Update app.py

app.py

@@ -1,55 +1,80 @@
 import pandas as pd
 import numpy as np
 
-import os,io
+import os
+import io
 
 from datetime import datetime
 from datetime import timedelta
 
-import hvplot as hv
 import holoviews as hvs
 import panel as pn
-import hvplot.pandas
+# import hvplot as hv
+# import hvplot.pandas
 
 import yfinance as yf
 
 from dotenv import load_dotenv
-# from datasets import load_dataset
 
-from utils import upload_to_hf_dataset, download_from_hf_dataset, load_hf_dataset
+# from datasets import load_dataset
+from utils import load_hf_dataset  # ,upload_to_hf_dataset, download_from_hf_dataset
 
-pn.extension('bokeh', template='bootstrap')
+pn.extension("bokeh", template="bootstrap")
 
 def _extract_raw_data(ticker):
-  df = yf.Ticker(ticker)
-  return df.history(period="6mo", interval="1d").reset_index()
+    df = yf.Ticker(ticker)
+    return df.history(period="6mo", interval="1d").reset_index()
+
 
 def _transform_data(raw_data: pd.DataFrame):
-  data = raw_data[["Date", "Open", "High", "Low", "Close", "Volume"]].copy(deep=True).rename(columns={
-      "Date": "time",
-      "Open": "open",
-      "High": "high",
-      "Low": "low",
-      "Close": "close",
-      "Volume": "volume",
-  })
-  t_delta = timedelta(hours=1)
-  data['time_start'] = data.time - 9*t_delta # rectangles start
-  data['time_end'] = data.time + 9*t_delta    # rectangles end
-  data['positive'] = ((data.close - data.open)>0).astype(int)
-  return data
+    data = (
+        raw_data[["Date", "Open", "High", "Low", "Close", "Volume"]]
+        .copy(deep=True)
+        .rename(
+            columns={
+                "Date": "time",
+                "Open": "open",
+                "High": "high",
+                "Low": "low",
+                "Close": "close",
+                "Volume": "volume",
+            }
+        )
+    )
+    t_delta = timedelta(hours=1)
+    data["time_start"] = data.time - 9 * t_delta  # rectangles start
+    data["time_end"] = data.time + 9 * t_delta  # rectangles end
+    data["positive"] = ((data.close - data.open) > 0).astype(int)
+    return data
+
 
 def make_candle_stick(ticker):
-    raw_data = _extract_raw_data(ticker = ticker)
+    raw_data = _extract_raw_data(ticker=ticker)
     data = _transform_data(raw_data=raw_data)
     _delta = np.median(np.diff(data.time))
-    candlestick = hvs.Segments(data, kdims=['time', 'low', 'time', 'high']) * hvs.Rectangles(data, kdims=['time_start','open', 'time_end', 'close'], vdims=['positive'])
-    candlestick = candlestick.redim.label(Low='Values')
-    candlechart = pn.Column(candlestick.opts(hvs.opts.Rectangles(color='positive', cmap=['red', 'green'], responsive=True), hvs.opts.Segments(color='black', height=400, responsive=True , show_grid=True)) , 
-                     data.hvplot(x="time", y="volume", kind="line", responsive=True, height=200).opts( show_grid=True) )
-                    #  data.hvplot(y="volume", kind="bar", responsive=True, height=200) )
+    candlestick = hvs.Segments(
+        data, kdims=["time", "low", "time", "high"]
+    ) * hvs.Rectangles(
+        data, kdims=["time_start", "open", "time_end", "close"], vdims=["positive"]
+    )
+    candlestick = candlestick.redim.label(Low="Values")
+    candlechart = pn.Column(
+        candlestick.opts(
+            hvs.opts.Rectangles(
+                color="positive", cmap=["red", "green"], responsive=True
+            ),
+            hvs.opts.Segments(
+                color="black", height=400, responsive=True, show_grid=True
+            ),
+        ),
+        data.hvplot(
+            x="time", y="volume", kind="line", responsive=True, height=200
+        ).opts(show_grid=True),
+    )
+    #  data.hvplot(y="volume", kind="bar", responsive=True, height=200) )
     return candlechart
 
+
 # Function to convert DataFrame to CSV
 def get_csv(df):
     sio = io.StringIO()
@@ -57,10 +82,11 @@ def get_csv(df):
     sio.seek(0)
     return sio
 
+
 # Function to convert the 'Ticker' column to a comma-separated string in a text file
 def get_text(df):
-    tickers = df['Ticker'].tolist()
-    tickers_str = ','.join(tickers)
+    tickers = df["Ticker"].tolist()
+    tickers_str = ",".join(tickers)
     sio = io.StringIO()
     sio.write(tickers_str)
     sio.seek(0)
@@ -71,158 +97,340 @@ def get_text(df):
 load_dotenv()
 
 # 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')
+HF_TOKEN = os.getenv("HF_TOKEN")
 
 # Get the name of the GuruFocus dataset for TradingView, Finviz, MarketBeat and TipRanks to read from
-dataset_name_BeatingMarket_input = os.getenv('dataset_name_BeatingMarket_input')
-dataset_name_TradingView_input = os.getenv('dataset_name_TradingView_input')
-dataset_name_GuruFocus_input = os.getenv('dataset_name_GuruFocus_input')
-dataset_name_FinViz_input = os.getenv('dataset_name_FinViz_input')
-dataset_name_TipRanks_input = os.getenv('dataset_name_TipRanks_input')
-
-
-current_datetime = datetime.now().strftime("%Y-%m-%d")    
+dataset_name_BeatingMarket_input = os.getenv("dataset_name_BeatingMarket_input")
+dataset_name_TradingView_input = os.getenv("dataset_name_TradingView_input")
+dataset_name_GuruFocus_input = os.getenv("dataset_name_GuruFocus_input")
+dataset_name_FinViz_input = os.getenv("dataset_name_FinViz_input")
+dataset_name_TipRanks_input = os.getenv("dataset_name_TipRanks_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)
+    # 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_marketbeat(current_datetime):
-  return load_hf_dataset("beatingmarket.csv", HF_TOKEN, dataset_name_BeatingMarket_input)
+    return load_hf_dataset(
+        "beatingmarket.csv", HF_TOKEN, dataset_name_BeatingMarket_input
+    )
+
 
 @pn.cache()
 def get_gurufocus(current_datetime):
-  #Rading gurufocus from github action pipeline
-  # daily_gurufocus_csvfile = f"https://raw.githubusercontent.com/alirezax2/GurusFocusCrawl/main/gurufocusuruFocus_merged_{current_datetime}.csv"
-  # daily_gurufocus_DF = pd.read_csv(daily_gurufocus_csvfile)
-  # 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)
-  
+    # 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
+    )
+
+
 @pn.cache()
 def get_finviz(current_datetime):
-   return load_hf_dataset("FinViz.csv", HF_TOKEN, dataset_name_FinViz_input)
+    # Load lastest FinViz DataSet from HuggingFace Dataset which is always FinViz.csv
+    return load_hf_dataset("FinViz.csv", HF_TOKEN, dataset_name_FinViz_input)
+
 
 @pn.cache()
 def get_tipranks(current_datetime):
-  return load_hf_dataset("tipranks.csv", HF_TOKEN, dataset_name_TipRanks_input)
+    # Load lastest TipRanks DataSet from HuggingFace Dataset which is always tipranks.csv
+    return load_hf_dataset("tipranks.csv", HF_TOKEN, dataset_name_TipRanks_input)
 
 
-#Reading gurufocus,finviz from local crawling pipeline; Need to update github action to merge gurufocus daily with monthly tiprank
+# Reading gurufocus,finviz from crawling pipelines with GitHub Action
+current_datetime = datetime.now().strftime("%Y-%m-%d")
 daily_gurufocus_DF = get_gurufocus(current_datetime)
 daily_finviz_DF = get_finviz(current_datetime)
 daily_marketbeat = get_marketbeat(current_datetime)
 monthly_tiprank_DF = get_tipranks(current_datetime)
-monthly_tiprank_DF = monthly_tiprank_DF[['Ticker','SmartScore','Market Capitalization','Sector','Industry']]
-
 
-daily_finviz_DF['FinVizPrice']  = pd.to_numeric(daily_finviz_DF['Price'], errors='coerce').fillna(0).astype(float)
-daily_finviz_DF['FinVizTarget']  = pd.to_numeric(daily_finviz_DF['Target Price'], errors='coerce').fillna(0).astype(float)
-daily_finviz_DF['FinVizTargetpercent'] = (100*(daily_finviz_DF['FinVizTarget']-daily_finviz_DF['FinVizPrice'])/daily_finviz_DF['FinVizPrice']).round(2)
-daily_finviz_DF_filtered = daily_finviz_DF[['Ticker','Price','FinVizTarget','FinVizTargetpercent']]
+# TipRanks
+monthly_tiprank_DF = monthly_tiprank_DF[["Ticker", "SmartScore"]]
 
-#Merging tipranks with Gurufocus
-DFgurufocus = daily_gurufocus_DF[['Ticker' , 'GFValue']] # , 'GFValuediff']]
+# FinViz
+daily_finviz_DF["FinVizPrice"] = (
+    pd.to_numeric(daily_finviz_DF["Price"], errors="coerce").fillna(0).astype(float)
+)
+daily_finviz_DF["FinVizTarget"] = (
+    pd.to_numeric(daily_finviz_DF["Target Price"], errors="coerce")
+    .fillna(0)
+    .astype(float)
+)
+daily_finviz_DF["FinVizTargetpercent"] = (
+    100
+    * (daily_finviz_DF["FinVizTarget"] - daily_finviz_DF["FinVizPrice"])
+    / daily_finviz_DF["FinVizPrice"]
+).round(2)
+daily_finviz_DF_filtered = daily_finviz_DF[
+    ["Ticker", "Price", "FinVizTarget", "FinVizTargetpercent"]
+]
+
+# Merging tipranks with Gurufocus
+DFgurufocus = daily_gurufocus_DF[
+    ["Ticker", "GFValue", "Market Capitalization", "Sector", "Industry"]
+]  # , 'GFValuediff']]
 DFmerge_tipranks_gurufocus = DFgurufocus.merge(monthly_tiprank_DF)
 
-#Merging Finviz with Merged last one
+# Merging Finviz with Merged last one
 DFmerge_tipranks_gurufocus = DFmerge_tipranks_gurufocus.merge(daily_finviz_DF_filtered)
 
-print(daily_marketbeat.columns)
 # ['Ticker', 'AverageTarget', 'MaxTarget', 'LowTarget', 'CurrentPrice']
-daily_marketbeat['AllTargetsAbovePrice'] = ((daily_marketbeat['MaxTarget'] > daily_marketbeat['CurrentPrice']) & 
-                       (daily_marketbeat['LowTarget'] > daily_marketbeat['CurrentPrice']) & 
-                       (daily_marketbeat['AverageTarget'] > daily_marketbeat['CurrentPrice'])).astype(int)
+daily_marketbeat["MarketBeat"] = (
+    (daily_marketbeat["MaxTarget"] > daily_marketbeat["CurrentPrice"])
+    & (daily_marketbeat["LowTarget"] > daily_marketbeat["CurrentPrice"])
+    & (daily_marketbeat["AverageTarget"] > daily_marketbeat["CurrentPrice"])
+).astype(int)
 
-#Merging daily_marketbeat with Merged last one
+# Merging daily_marketbeat with Merged last one
 DFmerge_tipranks_gurufocus = DFmerge_tipranks_gurufocus.merge(daily_marketbeat)
 
-if 'Price' in DFmerge_tipranks_gurufocus.columns and 'GFValue' in DFmerge_tipranks_gurufocus.columns:
-  DFmerge_tipranks_gurufocus['GFValuepercent'] = 100* ( DFmerge_tipranks_gurufocus['GFValue'] - DFmerge_tipranks_gurufocus['Price']) / DFmerge_tipranks_gurufocus['Price']
-  DFmerge_tipranks_gurufocus['GFValuepercent'] = DFmerge_tipranks_gurufocus['GFValuepercent'].round(2)
-  DFmerge_tipranks_gurufocus['Market Capitalization'] = DFmerge_tipranks_gurufocus['Market Capitalization'] / 1e9
-  DFmerge_tipranks_gurufocus['MarketCap'] = DFmerge_tipranks_gurufocus['Market Capitalization'].round(1)
-  DFmerge_tipranks_gurufocus = DFmerge_tipranks_gurufocus.drop(columns=['Market Capitalization'])
-  DFmerge_tipranks_gurufocus = DFmerge_tipranks_gurufocus[['Ticker', 'Sector', 'Industry' , 'MarketCap' , 'SmartScore', 'Price' , 'GFValue' , 'GFValuepercent' , 'FinVizTarget','FinVizTargetpercent']]
-
-
-#widget
-ticker = pn.widgets.AutocompleteInput(name='Ticker', options=list(DFmerge_tipranks_gurufocus.Ticker) , placeholder='Write Ticker here همین جا',value='ALL', restrict=False)
-SmartScore = pn.widgets.EditableRangeSlider(name='Smart Score', start=0, end=10, value=(9, 10), step=1)
-Industry = pn.widgets.CheckBoxGroup( name='Select Industry', value=list(set(DFmerge_tipranks_gurufocus.Industry)), options=list(set(DFmerge_tipranks_gurufocus.Industry)), inline=True)
-Sector = pn.widgets.MultiSelect( name='Select Sector', value=list(set(DFmerge_tipranks_gurufocus.Sector)), options=list(set(DFmerge_tipranks_gurufocus.Sector)) )#, inline=False)
-GFValuepercent = pn.widgets.FloatSlider(name='GF Value %', start=-100, end=100, step=1, value=12.0)
-FinVizTargetpercent = pn.widgets.FloatSlider(name='FinViz Target %', start=-100, end=100, step=1, value=12.0)
-MarketCap = pn.widgets.FloatSlider(name='Market Capital (B$)', start=0, end=1000, step=1, value=10)
-MarketBeat_radio_group = pn.widgets.RadioButtonGroup(name='MarketBeat', options=['Default', 'Above all Targets'], button_type='success')
+if (
+    "Price" in DFmerge_tipranks_gurufocus.columns
+    and "GFValue" in DFmerge_tipranks_gurufocus.columns
+):
+    DFmerge_tipranks_gurufocus["GFValuepercent"] = (
+        100
+        * (DFmerge_tipranks_gurufocus["GFValue"] - DFmerge_tipranks_gurufocus["Price"])
+        / DFmerge_tipranks_gurufocus["Price"]
+    )
+    DFmerge_tipranks_gurufocus["GFValuepercent"] = DFmerge_tipranks_gurufocus[
+        "GFValuepercent"
+    ].round(2)
+    DFmerge_tipranks_gurufocus["Market Capitalization"] = (
+        DFmerge_tipranks_gurufocus["Market Capitalization"] / 1e9
+    )
+    DFmerge_tipranks_gurufocus["MarketCap"] = DFmerge_tipranks_gurufocus[
+        "Market Capitalization"
+    ].round(1)
+    DFmerge_tipranks_gurufocus = DFmerge_tipranks_gurufocus.drop(
+        columns=["Market Capitalization"]
+    )
+    DFmerge_tipranks_gurufocus = DFmerge_tipranks_gurufocus[
+        [
+            "Ticker",
+            "Sector",
+            "Industry",
+            "MarketCap",
+            "SmartScore",
+            "Price",
+            "GFValue",
+            "GFValuepercent",
+            "FinVizTarget",
+            "FinVizTargetpercent",
+            "MarketBeat",
+        ]
+    ]
+
+
+# widget
+ticker = pn.widgets.AutocompleteInput(
+    name="Ticker",
+    options=list(DFmerge_tipranks_gurufocus.Ticker),
+    placeholder="Write Ticker here همین جا",
+    value="ALL",
+    restrict=False,
+)
+SmartScore = pn.widgets.EditableRangeSlider(
+    name="Smart Score", start=0, end=10, value=(9, 10), step=1
+)
+Industry = pn.widgets.CheckBoxGroup(
+    name="Select Industry",
+    value=list(set(DFmerge_tipranks_gurufocus.Industry)),
+    options=list(set(DFmerge_tipranks_gurufocus.Industry)),
+    inline=True,
+)
+Sector = pn.widgets.MultiSelect(
+    name="Select Sector",
+    value=list(set(DFmerge_tipranks_gurufocus.Sector)),
+    options=list(set(DFmerge_tipranks_gurufocus.Sector)),
+)  # , inline=False)
+GFValuepercent = pn.widgets.FloatSlider(
+    name="GF Value %", start=-100, end=100, step=1, value=12.0
+)
+FinVizTargetpercent = pn.widgets.FloatSlider(
+    name="FinViz Target %", start=-100, end=100, step=1, value=12.0
+)
+MarketCap = pn.widgets.FloatSlider(
+    name="Market Capital (B$)", start=0, end=1000, step=1, value=10
+)
+MarketBeat_radio_group = pn.widgets.RadioButtonGroup(
+    name="MarketBeat",
+    options=["Default Targets", "Above all Targets"],
+    button_type="success",
+    value="Above all Targets",
+)
 
 # Create a file download link
 download_button_GuruFocus = pn.widgets.FileDownload(
-    filename=f'GuruFocus_merged_{current_datetime}.csv',
-    callback=pn.bind(get_csv,daily_gurufocus_DF),
-    button_type='primary',
-    label='Download GuruFocus', width=250
+    filename=f"GuruFocus_merged_{current_datetime}.csv",
+    callback=pn.bind(get_csv, daily_gurufocus_DF),
+    button_type="primary",
+    label="Download GuruFocus",
+    width=250,
 )
 
 download_button_FinViz = pn.widgets.FileDownload(
-    filename=f'FinViz_{current_datetime}.csv',
-    callback=pn.bind(get_csv,daily_finviz_DF),
-    button_type='primary',
-    label='Download FinViz', width=250
+    filename=f"FinViz_{current_datetime}.csv",
+    callback=pn.bind(get_csv, daily_finviz_DF),
+    button_type="primary",
+    label="Download FinViz",
+    width=250,
 )
 
 download_button_MarketBeat = pn.widgets.FileDownload(
-    filename=f'MarketBeat_{current_datetime}.csv',
-    callback=pn.bind(get_csv,daily_marketbeat),
-    button_type='warning',
-    label='Download MarketBeat', width=250
+    filename=f"MarketBeat_{current_datetime}.csv",
+    callback=pn.bind(get_csv, daily_marketbeat),
+    button_type="warning",
+    label="Download MarketBeat",
+    width=250,
 )
 
 download_button_TipRanks = pn.widgets.FileDownload(
-    filename=f'TipRanks_{current_datetime}.csv',
-    callback=pn.bind(get_csv,monthly_tiprank_DF),
-    button_type='warning',
-    label='Download TipRanks', width=250
-)
-
-png_pane = pn.pane.GIF('https://tuozi.vip/shqu/wordpress/wp-content/themes/CorePress/static/img/loading.gif', width=200) #, height=150)
-def get_DF(DF,ticker,SmartScore,GFValuepercent, FinVizTargetpercent, Sector,MarketCap,MarketBeat):
-  if ticker and ticker!="ALL":
-    table1 = pn.widgets.Tabulator(DF.query("Ticker == @ticker"), height=200, widths=200, show_index=False)
-    chart1 = make_candle_stick(ticker)
-    return pn.Column(table1,chart1)
-  else:
-    if MarketBeat == 0:
-      tabulator = pn.widgets.Tabulator( DF.query("SmartScore>=@SmartScore[0] & SmartScore <= @SmartScore[1] & GFValuepercent>=@GFValuepercent & FinVizTargetpercent>@FinVizTargetpercent & Sector in @Sector & MarketCap>@MarketCap & AllTargetsAbovePrice==1"), height=800, widths=200, show_index=False ,theme='modern')
-    else:
-      tabulator = pn.widgets.Tabulator( DF.query("SmartScore>=@SmartScore[0] & SmartScore <= @SmartScore[1] & GFValuepercent>=@GFValuepercent & FinVizTargetpercent>@FinVizTargetpercent & Sector in @Sector & MarketCap>@MarketCap"), height=800, widths=200, show_index=False ,theme='modern')
-    tabulator.disabled = True
-    print(tabulator.disabled)
-    print(80*'***')
-    return tabulator
-  
-def get_DF_filter(DF,ticker,SmartScore,GFValuepercent, FinVizTargetpercent, Sector,MarketCap):
-  return DF.query("SmartScore>=@SmartScore[0] & SmartScore <= @SmartScore[1] & GFValuepercent>=@GFValuepercent & FinVizTargetpercent>@FinVizTargetpercent & Sector in @Sector & MarketCap>@MarketCap")
+    filename=f"TipRanks_{current_datetime}.csv",
+    callback=pn.bind(get_csv, monthly_tiprank_DF),
+    button_type="warning",
+    label="Download TipRanks",
+    width=250,
+)
 
-download_button_Filter = pn.widgets.FileDownload(
-    filename=f'Filter_{current_datetime}.csv',
-    callback=pn.bind(get_csv,pn.bind(get_DF_filter, DF=DFmerge_tipranks_gurufocus,ticker=ticker,SmartScore=SmartScore,GFValuepercent=GFValuepercent, FinVizTargetpercent=FinVizTargetpercent, Sector=Sector ,MarketCap=MarketCap) ),
-    button_type='danger',
-    label='Download your Filter', width=250
 
+def get_DF_filter(
+    DF, ticker, SmartScore, GFValuepercent, FinVizTargetpercent, Sector, MarketCap
+):
+    return DF.query(
+        "SmartScore>=@SmartScore[0] & SmartScore <= @SmartScore[1] & GFValuepercent>=@GFValuepercent & FinVizTargetpercent>@FinVizTargetpercent & Sector in @Sector & MarketCap>@MarketCap"
+    )
+
+download_button_Filter = pn.widgets.FileDownload(
+    filename=f"Filter_{current_datetime}.csv",
+    callback=pn.bind(
+        get_csv,
+        pn.bind(
+            get_DF_filter,
+            DF=DFmerge_tipranks_gurufocus,
+            ticker=ticker,
+            SmartScore=SmartScore,
+            GFValuepercent=GFValuepercent,
+            FinVizTargetpercent=FinVizTargetpercent,
+            Sector=Sector,
+            MarketCap=MarketCap,
+        ),
+    ),
+    button_type="danger",
+    label="Download your Filter",
+    width=250,
 )
 
 download_button_watchlist = pn.widgets.FileDownload(
-    filename=f'watchlist_{current_datetime}.txt',
-    callback=pn.bind(get_text,pn.bind(get_DF_filter, DF=DFmerge_tipranks_gurufocus,ticker=ticker,SmartScore=SmartScore,GFValuepercent=GFValuepercent, FinVizTargetpercent=FinVizTargetpercent, Sector=Sector ,MarketCap=MarketCap) ),
-    button_type='success',
-    label='Download Watchlist', width=250
+    filename=f"watchlist_{current_datetime}.txt",
+    callback=pn.bind(
+        get_text,
+        pn.bind(
+            get_DF_filter,
+            DF=DFmerge_tipranks_gurufocus,
+            ticker=ticker,
+            SmartScore=SmartScore,
+            GFValuepercent=GFValuepercent,
+            FinVizTargetpercent=FinVizTargetpercent,
+            Sector=Sector,
+            MarketCap=MarketCap,
+        ),
+    ),
+    button_type="success",
+    label="Download Watchlist",
+    width=250,
 )
 
-pn.extension('tabulator')
-bound_plot = pn.bind(get_DF, DF=DFmerge_tipranks_gurufocus,ticker=ticker,SmartScore=SmartScore,GFValuepercent=GFValuepercent, FinVizTargetpercent=FinVizTargetpercent, Sector=Sector ,MarketCap=MarketCap,MarketBeat=MarketBeat_radio_group)
+png_pane = pn.pane.GIF(
+    "https://tuozi.vip/shqu/wordpress/wp-content/themes/CorePress/static/img/loading.gif",
+    width=200,
+)  # , height=150)
+png_pane2 = pn.pane.GIF(
+    "https://www.mywallstreetadvisor.com/_next/image?url=%2FMyWallStreetAdvisorLOGO.png&w=64&q=75",
+    width=50,
+)  # , height=150)
+
+
+def get_DF(
+    DF,
+    ticker,
+    SmartScore,
+    GFValuepercent,
+    FinVizTargetpercent,
+    Sector,
+    MarketCap,
+    MarketBeat,
+):
+    if ticker and ticker != "ALL":
+        table1 = pn.widgets.Tabulator(
+            DF.query("Ticker == @ticker"), height=200, widths=200, show_index=False
+        )
+        table1.disabled = True
+        chart1 = make_candle_stick(ticker)
+        return pn.Column(table1, chart1)
+    else:
+        if MarketBeat == "Above all Targets":
+            tabulator = pn.widgets.Tabulator(
+                DF.query(
+                    "SmartScore>=@SmartScore[0] & SmartScore <= @SmartScore[1] & GFValuepercent>=@GFValuepercent & FinVizTargetpercent>@FinVizTargetpercent & Sector in @Sector & MarketCap>@MarketCap & MarketBeat==1"
+                ),
+                height=800,
+                widths=200,
+                show_index=False,
+                theme="modern",
+            )
+        else:
+            tabulator = pn.widgets.Tabulator(
+                DF.query(
+                    "SmartScore>=@SmartScore[0] & SmartScore <= @SmartScore[1] & GFValuepercent>=@GFValuepercent & FinVizTargetpercent>@FinVizTargetpercent & Sector in @Sector & MarketCap>@MarketCap"
+                ),
+                height=800,
+                widths=200,
+                show_index=False,
+                theme="modern",
+            )
+        tabulator.disabled = True
+        return tabulator
+
+
+pn.extension("tabulator")
+bound_plot = pn.bind(
+    get_DF,
+    DF=DFmerge_tipranks_gurufocus,
+    ticker=ticker,
+    SmartScore=SmartScore,
+    GFValuepercent=GFValuepercent,
+    FinVizTargetpercent=FinVizTargetpercent,
+    Sector=Sector,
+    MarketCap=MarketCap,
+    MarketBeat=MarketBeat_radio_group,
+)
 
-pn.Column(pn.Row(pn.Column(ticker,SmartScore,GFValuepercent, FinVizTargetpercent, MarketCap, MarketBeat_radio_group, png_pane, download_button_GuruFocus,download_button_FinViz , download_button_MarketBeat, download_button_TipRanks, download_button_Filter, download_button_watchlist),bound_plot)).servable(title="Fair Value Ranking - Merged Gurufocus & Tipranks & FinViz & MorningStars & MarketBeat")
+pn.Column(
+    pn.Row(
+        pn.Column(
+            pn.Row(png_pane2, align="center"),
+            ticker,
+            SmartScore,
+            GFValuepercent,
+            FinVizTargetpercent,
+            MarketCap,
+            pn.Row(MarketBeat_radio_group, align="start"),
+            png_pane,
+            download_button_GuruFocus,
+            download_button_FinViz,
+            download_button_MarketBeat,
+            download_button_TipRanks,
+            download_button_Filter,
+            download_button_watchlist,
+        ),
+        pn.Row(bound_plot, align="center"),
+    )
+).servable(
+    title="Fair Value Ranking - Merged Gurufocus & Tipranks & FinViz & MorningStars & MarketBeat"
+)