work on expanding api to use periods then create the infrastructure for random trials

1 files changed, 77 insertions, 5 deletions

diff --git a/simulate.py b/simulate.py
index 8d69b3d..7b01c21 100644
--- a/simulate.py
+++ b/simulate.py
@@ -1,8 +1,10 @@
 from algo import Algo
 from ema_algo import Ema_Algo
-from api import fetch_chart_data
+from api import fetch_chart_data, fetch_chart_data_backtest
 import datetime
 import json
+import random
+import os
 
 """
 Function that takes in data and returns a buy, sell, or hold singal per interval
@@ -67,7 +69,78 @@ def backtest_algo(algo : Algo, timestamps, prices, init_offset=5, starting_money
     # store all algo name, buy, sell, price data, timestamps, into a json so it can be viewed as a trial
     # caluclate some metrics (NOW: only how much money gained, how many trades, trades per day... etc)
 
-    pass
+ticker_bank = ['BTC-USD', 'ADA-USD', 'ETH-USD', 'ETC-USD', 'DOGE-USD']
+year_bank = [2020, 2021, 2022, 2023, 2024, 2025]
+# time_bank = [0]
+# max_seconds = 24 * 60 * 60
+# timedelta(seconds=rand_second) + datetime(created with 0 time)
+
+"""
+Runs N trials with random parameters
+"""
+def run_batch(batch_name, algo, num_trials=100):
+    i = 1
+    while i <= num_trials:
+        # pick a random set of parameters
+        rand_ticker = ticker_bank[random.randint(0, len(ticker_bank) - 1)]
+        rand_year = year_bank[random.randint(0, len(year_bank) - 1)]
+        rand_day = random.randint(1, 31)
+        rand_month = random.randint(1, 12)
+
+        # ensure the date is valid
+        rand_date = None
+        try: 
+            rand_date = datetime.datetime(rand_year, rand_month, rand_day)
+        except ValueError:
+            # date creation failed
+            continue
+
+        # ensure date is not in future
+        curr_date = datetime.datetime.now()
+        if rand_date > curr_date:
+            continue
+        
+        # pull chart data for these params and run the algo
+        data = fetch_chart_data_backtest(rand_ticker, '1m', rand_date)
+        results = backtest_algo(algo, data['timestamps'], data['prices'], 13)
+
+        # TODO: make this generalized
+        url_params = {
+            "ticker" : rand_ticker,
+            "period" : '8d',
+            "interval" : '1m',
+        }
+        # store the results in into a file
+        trial_data = {
+            "chart_data" : data,
+            "url_params" : url_params,
+            "backtest_results" : results
+        }
+
+        # make a new directory for the batch
+        path = f'batches_{algo.name}/{batch_name}'
+        if i == 1:
+            print(path)
+            try:
+                os.makedirs(path)
+            except PermissionError:
+                print(f"Permission denied: Unable to create {path}.")
+                return
+            except Exception as e:
+                print(f"An error occurred: {e}")
+                return
+
+        percent_gain = results['percent_gain']
+        date_format = datetime.datetime.isoformat(rand_date)
+        file_name = f'{path}/{percent_gain}_{rand_ticker}_{date_format}.json'
+        fd = open(file_name, 'w')
+        fd.write(json.dumps(trial_data))
+        fd.close()
+
+        # increment trial num
+        i += 1
+
+run_batch('test', Ema_Algo(), 5)
 
 def test():
     print("MAIN simulate.py")
@@ -79,7 +152,8 @@ def test():
     interval = '1m'
 
     # get data
-    data = fetch_chart_data(ticker, period, interval)
+    # data = fetch_chart_data(ticker, period, interval)
+    data = fetch_chart_data_backtest()
     print(data.keys())
 
     url_params = {
@@ -101,5 +175,3 @@ def test():
     fd = open('bt-recent.json', 'w')
     fd.write(json.dumps(trial_data))
     fd.close()
-
-test()
\ No newline at end of file