Added sessionstate

SessionState.py

@@ -0,0 +1,100 @@
+"""Hack to add per-session state to Streamlit.
+    Usage
+    -----
+    >>> import SessionState
+    >>>
+    >>> session_state = SessionState.get(user_name='', favorite_color='black')
+    >>> session_state.user_name
+    ''
+    >>> session_state.user_name = 'Mary'
+    >>> session_state.favorite_color
+    'black'
+    Since you set user_name above, next time your script runs this will be the
+    result:
+    >>> session_state = get(user_name='', favorite_color='black')
+    >>> session_state.user_name
+    'Mary'
+"""
+from streamlit.script_runner import get_script_run_ctx as get_report_ctx
+from streamlit.server import Server
+
+
+class SessionState(object):
+    def __init__(self, **kwargs):
+        """A new SessionState object.
+        Parameters
+        ----------
+        **kwargs : any
+            Default values for the session state.
+        Example
+        -------
+        >>> session_state = SessionState(user_name='', favorite_color='black')
+        >>> session_state.user_name = 'Mary'
+        ''
+        >>> session_state.favorite_color
+        'black'
+        """
+        for key, val in kwargs.items():
+            setattr(self, key, val)
+
+
+def get(**kwargs):
+    """Gets a SessionState object for the current session.
+    Creates a new object if necessary.
+    Parameters
+    ----------
+    **kwargs : any
+        Default values you want to add to the session state, if we're creating a
+        new one.
+    Example
+    -------
+    >>> session_state = get(user_name='', favorite_color='black')
+    >>> session_state.user_name
+    ''
+    >>> session_state.user_name = 'Mary'
+    >>> session_state.favorite_color
+    'black'
+    Since you set user_name above, next time your script runs this will be the
+    result:
+    >>> session_state = get(user_name='', favorite_color='black')
+    >>> session_state.user_name
+    'Mary'
+    """
+    # Hack to get the session object from Streamlit.
+
+    ctx = get_report_ctx()
+
+    this_session = None
+
+    current_server = Server.get_current()
+    if hasattr(current_server, '_session_infos'):
+        # Streamlit < 0.56
+        session_infos = Server.get_current()._session_infos.values()
+    else:
+        session_infos = Server.get_current()._session_info_by_id.values()
+
+    for session_info in session_infos:
+        s = session_info.session
+        if (
+            # Streamlit < 0.54.0
+            (hasattr(s, '_main_dg') and s._main_dg == ctx.main_dg)
+            or
+            # Streamlit >= 0.54.0
+            (not hasattr(s, '_main_dg') and s.enqueue == ctx.enqueue)
+            or
+            # Streamlit >= 0.65.2
+            (not hasattr(s, '_main_dg') and s._uploaded_file_mgr == ctx.uploaded_file_mgr)
+        ):
+            this_session = s
+
+    if this_session is None:
+        raise RuntimeError(
+            "Oh noes. Couldn't get your Streamlit Session object. "
+            'Are you doing something fancy with threads?')
+
+    # Got the session object! Now let's attach some state into it.
+
+    if not hasattr(this_session, '_custom_session_state'):
+        this_session._custom_session_state = SessionState(**kwargs)
+
+    return this_session._custom_session_state

app.py

@@ -1,5 +1,6 @@
 import time
 import warnings
+# import SessionState
 import numpy as np
 import pandas as pd
 import datetime as dt
@@ -7,19 +8,22 @@ import streamlit as st
 import tensorflow as tf
 import pandas_datareader as pdr
 import matplotlib.pyplot as plt
+from PIL import Image
 from sklearn.preprocessing import MinMaxScaler
 from tensorflow.keras.models import load_model
 
 # warnings.filterwarnings('ignore')
 # plt.style.use('fivethirtyeight')
 
+im = Image.open('bitcoin.png')
+
 st.set_page_config(
         page_title="FANG Stock Prediction",
-        page_icon=":currency:",
+        page_icon=im,
         layout="wide"
     )
 
-st.write("# Welcome to FANG Stock Prediction Dashboard :bitcoin:")
+st.write("# Welcome to FANG Stock Prediction Dashboard :man: :coffee:")
 
 company_ticker = ['FB', 'AAPL', 'TSLA', 'GOOG', 'NVDA']
 
@@ -86,7 +90,7 @@ elif selection == 'Actual Stock Price and Model Prediction':
   st.line_chart(data_GOOG.filter(['Adj Close'])).add_rows(valid)
   st.table(valid)
 
-real_data = [model_inputs[len(model_inputs) + 2 - prediction_days:len(model_inputs) + 2, 0]]
+real_data = [model_inputs[len(model_inputs) + 1 - prediction_days:len(model_inputs) + 1, 0]]
 real_data = np.array(real_data)
 real_data = np.reshape(real_data, (real_data.shape[0], real_data.shape[1], 1))