1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
|
import requests
import json
from datetime import datetime, timedelta, timezone
import pytz
# helper function to pull most recent chart data on failure
def pull_last_from_file():
fd = open('last_chart_data.json', 'r')
d = json.loads(fd.read())
fd.close()
return d
def update_last_file(data):
fd = open('last_chart_data.json', 'w')
fd.truncate(0)
fd.write(json.dumps(data))
fd.close()
"""
Given the parameters,
fetches the data for the corresponding chart using yahoo finance.
If bad request, returns the previous chart.
"""
def fetch_chart_data(ticker, period='5d', interval='1m'):
params = {
'interval' : interval, # 1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 4h, 1d, 5d, 1wk, 1mo, 3mo
'range' : period, # "1d","5d","1mo","3mo","6mo","1y","2y","5y","10y","ytd","max"
'events' : 'div|split|earn',
'includePrePost' : 'false' }
headers = {'User-agent' : 'fin-backtesting-proj'}
r = requests.get("https://query1.finance.yahoo.com/v8/finance/chart/" + ticker, headers=headers, params=params)
print(r.url)
print("status_code:\t", r.status_code)
# decode the JSON response data into a Python object
try:
r.raise_for_status() # raises if error before parsing
except:
last_data = pull_last_from_file()
last_data['error'] = True
return last_data
data_obj = r.json()
# get the specific data we want
if 'timestamp' not in data_obj['chart']['result'][0]:
last_data = pull_last_from_file()
last_data['error'] = True
return last_data
timestamps = data_obj['chart']['result'][0]['timestamp']
close_prices = data_obj['chart']['result'][0]['indicators']['quote'][0]['close']
# clean out null's and 0s from the data
i = 0
while i < len(timestamps):
if close_prices[i] == None or close_prices[i] == 0:
del close_prices[i]
del timestamps[i]
i -= 1
i += 1
name = data_obj['chart']['result'][0]['meta']['longName']
data = {'timestamps': timestamps, 'prices': close_prices, 'name': name, 'error': False}
# update_last_file(data)
# save data to file in case necessary
return data
"""
Given the parameters,
fetches the data for the corresponding chart using yahoo finance.
Cosumes period_length as a timedelta and period_end_date as a date
If bad request, returns the previous chart.
"""
def fetch_chart_data_backtest(ticker='XRP/USD', interval='1Min', period_end_date=None, period_length=None):
if period_end_date == None:
period_end_date = datetime.now().astimezone(pytz.timezone('UTC'))
if period_length == None:
period_length = timedelta(days=5)
# cast to int to truncate the decimal
period2 = datetime.isoformat(period_end_date)
# find the first period via subtracting the period length
period1 = datetime.isoformat(period_end_date - period_length)
print(period2, period1)
params = {
'symbols' : ticker,
'timeframe' : interval,
'start' : period1,
'end' : period2,
'limit': 10000,
'sort' : 'asc',
}
headers = {"accept": "application/json"}
url = "https://data.alpaca.markets/v1beta3/crypto/us/bars"
# r = requests.get(url, headers=headers, params=params)
r = requests.get(url, params=params, headers=headers)
print(r.url)
print("status_code:\t", r.status_code)
# print(r.text)
# decode the JSON response data into a Python object
try:
r.raise_for_status() # raises if error before parsing
except:
print(r.text)
last_data = pull_last_from_file()
last_data['error'] = True
return last_data
data_obj = r.json()
res_headers = r.headers
print(res_headers)
timestamps = []
close_prices = []
assert ticker in data_obj['bars']
chart_data = data_obj['bars'][ticker]
for tmp in chart_data:
# t, o, h, l, c, v, n, vw (keys for data)
timezone_adjusted = datetime.fromisoformat(tmp['t']).astimezone(pytz.timezone('US/Eastern'))
timestamps.append(timezone_adjusted.timestamp())
close_prices.append(tmp['c'])
# clean out null's and 0s from the data
# i = 0
# while i < len(timestamps):
# if close_prices[i] == None or close_prices[i] == 0:
# del close_prices[i]
# del timestamps[i]
# i -= 1
# i += 1
name = ticker
data = {'timestamps': timestamps, 'prices': close_prices, 'name': name, 'error': False}
update_last_file(data)
# save data to file in case necessary
return data
def fetch_chart_data_yahoo(ticker='ADA-USD', interval='1m', period_end_date=None, period_length=None):
if period_end_date == None:
period_end_date = datetime.now()
if period_length == None:
period_length = timedelta(days=5)
# cast to int to truncate the decimal
period2 = int(datetime.timestamp(period_end_date))
# find the first period via subtracting the period length
period1 = int(datetime.timestamp(period_end_date - period_length))
print(datetime.isoformat(datetime.fromtimestamp(period2)), datetime.isoformat(datetime.fromtimestamp(period1)))
params = {
'period1' : period1, # the start date (in epoch time)
'period2' : period2, # the end time (in epoch time)
'interval' : interval, # 1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 4h, 1d, 5d, 1wk, 1mo, 3mo
'events' : 'div|split|earn',
'includePrePost' : 'false',
'lang' : 'en-US',
'region' : 'US' }
headers = {'User-agent' : 'fin-backtesting-proj'}
r = requests.get("https://query2.finance.yahoo.com/v8/finance/chart/" + ticker, headers=headers, params=params)
print(r.url)
print("status_code:\t", r.status_code)
# decode the JSON response data into a Python object
try:
r.raise_for_status() # raises if error before parsing
except:
print(r.text)
last_data = pull_last_from_file()
last_data['error'] = True
return last_data
data_obj = r.json()
# get the specific data we want
if 'timestamp' not in data_obj['chart']['result'][0]:
last_data = pull_last_from_file()
last_data['error'] = True
return last_data
timestamps = data_obj['chart']['result'][0]['timestamp']
close_prices = data_obj['chart']['result'][0]['indicators']['quote'][0]['close']
# clean out null's and 0s from the data
i = 0
while i < len(timestamps):
if close_prices[i] == None or close_prices[i] == 0:
del close_prices[i]
del timestamps[i]
i -= 1
i += 1
name = data_obj['chart']['result'][0]['meta']['longName']
data = {'timestamps': timestamps, 'prices': close_prices, 'name': name, 'error': False}
# save data to file in case necessary
return data
def test():
fetch_chart_data_backtest()
test()
|