trader.py

import json
from matplotlib import style, pyplot as plt
import pandas
import urllib.request
import finta

style.use('default')

STOCK_SYMBOL = 'AAPL'

INPUT_URL = 'https://www.quandl.com/api/v3/datasets/WIKI/%s.json?order=asc' % (STOCK_SYMBOL)
OUTPUT_PATH = './data/OHLCV/%s.xlsx' % (STOCK_SYMBOL)


def import_data():
    response = urllib.request.urlopen(INPUT_URL)
    response_data = json.loads(response.read())
    sanitized_data = response_data['dataset']['data']
    return sanitized_data


def create_dataframe(dataframe_data):
    df = pandas.read_json(json.dumps(dataframe_data))
    df.columns = ['date', 'open', 'high', 'low', 'close', 'volume', 'ex-dividend', 'split ratio', 'adj. open', 'adj. high', 'adj. low', 'adj. close', 'adj. volume']
    df['std'] = df['close'].std()
    df['ema7'] = finta.TA.EMA(df, period=7)
    df['ema20'] = finta.TA.EMA(df, period=20)
    df = df.join(finta.TA.BBANDS(df, MA=df['ema20'], column='close'))
    return df


def draw_image(df):
    fig, ax = plt.subplots()
    df = df[[
        'date',
        'close',
        'std',
        'upper_bband',
        'middle_bband',
        'lower_bband',
        'b_bandwith'
    ]].copy()
    df.date = pandas.to_datetime(df.date, format='%Y-%m-%d')
    df.set_index(['date'], inplace=True)
    ax.set(title=STOCK_SYMBOL, xlabel='time (days)', ylabel='price ($)')
    ax.grid()
    df.plot(ax=ax)
    plt.show()


def write_excel_file(df):
    df.to_excel(OUTPUT_PATH, sheet_name=STOCK_SYMBOL)


data = import_data()
ohlc = create_dataframe(data)

draw_image(ohlc)
write_excel_file(ohlc)