newellp88
52 lines
1.9 KiB
Python
52 lines
1.9 KiB
Python
"""
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script that runs continuously and collects pricing and technical indicators data,
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entering the data into instrument/window data tables.
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"""
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import sqlite3
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import sqlalchemy
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import pandas as pd
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from datetime import datetime
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from backend.pricing import history
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from backend.config import currencies
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from backend.indicators import sma, stoch, pivotPoints, bollBands
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windows = ['M5', 'M15', 'H1', 'H4', 'D']
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for instr in currencies:
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for w in windows:
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LiteCurrencyDB(instr, w)
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def LiteCurrencyDB(instr, w):
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# connect to the DB
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db = sqlite3.connect('liteDB/currencies.db')
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c = db.cursor()
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table_name = "%s_%s" % (instr, w)
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# get last 500 data points
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df = history(instr, w)
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prices = df['Close']
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# set the dataframe with our technical indicators
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df['fast_sma'] = sma(prices, 6)
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df['slow_sma'] = sma(prices, 10)
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df = stoch(df, 6, 3)
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df = bollBands(df, 5, 0.5)
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pp = pd.DataFrame(data=pivotPoints(df))
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df = pd.concat([df,pp], axis=1, join_axes=[df.index])
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inputs = list(tuple(row for idx, row in df.iterrows()))
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# insert them into the dedicated table for this currency and timeframe
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c.execute('''CREATE TABLE IF NOT EXISTS {}(
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dt TEXT, Open REAL, High REAL, Low REAL, Close REAL,
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Volume INTEGER, fast_sma REAL, slow_sma REAL, Lstoch REAL,
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Hstoch REAL, K REAL, D REAL, rolling_mean REAL, boll_high REAL,
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boll_low REAL, PP REAL, R1 REAL, R2 REAL, R3 REAL, S1 REAL,
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S2 REAL, S3 REAL
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)'''.format(table_name))
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c.executemany('''INSERT INTO {}(
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dt, Open, High, Low, Close, Volume, fast_sma, slow_sma, Lstoch,
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Hstoch, K, D, rolling_mean, boll_high, boll_low, PP, R1, R2, R3,
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S1, S2, S3
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) VALUES(?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)'''
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.format(table_name), inputs)
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db.commit()
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print('table created successfully')
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return db, df
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