From f48d79afb94f197a2cf7d6866e968c3bf579a2a9 Mon Sep 17 00:00:00 2001 From: gouravkr Date: Sun, 20 Feb 2022 11:36:56 +0530 Subject: [PATCH] test files --- dict_iter.py | 29 + fincal/core.py | 11 +- my_test.py | 23 + test_files/nav_history_daily - Copy.csv | 4403 +++++++++++++++++++ test_files/nav_history_daily.csv | 139 + test_files/nav_history_monthly - Copy.csv | 219 + test_files/nav_history_monthly.csv | 11 + test_files/nav_history_quarterly - Copy.csv | 71 + test_files/nav_history_quarterly.csv | 9 + 9 files changed, 4910 insertions(+), 5 deletions(-) create mode 100644 dict_iter.py create mode 100644 my_test.py create mode 100644 test_files/nav_history_daily - Copy.csv create mode 100644 test_files/nav_history_daily.csv create mode 100644 test_files/nav_history_monthly - Copy.csv create mode 100644 test_files/nav_history_monthly.csv create mode 100644 test_files/nav_history_quarterly - Copy.csv create mode 100644 test_files/nav_history_quarterly.csv diff --git a/dict_iter.py b/dict_iter.py new file mode 100644 index 0000000..47ed46b --- /dev/null +++ b/dict_iter.py @@ -0,0 +1,29 @@ +import pandas + +from fincal.fincal import TimeSeries + +dfd = pandas.read_csv('test_files/nav_history_daily - Copy.csv') +dfm = pandas.read_csv('test_files/nav_history_monthly.csv') + +data_d = [(i.date, i.nav) for i in dfd.itertuples() if i.amfi_code == 118825] +data_d.sort() +data_m = [{'date': i.date, 'value': i.nav} for i in dfm.itertuples()] + +tsd = TimeSeries(data_d, frequency='D') + +md = dict(data_d) +counter = 1 +for i in iter(md): + print(i) + counter += 1 + if counter >= 5: break + +print('\n') +counter = 1 +for i in reversed(md): + print('rev', i) + counter += 1 + if counter >= 5: break + +x = [next(i) for i in iter(md)] +print(x) diff --git a/fincal/core.py b/fincal/core.py index 76449df..8fac8d8 100644 --- a/fincal/core.py +++ b/fincal/core.py @@ -1,7 +1,6 @@ import datetime from dataclasses import dataclass -from msilib import sequence -from typing import Dict, Iterable, List, Literal, Mapping, Sequence, Tuple, Union +from typing import Iterable, List, Literal, Mapping, Sequence, Tuple, Union @dataclass @@ -134,7 +133,9 @@ class TimeSeriesCore: def __repr__(self): if len(self.time_series) > 6: - printable_data_1 = list(self.time_series)[:3] + iter_f = iter(self.time_series) + iter_b = reversed(self.time_series) + printable_data_1 = [next(i) for i in iter(dict)] printable_data_2 = list(self.time_series)[-3:] printable_str = "TimeSeries([{}\n\t...\n\t{}])".format( ',\n\t'.join([str((i, self.time_series[i])) for i in printable_data_1]), @@ -160,7 +161,7 @@ class TimeSeriesCore: return printable_str def __getitem__(self, n): - all_keys = list(self.time_series.keys()) + all_keys = list(self.time_series) if isinstance(n, int): keys = [all_keys[n]] else: @@ -172,7 +173,7 @@ class TimeSeriesCore: return item def __len__(self): - return len(self.time_series.keys()) + return len(self.time_series) def head(self, n: int = 6): keys = list(self.time_series.keys()) diff --git a/my_test.py b/my_test.py new file mode 100644 index 0000000..7fe9139 --- /dev/null +++ b/my_test.py @@ -0,0 +1,23 @@ +import time + +import pandas + +from fincal.fincal import AllFrequencies, Frequency, TimeSeries, create_date_series + +dfd = pandas.read_csv('test_files/nav_history_daily - Copy.csv') +dfm = pandas.read_csv('test_files/nav_history_monthly.csv') +dfq = pandas.read_csv('test_files/nav_history_quarterly.csv') + +data_d = [(i.date, i.nav) for i in dfd.itertuples()] +data_m = [{'date': i.date, 'value': i.nav} for i in dfm.itertuples()] +data_q = {i.date: i.nav for i in dfq.itertuples()} + +tsd = TimeSeries(data_d, frequency='D') +tsm = TimeSeries(data_m, frequency='M', date_format='%d-%m-%Y') +tsq = TimeSeries(data_q, frequency='Q', date_format='%d-%m-%Y') + +start = time.time() +# ts.calculate_rolling_returns(datetime.datetime(2015, 1, 1), datetime.datetime(2022, 2, 1), years=1) +# fdata = tsd.ffill() +# rr = tsd.calculate_rolling_returns(datetime.datetime(2022, 1, 1), datetime.datetime(2022, 2, 1), years=1) +print(time.time() - start) diff --git a/test_files/nav_history_daily - Copy.csv b/test_files/nav_history_daily - Copy.csv new file mode 100644 index 0000000..116d054 --- /dev/null +++ b/test_files/nav_history_daily - Copy.csv @@ -0,0 +1,4403 @@ +"amfi_code","date","nav" +119528,2020-04-23,192.09 +118825,2020-04-23,45.276 +118825,2013-01-02,18.972 +118825,2013-01-03,19.011 +118825,2013-01-04,19.008 +118825,2013-01-07,18.95 +118825,2013-01-08,18.954 +118825,2013-01-09,18.94 +118825,2013-01-10,18.957 +118825,2013-01-11,18.948 +118825,2013-01-14,19.177 +118825,2013-01-15,19.272 +118825,2013-01-16,19.08 +118825,2013-01-17,19.189 +118825,2013-01-18,19.2 +118825,2013-01-21,19.236 +118825,2013-01-22,19.089 +118825,2013-01-23,19.088 +118825,2013-01-24,18.868 +118825,2013-01-25,19.098 +118825,2013-01-28,19.074 +118825,2013-01-29,19.001 +118825,2013-01-30,18.982 +118825,2013-01-31,18.913 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0000000..05b618c --- /dev/null +++ b/test_files/nav_history_quarterly - Copy.csv @@ -0,0 +1,71 @@ +"amfi_code","date","nav" +118825,2013-03-28,17.563 +118825,2013-06-28,17.802 +118825,2013-09-30,17.732 +118825,2013-12-31,20.499 +118825,2014-03-31,22.339 +118825,2014-06-30,27.011 +118825,2014-09-30,29.493 +118825,2014-12-31,31.646 +118825,2015-03-31,33.14 +118825,2015-06-30,33.227 +118825,2015-09-30,32.94 +118825,2015-12-31,33.267 +118825,2016-03-31,32.034 +118825,2016-06-30,35.006 +118825,2016-09-30,37.724 +118825,2016-12-30,36.239 +118825,2017-03-31,41.421 +118825,2017-06-30,43.979 +118825,2017-09-29,46.085 +118825,2017-12-29,50.579 +118825,2018-03-28,46.858 +118825,2018-06-29,48.716 +118825,2018-09-28,49.863 +118825,2018-12-31,50.691 +118825,2019-03-31,54.017 +118825,2019-06-28,55.181 +118825,2019-09-30,54.058 +118825,2019-12-31,57.771 +118825,2020-03-31,41.452 +118825,2020-06-30,49.526 +118825,2020-12-31,66.415 +118825,2021-03-31,70.69 +118825,2021-06-30,77.109 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a/test_files/nav_history_quarterly.csv b/test_files/nav_history_quarterly.csv new file mode 100644 index 0000000..800d496 --- /dev/null +++ b/test_files/nav_history_quarterly.csv @@ -0,0 +1,9 @@ +amfi_code,date,nav +118825,31-03-2019,54.017 +118825,28-06-2019,55.181 +118825,31-12-2019,57.771 +118825,31-03-2020,41.452 +118825,30-06-2020,49.526 +118825,30-06-2021,77.109 +118825,30-09-2021,86.128 +118825,31-12-2021,85.759