Update app.py

app.py

@@ -24,35 +24,26 @@ from utils import load_hf_dataset  # ,upload_to_hf_dataset, download_from_hf_dat
 # Get the Hugging Face API token from the environment; either set in .env file or in the environment directly in GitHub
 HF_TOKEN = os.getenv("HF_TOKEN")
 
-# Get the name of the  dataset for TradingView, GuruFocus to read from
-dataset_name_TradingView_input = os.getenv("dataset_name_TradingView_input")
+# Get the name of the  dataset for GuruFocus to read from
 dataset_name_GuruFocus_input = os.getenv("dataset_name_GuruFocus_input")
 
-
-@pn.cache()
-def get_tradingview(current_datetime):
-    # Load lastest TradingView DataSet from HuggingFace Dataset which is always america.csv
-    # download_from_hf_dataset("america.csv", dataset_name_TradingView_input, HF_TOKEN)
-    return load_hf_dataset("america.csv", HF_TOKEN, dataset_name_TradingView_input)
-
-
 @pn.cache()
 def get_gurufocus(current_datetime):
     # Load lastest GuruFocus DataSet from HuggingFace Dataset which is always GuruFocus_merged.csv
     # daily_gurufocus_DF = load_dataset(dataset_name_GuruFocus_output , data_files="GuruFocus_merged.csv", split="train" , token=HF_TOKEN ).to_pandas()
     return load_hf_dataset(
-        "GuruFocus_merged.csv", HF_TOKEN, dataset_name_GuruFocus_input
+        f"GuruFocus_merged_{current_datetime}.csv", HF_TOKEN, dataset_name_GuruFocus_input
     )
 
-
 todaydate = pn.widgets.DatePicker(
     name="End Date",  # value=datetime(2000, 1, 1),
+    value=date.today() - timedelta(days=1),
     description="Select a Date",
     end=date.today(),  # date(2023, 9, 1)
 )
 
-todaydate2 = datetime.today().strftime("%Y-%m-%d")
-df = get_gurufocus(todaydate2)
+todaydate_readcols = datetime.today().strftime("%Y-%m-%d")
+df = get_gurufocus(todaydate_readcols)
 selectedcol = pn.widgets.Select(
     name="Select Ratio", value="PEG Ratio", options=list(df.columns)
 )
@@ -72,7 +63,6 @@ ticker.value = "AAPL"
 selectedhover = "Ticker"
 hv.extension("bokeh")
 
-
 def create_plot(selectedcol, selecteditem, todaydate, selectedmethod, ticker):
     df = get_gurufocus(todaydate)
     if selectedmethod == "Mean":
@@ -105,7 +95,6 @@ def create_alert(selectedcol):
     text = f"### {selectedcol} \n {DescriptionDict[selectedcol]}"
     return pn.pane.Alert(text, alert_type="warning")
 
-
 bound_plot = pn.bind(
     create_plot,
     selectedcol=selectedcol,
@@ -114,6 +103,7 @@ bound_plot = pn.bind(
     selectedmethod=selectedmethod,
     ticker=ticker,
 )
+
 bound_alert = pn.bind(create_alert, selectedcol=selectedcol)
 pn.Column(
     pn.Row(selectedcol, selecteditem, todaydate, selectedmethod, ticker),