attemp using the alpaca api for history data

1 files changed, 79 insertions, 8 deletions

diff --git a/api.py b/api.py
index 48e8f72..2bc5724 100644
--- a/api.py
+++ b/api.py
@@ -1,6 +1,7 @@
 import requests
 import json
-from datetime import date, date, datetime, timedelta
+from datetime import datetime, timedelta, timezone
+import pytz
 
 # helper function to pull most recent chart data on failure
 def pull_last_from_file():
@@ -20,14 +21,14 @@ 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='1y', interval='1d'):
+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://query2.finance.yahoo.com/v8/finance/chart/" + ticker, headers=headers, params=params)
+    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)
@@ -62,7 +63,7 @@ def fetch_chart_data(ticker, period='1y', interval='1d'):
     name = data_obj['chart']['result'][0]['meta']['longName']
 
     data = {'timestamps': timestamps, 'prices': close_prices, 'name': name, 'error': False}
-    update_last_file(data)
+    # update_last_file(data)
     # save data to file in case necessary
     return data
 
@@ -72,11 +73,82 @@ 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='ADA-USD', interval='1m', period_end_date=None, period_length=None):
+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()
+        period_end_date = datetime.now().astimezone(pytz.timezone('UTC'))
     if period_length == None:
-        period_length = timedelta(days=8)
+        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))
@@ -130,7 +202,6 @@ def fetch_chart_data_backtest(ticker='ADA-USD', interval='1m', period_end_date=N
     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