time series, For instance, if the input date is before the starting of the first date of the time series,
but match mode is set to previous. A DateOutOfRangeError will be raised in such cases. but match mode is set to previous. A DateOutOfRangeError will be raised in such cases.
compounding : bool, optional annual_compounded_returns : bool, optional
Should the returns be compounded annually. Should the returns be compounded annually.
return_period_unit : years | month | days return_period_unit : years | month | days
@ -410,7 +410,7 @@ class TimeSeries(TimeSeriesCore):
Returns Returns
------- -------
Returs the rolling returns as a TimeSeries object. Returns the rolling returns as a TimeSeries object.
Raises Raises
------ ------
@ -431,7 +431,7 @@ class TimeSeries(TimeSeriesCore):
raise ValueError(f"Invalid argument for frequency {frequency}") raise ValueError(f"Invalid argument for frequency {frequency}")
if from_date is None: if from_date is None:
from_date = self.start_date + relativedelta( from_date = self.start_date + relativedelta(
days=int(_interval_to_years(return_period_unit, return_period_value) * 365 + 1) days=math.ceil(_interval_to_years(return_period_unit, return_period_value) * 365)
) )
if to_date is None: if to_date is None:
@ -476,7 +476,7 @@ class TimeSeries(TimeSeriesCore):
) -> float: ) -> float:
"""Calculates the volatility of the time series.add() """Calculates the volatility of the time series.add()
The volatility is calculated as the standard deviaion of periodic returns. The volatility is calculated as the standard deviation of periodic returns.
The periodicity of returns is based on the periodicity of underlying data. The periodicity of returns is based on the periodicity of underlying data.
Parameters: Parameters:
@ -761,10 +761,10 @@ class TimeSeries(TimeSeriesCore):
Parameters: Parameters:
----------- -----------
other: TimeSeries other: TimeSeries
Another object of TimeSeries class whose dates need to be syncronized Another object of TimeSeries class whose dates need to be synchronized
fill_method: ffill | bfill, default ffill fill_method: ffill | bfill, default ffill
Method to use to fill missing values in time series when syncronizing Method to use to fill missing values in time series when synchronizing
Returns: Returns:
-------- --------
@ -903,7 +903,7 @@ def read_csv(
header = data[read_start_row] header = data[read_start_row]
print(header) print(header)
# fmt: off # fmt: off
# Black and pylance disagree on the foratting of the following line, hence formatting is disabled # Black and pylance disagree on the formatting of the following line, hence formatting is disabled
data = data[(read_start_row + 1):read_end_row] data = data[(read_start_row + 1):read_end_row]
# fmt: on # fmt: on