def get_data():
database = sqliteDb()
currency = request.args.get('currency')
timeframe = request.args.get('timeframe')
indicator_name = request.args.get('indicator_name')
indicator_period = request.args.get('indicator_period')
candle = request.args.get('candle')
response = database.getData(currency, timeframe)
database.close()
df = pd.DataFrame.from_records(
response,
columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])
if indicator_name == 'EMA':
indicator = ta.ema(df['close'], length=int(indicator_period))
elif indicator_name == 'RSI':
indicator = ta.rsi(df['close'], length=int(indicator_period))
indicator = indicator.fillna('undefined')
dict = indicator.to_dict()
result = {
'open value': response[99 - int(candle)][1],
'high value': response[99 - int(candle)][2],
'low value': response[99 - int(candle)][3],
'close value': response[99 - int(candle)][4],
'timestamp': response[99 - int(candle)][0],
indicator_name: dict[99 - int(candle)]
}
return json.dumps(result)
def get_moment_last_spray():
spray_moments = list(sqliteDb().get_spray_moments())
# we assume the last record in the database is the latest
moment_last_spray = spray_moments[len(spray_moments) - 1]
format = '%Y-%m-%d %H:%M:%S'
return (datetime.strptime(moment_last_spray, format))
def predictions():
accept_header = request.headers.get('Accept')
predictions = sqliteDb().get_predictions()
if 'application/json' in accept_header:
return jsonify(predictions)
elif 'text/html' in accept_header:
columns = list(predictions[0].keys())
rows = []
for prediction in predictions:
rows.append([*prediction.values()])
return render_template('predictions.html',
predictions=predictions,
columns=columns,
rows=rows)
else:
return (
"I'm sorry but support for that content type has not been implemented yet."
)
def get_last_prediction():
predictions = sqliteDb().get_predictions()
last_prediction = predictions[len(predictions) - 1]
return last_prediction
from binance_api import Binance
import datetime
import json
from db import sqliteDb
api = Binance(
'AMWNxQ9DJ7t7ZKEAR8qT5boPYrdUIQHXUXBb7BgGb4fgKP53yK0YXaG9XPPkrJXU',
'tSr4OaBiH0IXqXUNvVzsSRXyYpG314a03Yhltx9NQa9ok6M9h96YJwnu5BDMYGoa')
pattern = [["ETHUSDT", "LTCUSDT", "XLMUSDT", "XMRUSDT", "XEMUSDT"],
['1h', '1d']]
db = sqliteDb()
print('recording to db... ' +
datetime.datetime.now().strftime("%m/%d/%Y, %H:%M:%S"))
for currency in pattern[0]:
for interval in pattern[1]:
responses = api.call_api(
**{
'command': 'klines',
'symbol': currency,
'interval': interval,
'limit': 100
})
db.addToDb(currency, interval, json.dumps(responses))
db.close()
print('finished ' + datetime.datetime.now().strftime("%m/%d/%Y, %H:%M:%S"))