def download_one(self, symbol):
stock_data = pd.DataFrame(columns=['date', 'change_perc1', 'change_perc2',
'open', 'high', 'low', 'close',
'avg', 'volume_match', 'volume_reconcile'])
last_page = self.get_last_page(symbol)
# logging.info('Last page {}'.format(last_page))
for i in range(last_page):
stock_slice_batch = self.download_batch(i+1, symbol)
stock_data = pd.concat([stock_data, stock_slice_batch], axis=0)
stock_data = stock_data.set_index('date').apply(pd.to_numeric, errors='coerce')
stock_data.index = list(map(utils.convert_date, stock_data.index))
stock_data.index.name = 'date'
stock_data = stock_data.sort_index()
stock_data.fillna(0, inplace=True)
stock_data['volume'] = stock_data.volume_match + stock_data.volume_reconcile
# Create multiple columns
iterables = [stock_data.columns.tolist(), [symbol]]
mulindex = pd.MultiIndex.from_product(iterables, names=['Attributes', 'Symbols'])
stock_data.columns = mulindex
logging.info('data {} from {} to {} have already cloned!' \
.format(symbol,
utils.convert_text_dateformat(self.start, origin_type = '%d/%m/%Y', new_type = '%Y-%m-%d'),
utils.convert_text_dateformat(self.end, origin_type='%d/%m/%Y', new_type='%Y-%m-%d')))
return stock_data
def download_one(self, symbol):
stock_data = pd.DataFrame(columns=[
'date', 'change_perc1', 'change_perc2', 'open', 'high', 'low',
'close', 'avg', 'volume_match', 'volume_reconcile'
])
for i in range(1000):
stock_slice_batch = self.download_batch(i + 1, symbol)
stock_data = pd.concat([stock_data, stock_slice_batch], axis=0)
try:
date_end_batch = stock_slice_batch.date.values[-1]
except:
# start date is holiday or weekend
break
is_touch_end = utils.convert_date(
self.start,
'%d/%m/%Y') == utils.convert_date(date_end_batch, '%d/%m/%Y')
# logging.info('batch: {}; start date out range: {}; date_end_batch: {}'.format(i + 1, is_touch_end, date_end_batch))
if is_touch_end:
break
stock_data['change_perc1'], stock_data[
'change_perc2'] = stock_data.change_perc.apply(
utils.split_change_col).str
if 'change_perc' in stock_data.columns:
stock_data.pop('change_perc')
if 'avg' in stock_data.columns:
stock_data.pop('avg')
stock_data = stock_data.set_index('date').apply(pd.to_numeric,
errors='coerce')
stock_data.index = list(
map(
lambda text: utils.convert_date(text, date_type='%d/%m/%Y'
), stock_data.index))
stock_data.index.name = 'date'
stock_data = stock_data.sort_index()
stock_data.fillna(0, inplace=True)
stock_data[
'volume'] = stock_data.volume_match + stock_data.volume_reconcile
# Create multiple columns
iterables = [stock_data.columns.tolist(), [symbol]]
mulindex = pd.MultiIndex.from_product(iterables,
names=['Attributes', 'Symbols'])
stock_data.columns = mulindex
logging.info('data {} from {} to {} have already cloned!' \
.format(symbol,
utils.convert_text_dateformat(self.start, origin_type = '%d/%m/%Y', new_type = '%Y-%m-%d'),
utils.convert_text_dateformat(self.end, origin_type='%d/%m/%Y', new_type='%Y-%m-%d')))
return stock_data
def download_one_new(self, symbol):
start_date = utils.convert_text_dateformat(self.start,
origin_type='%d/%m/%Y',
new_type='%Y-%m-%d')
end_date = utils.convert_text_dateformat(self.end,
origin_type='%d/%m/%Y',
new_type='%Y-%m-%d')
API_VNDIRECT = 'https://finfo-api.vndirect.com.vn/v4/stock_prices/'
query = 'code:' + symbol + '~date:gte:' + start_date + '~date:lte:' + end_date
delta = datetime.strptime(end_date, '%Y-%m-%d') - datetime.strptime(
start_date, '%Y-%m-%d')
params = {
"sort": "date",
"size": delta.days + 1,
"page": 1,
"q": query
}
res = requests.get(API_VNDIRECT, params=params)
data = res.json()['data']
data = pd.DataFrame(data)
stock_data = data[[
'date', 'adClose', 'close', 'pctChange', 'average', 'nmVolume',
'nmValue', 'ptVolume', 'ptValue', 'open', 'high', 'low'
]].copy()
stock_data.columns = [
'date', 'adjust', 'close', 'change_perc', 'avg', 'volume_match',
'value_match', 'volume_reconcile', 'value_reconcile', 'open',
'high', 'low'
]
stock_data = stock_data.set_index('date').apply(pd.to_numeric,
errors='coerce')
stock_data.index = list(map(utils.convert_date, stock_data.index))
stock_data.index.name = 'date'
stock_data = stock_data.sort_index()
stock_data.fillna(0, inplace=True)
stock_data[
'volume'] = stock_data.volume_match + stock_data.volume_reconcile
# Create multiple columns
iterables = [stock_data.columns.tolist(), [symbol]]
mulindex = pd.MultiIndex.from_product(iterables,
names=['Attributes', 'Symbols'])
stock_data.columns = mulindex
logging.info('data {} from {} to {} have already cloned!' \
.format(symbol,
utils.convert_text_dateformat(self.start, origin_type = '%d/%m/%Y', new_type = '%Y-%m-%d'),
utils.convert_text_dateformat(self.end, origin_type='%d/%m/%Y', new_type='%Y-%m-%d')))
return stock_data
def __init__(self, symbols, start, end, *arg, **karg):
self.symbols = symbols
self.start = utils.convert_text_dateformat(start, new_type = '%d/%m/%Y')
self.end = utils.convert_text_dateformat(end, new_type = '%d/%m/%Y')