def str_perc_avg(data):
# Average of success buy prices
d = get_perc_from_history(data, 4)
if len(d) > 0:
return mean([l['y0'] for l in d])
else:
return None
def str_perc_low(data):
# Low of success buy prices
d = get_perc_from_history(data, 4)
if len(d) > 0:
return min([l['y0'] for l in d])
else:
return None
def str_perc_first(data):
# Sort by timestamp
# Low of success buy prices
data = get_perc_from_history(data, 4)
if len(data) > 0:
return sorted(data, key=lambda k: k['t0'])[0]['y0']
else:
return None
def run(self, perc):
# Get day cheap symbols
i = 0
ret = {}
for f in glob.glob(dir_day + '/*.json'):
if debug is True and i == 2:
continue
symbol = os.path.splitext(os.path.basename(f))[0]
with open(f) as f:
# [ { o, c, h, l, v, t }, { o, c, h, l, v, t } ]
# Get perc
data = json.load(f)
if len(data) == 0:
continue
ret[symbol] = get_perc_from_history(data, perc)
i += 1
# Print
print('Found %i symbols' % len(ret))
# Format as JSON
out = {}
for symbol in ret:
out[symbol] = {}
out[symbol].update({
'len': len(ret[symbol]),
'data': [],
})
print('%s: %i' % (symbol, len(ret[symbol])))
for p in ret[symbol]:
out[symbol]['data'].append({
'time': {
't0': to_hour(p['t0']),
't1': to_hour(p['t1']),
},
'price': {
'y0': p['y0'],
'y1': p['y1'],
},
'perc': round(p['perc'], 2),
'volume': {
'v0': p['v0'],
'v1': p['v1'],
},
})
print(json.dumps(out, indent=2))
'low',
'perc_avg',
'perc_first',
'perc_low',
]
ret = {
'summary': {
'success_days': 0,
'success_total': 0,
'strategies': {},
}
}
# Get count of successful buy/sell pairs (benchmark)
for date, points in sorted(data_by_date.items()):
success_count = len(get_perc_from_history(points, 4))
if success_count > 0:
ret['summary']['success_days'] += 1
ret['summary']['success_total'] += success_count
for strategy in strategies:
strategy_info = {
'success_total': 0,
'success_days': 0,
'success_dates': [],
'success_days_perc': 0,
}
print('====', strategy)
prev = None
for date, points in sorted(data_by_date.items()):
if prev is not None: