def read_thru_date(lines, latest_date):
for line in lines:
splitted_line = get_date_value_line(line)
if splitted_line:
(date_str, value) = splitted_line
date = str_to_date(date_str)
if (latest_date == None or date > latest_date):
return splitted_line
def test_next_business_day(self):
date_str = '2016-12-31'
current_date = str_to_date(date_str)
print(current_date)
print(f'current_date = {current_date}')
next_day = next_business_day(current_date)
print(f'next_day = {next_day}')
data = yf.download("GOOG",
start=next_day,
end=next_day + datetime.timedelta(days=1),
period="1d",
interval="1d",
rounding=True)
print(data)
self.assertTrue(data['Open'][0], 778.81)
def get_samples(company_ids, date_list, features_ids):
connection, cursor = get_connection_cursor()
sql = get_samples_sql(company_ids, date_list, features_ids)
cursor.execute(sql)
sample_wrapper_list = []
for row in tqdm(cursor):
row_list = list(row)
company_id = row_list[COMPANY_ID]
ticker = row_list[TICKER]
date = row_list[DATE]
date_obj = str_to_date(date)
sample = row_list[SAMPLE_START:]
sample_wrapper = RawSample(company_id, ticker, date_obj, sample)
sample_wrapper_list.append(sample_wrapper)
print(f"there are potential {len(sample_wrapper_list)} raw samples")
return sample_wrapper_list
def get_yahoo_responses(companies_ids, date_str_list):
dateticker_to_closingprice_map = {}
ticker_list = get_tickers(companies_ids)
for date_str in tqdm(date_str_list, desc="looping over all given quarters, calling Yahoo on each", colour="CYAN"):
date = str_to_date(date_str)
missing_tickers = TickersPricesDAO.get_missing_tickers(date, ticker_list)
sizeof_missing_tickers = len(missing_tickers)
if sizeof_missing_tickers:
end_date = date + datetime.timedelta(days=3)
end_date_str = str(end_date)
print(
f'\nis about to download stock info from yahoo. Original date: {date_str}, looking for range ({date_str} -- {end_date_str}). Looking for {sizeof_missing_tickers} missing tickers: {missing_tickers}, ')
data = yf.download(missing_tickers, start=date_str, end=end_date_str, period="1d")
print(data)
single_date_map = create_dateticker_to_closingprice(data, missing_tickers, date)
# insert_data_into_db(single_date_map)
# single_date_map = insert_data_into_db(data, missing_tickers, date)
# # responses[date] = data
dateticker_to_closingprice_map = {**dateticker_to_closingprice_map, **single_date_map}
return dateticker_to_closingprice_map
def test_get_max_date_for_metric_id(self):
old_date = str_to_date('2019-3-31')
max_date = get_max_date_for_metric_id(1)
self.assertTrue(max_date > old_date)
def test_next_business_day(self):
date_str = '2016-12-31'
current_date = str_to_date(date_str)
next_day = next_business_day(current_date)
print(next_day)
def test_adding_dates(self):
date = str_to_date('2020-03-31')
next_date = date + datetime.timedelta(days=91)
print(f"next date = {next_date}")