def test_not_empty_result(self):
df = stock.get_index_ohlcv_by_date("20190101", "20190228", "코스피 200")
self.assertNotEqual(df.empty, True)
df = stock.get_index_ohlcv_by_date("20190101", "20190228", "코스닥 150")
self.assertNotEqual(df.empty, True)
df = stock.get_index_status_by_group("20190228", "KOSPI")
self.assertNotEqual(df.empty, True)
df = stock.get_index_status_by_group("20190228", "KOSDAQ")
self.assertNotEqual(df.empty, True)
def get_index_ohlcv(ticker: str, fromdate: date,
todate: date) -> Dict[date, Ohlcv]:
df = stock.get_index_ohlcv_by_date(ticker=ticker,
fromdate=date_to_str(fromdate),
todate=date_to_str(todate))
# check index changes
expected_df_columns = ['시가', '고가', '저가', '종가', '거래량', '거래대금']
for i in range(len(expected_df_columns)):
assert df.columns[i] == expected_df_columns[
i], f'Index changed: ({df.index[i]}, {expected_df_columns[i]})'
# convert Dataframe to dict
df_dict = df.to_dict(orient='index')
# marshalling
result = {}
for timestamp in df_dict.keys():
d = timestamp.date()
values = list(df_dict.get(timestamp).values())
result.update({
d:
Ohlcv(
open=values[0],
high=values[1],
low=values[2],
close=values[3],
vol=values[4],
transaction=values[5],
)
})
return result
def test_ohlcv_with_nan(self):
df = stock.get_index_ohlcv_by_date("19800101", "20200831", "1001")
# 시가 고가 저가 종가 거래량 거래대금
# 날짜
# 1980-01-04 0.00 0.00 0.00 100.00 95900 602800000
# 1980-01-05 0.00 0.00 0.00 100.15 131100 776400000
# 1980-01-07 0.00 0.00 0.00 102.53 358300 2029700000
# 1980-01-08 0.00 0.00 0.00 105.28 795800 5567200000
temp = df.iloc[0:5, 0] == np.array([0, 0, 0, 0, 0])
self.assertEqual(temp.sum(), 5)
def test_ohlcv_with_freq(self):
df = stock.get_index_ohlcv_by_date("20200101", "20200630", "1001", freq="m")
# 시가 고가 저가 종가 거래량
# 날짜
# 2020-01-31 2201.21 2277.23 2119.01 2119.01 13096066333
# 2020-02-29 2086.61 2255.49 1980.82 1987.01 13959766513
# 2020-03-31 1997.03 2089.08 1439.43 1754.64 17091025314
# 2020-04-30 1737.28 1957.51 1664.13 1947.56 21045120912
# 2020-05-31 1906.42 2054.52 1894.29 2029.60 16206496902
temp = df.iloc[0:5, 0] == np.array([2201.21, 2086.61, 1997.03, 1737.28, 1906.42])
self.assertEqual(temp.sum(), 5)
self.assertIsInstance(df.index , pd.core.indexes.datetimes.DatetimeIndex)
self.assertIsInstance(df.index[0], pd._libs.tslibs.timestamps.Timestamp)
self.assertTrue(df.index[0] < df.index[-1])
def test_ohlcv_simple(self):
df = stock.get_index_ohlcv_by_date("20210101", "20210130", "1001")
# 시가 고가 저가 종가 거래량 거래대금
# 날짜
# 2021-01-04 2874.50 2946.54 2869.11 2944.45 1026510465 25011393960858
# 2021-01-05 2943.67 2990.57 2921.84 2990.57 1519911750 26548380179493
# 2021-01-06 2993.34 3027.16 2961.37 2968.21 1793418534 29909396443430
# 2021-01-07 2980.75 3055.28 2980.75 3031.68 1524654500 27182807334912
# 2021-01-08 3040.11 3161.11 3040.11 3152.18 1297903388 40909490005818
temp = df.iloc[0:5, 0] == np.array([2874.50, 2943.67, 2993.34, 2980.75, 3040.11])
self.assertEqual(temp.sum(), 5)
self.assertIsInstance(df.index , pd.core.indexes.datetimes.DatetimeIndex)
self.assertIsInstance(df.index[0], pd._libs.tslibs.timestamps.Timestamp)
self.assertTrue(df.index[0] < df.index[-1])
def getKospi200Chart(self):
date = datetime.date(datetime.now())
date1yago = datetime.date(datetime.now() - relativedelta(years=1))
today = date.strftime("%Y%m%d")
today_1yago = date1yago.strftime("%Y%m%d")
stock_month = stock.get_index_ohlcv_by_date(today_1yago, today, '1028')
stock_month.columns = [
"StartPrice", "HighPrice", "LowPrice", "EndPrice", "Volume"
]
records = json.loads(stock_month.to_json())
return JsonResponse(records)
def test_ohlcv_in_holiday(self):
df = stock.get_index_ohlcv_by_date("20210101", "20210101", "1001")
self.assertIsInstance(df, pd.DataFrame)
self.assertTrue(df.empty)
def getDayIndex(self):
date = datetime.date(datetime.now())
date1wago = datetime.date(datetime.now() - relativedelta(weeks=2))
today = date.strftime("%Y%m%d")
today1wago = date1wago.strftime("%Y%m%d")
kospi = stock.get_index_ohlcv_by_date(today1wago, today, '1001') # KOSPI
kosdaq = stock.get_index_ohlcv_by_date(today1wago, today, '2001') # KOSDAQ
kospi200 = stock.get_index_ohlcv_by_date(today1wago, today,
'1028') # KOSPI 200
kospi = kospi.tail(2)
kosdaq = kosdaq.tail(2)
kospi200 = kospi200.tail(2)
# kospi
kospi_prev = kospi["종가"][0]
kospi_curr = kospi["종가"][1]
kospi_diff = kospi_curr - kospi_prev
kospi_diff = round(kospi_diff, 2)
kospi_flucRate = ((kospi_curr - kospi_prev) / kospi_prev) * 100
kospi_flucRate = round(kospi_flucRate, 2)
# kosdaq
kosdaq_prev = kosdaq["종가"][0]
kosdaq_curr = kosdaq["종가"][1]
print(kosdaq_prev)
print(kosdaq_curr)
kosdaq_diff = kosdaq_curr - kosdaq_prev
kosdaq_diff = round(kosdaq_diff, 2)
kosdaq_flucRate = ((kosdaq_curr - kosdaq_prev) / kosdaq_prev) * 100
kosdaq_flucRate = round(kosdaq_flucRate, 2)
# kospi 200
kospi200_prev = kospi200["종가"][0]
kospi200_curr = kospi200["종가"][1]
kospi200_diff = kospi200_curr - kospi200_prev
kospi200_diff = round(kospi200_diff, 2)
kospi200_flucRate = ((kospi200_curr - kospi200_prev) / kospi200_prev) * 100
kospi200_flucRate = round(kospi200_flucRate, 2)
json_file = OrderedDict()
json_file["KOSPI"] = {
'CurrentPrice': kospi_curr,
'FluctuatedAmount': kospi_diff,
'FluctuatedRate': kospi_flucRate
}
json_file["KOSDAQ"] = {
'CurrentPrice': kosdaq_curr,
'FluctuatedAmount': kosdaq_diff,
'FluctuatedRate': kosdaq_flucRate
}
json_file["KOSPI200"] = {
'CurrentPrice': kospi200_curr,
'FluctuatedAmount': kospi200_diff,
'FluctuatedRate': kospi200_flucRate
}
js = json.dumps(json_file)
return JsonResponse(js, safe=False)
