qharlie

C:\Users\charl\anaconda3\envs\prql\python.exe C:/Users/charl/workspace/prql/python/src/main.py

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Parsing /../resource/expressions.prql
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from otb_table
left_join some_other_table [otb_id=some_id]
select [
    otb_name,
    some_other_name,

qharlie

def memoize(f):
    """ Memoization decorator for a function taking one or more arguments. """
    class memodict(dict):
        def __getitem__(self, *key):
            return dict.__getitem__(self, key)

        def __missing__(self, key):
            ret = self[key] = f(*key)
            return ret

qharlie

# Copyright 2018 Tensorforce Team. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

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#!/usr/bin/env python

from nats.aio.client import Client as NATS
import json
import asyncio
import logging
import argparse
import gzip
import glob
import time

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import util.data as btu
from strategy import SMAStrategy
from joblib import Parallel, delayed

tickers = btu.get_nasdaq100()
def test_ticker(ticker):
    cash = 100000
    c = btu.run_backtest(SMAStrategy, ticker, '2019-05-01', '2019-05-14',cash)
    percent_gain = ((c.broker.getvalue() - cash) / cash) * 100
    print('Final Portfolio Value: {} for {} executing {} orders ( {}% )'.format(c.broker.getvalue(), ticker, len(c.broker.orders),percent_gain ))

qharlie

import backtrader as bt
import coloredlogs, logging

logger = logging.getLogger(__name__)
coloredlogs.install(fmt='%(name)s - %(levelname)s %(message)s', level='DEBUG')


class BaseStrategy(bt.Strategy):

    def log(self, txt, dt=None):

qharlie

import backtrader as bt
from strategy import BaseStrategy


class SMAStrategy(BaseStrategy):

    def __init__(self):
        super().__init__()
        self.sma_fast = bt.ind.ExponentialMovingAverage(period=10)
        self.sma_slow = bt.ind.ExponentialMovingAverage(period=30)

qharlie

import backtrader as bt
from collections import defaultdict


class KitchenSinkAnalyzer(bt.Analyzer):
    params = dict(sma_period=10, slow_sma_period=30, rsi_period=14, mean_period=10, moment_period=12, percent_period=15)

    def start(self):
        self.smas = {data: bt.indicators.SMA(data, period=self.p.sma_period)
                     for data in self.datas}

qharlie

import backtrader as bt
from collections import defaultdict


class KitchenSinkAnalyzer(bt.Analyzer):
    params = dict(sma_period=10, slow_sma_period=30, rsi_period=14, mean_period=10, moment_period=12, percent_period=15)

    def start(self):
        self.smas = {data: bt.indicators.SMA(data, period=self.p.sma_period)
                     for data in self.datas}

qharlie

import backtrader as bt
import util.data as btu
import os



def run_stock_scanner(tickers, _from, _to, analyzers):
    cerebro = bt.Cerebro()
    for ticker in tickers:
        DataFactory = btu.get_store().getdata