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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()
if period_length == None:
period_length = timedelta(days=5)
period_end_date = period_end_date.astimezone(pytz.timezone('UTC'))
# 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'].replace("Z", "")).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=8)
# 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()
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