From d5804c3f38fd1ae87a079572cd2ce2aecf3f9b76 Mon Sep 17 00:00:00 2001
From: MuslemRahimi <moslem_rahimi@hotmail.de>
Date: Wed, 25 Sep 2024 00:48:32 +0200
Subject: [PATCH] bugfixing

---
 .../classification.cpython-310.pyc            | Bin 8070 -> 7502 bytes
 app/ml_models/classification.py               |   6 +++---
 app/primary_cron_job.py                       |   4 ++--
 3 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/app/ml_models/__pycache__/classification.cpython-310.pyc b/app/ml_models/__pycache__/classification.cpython-310.pyc
index 905d98d96d30bdc0ee58a09bd76c3e5486379525..3edd68048f6c356954407548a4726319757bc5c9 100644
GIT binary patch
delta 414
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delta 1044
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diff --git a/app/ml_models/classification.py b/app/ml_models/classification.py
index ecb2831..853e037 100755
--- a/app/ml_models/classification.py
+++ b/app/ml_models/classification.py
@@ -25,7 +25,7 @@ import argparse
 # Set up argument parser
 parser = argparse.ArgumentParser(description="Train and test process script.")
 parser.add_argument('--train', action='store_true', help="Set to True to run training")
-    
+
 # Parse the arguments
 args = parser.parse_args()
 
@@ -43,7 +43,7 @@ async def download_data(ticker, start_date, end_date, nth_day):
 
 
 class TrendPredictor:
-    def __init__(self, nth_day, path="weights"):
+    def __init__(self, nth_day, path="ml_models/weights"):
         self.model = RandomForestClassifier(n_estimators=500, max_depth = 10, min_samples_split=10, random_state=42, n_jobs=10)
         self.scaler = MinMaxScaler()
         self.nth_day = nth_day
@@ -148,7 +148,7 @@ class TrendPredictor:
 async def train_process(nth_day):
     tickers =['KO','WMT','BA','PLD','AZN','LLY','INFN','GRMN','VVX','EPD','PII','WY','BLMN','AAP','ON','TGT','SMG','EL','EOG','ULTA','DV','PLNT','GLOB','LKQ','CWH','PSX','SO','TGT','GD','MU','NKE','AMGN','BX','CAT','PEP','LIN','ABBV','COST','MRK','HD','JNJ','PG','SPCB','CVX','SHEL','MS','GS','MA','V','JPM','XLF','DPZ','CMG','MCD','ALTM','PDD','MNST','SBUX','AMAT','ZS','IBM','SMCI','ORCL','XLK','VUG','VTI','VOO','IWM','IEFA','PEP','WMT','XOM','V','AVGO','BIDU','GOOGL','SNAP','DASH','SPOT','NVO','META','MSFT','ADBE','DIA','PFE','BAC','RIVN','NIO','CISS','INTC','AAPL','BYND','MSFT','HOOD','MARA','SHOP','CRM','PYPL','UBER','SAVE','QQQ','IVV','SPY','EVOK','GME','F','NVDA','AMD','AMZN','TSM','TSLA']
     tickers = list(set(tickers))
-    print(len(tickers))
+    #print(len(tickers))
 
     df_train = pd.DataFrame()
     df_test = pd.DataFrame()
diff --git a/app/primary_cron_job.py b/app/primary_cron_job.py
index 54ddfd4..a56102a 100755
--- a/app/primary_cron_job.py
+++ b/app/primary_cron_job.py
@@ -635,9 +635,9 @@ schedule.every().day.at("14:00").do(run_threaded, run_cron_sector).tag('sector_j
 schedule.every(2).days.at("01:00").do(run_threaded, run_market_maker).tag('markt_maker_job')
 schedule.every(2).days.at("08:30").do(run_threaded, run_financial_score).tag('financial_score_job')
 schedule.every().saturday.at("05:00").do(run_threaded, run_ownership_stats).tag('ownership_stats_job')
-schedule.every().saturday.at("08:00").do(run_threaded, run_trend_analysis).tag('trend_analysis_job')
+schedule.every().saturday.at("06:00").do(run_threaded, run_trend_analysis).tag('trend_analysis_job')
 schedule.every().saturday.at("08:00").do(run_threaded, run_sentiment_analysis).tag('sentiment_analysis_job')
-schedule.every().saturday.at("08:00").do(run_threaded, run_price_analysis).tag('price_analysis_job')
+schedule.every().saturday.at("10:00").do(run_threaded, run_price_analysis).tag('price_analysis_job')
 
 
 schedule.every(5).minutes.do(run_threaded, run_cron_market_movers).tag('market_movers_job')