app.py

import streamlit as st
from pytezos import pytezos
import pandas as pd

pytezos = pytezos.using(shell = 'https://rpc.tzkt.io/ghostnet', key='edsk3MrRkoidY2SjEgufvi44orvyjxgZoy4LhaJNTNcddWykW6SssL')
contract = pytezos.contract('KT1KvCVKiZhkPG8s9CCoxW3r135phk2HhZUV')

def welcome():
    return "Welcome To Decentralised Medical Records"

def addUser():
  name = st.text_input("Enter Full Name of the Patient")
  email = st.text_input("Enter Email of the Patient")
  number = st.number_input("Enter the Contact Number", step=1, min_value=1)
  age = st.number_input("Enter Age", step=1, min_value=18)
  gender = st.radio("Enter Gender", ('Male', 'Female'))
  #Hid = st.text_input("Enter your Unique Hospital Id")
  #hospital=st.text_input("Enter the Hospital details")


  if st.button("Register Patient"):
    a = pytezos.using(shell = 'https://rpc.tzkt.io/ghostnet', key='edsk3MrRkoidY2SjEgufvi44orvyjxgZoy4LhaJNTNcddWykW6SssL')
    contract = a.contract('KT1KvCVKiZhkPG8s9CCoxW3r135phk2HhZUV')

    contract.addUser(email = email, name = name, age = age, gender = gender,  number = number).with_amount(0).as_transaction().fill().sign().inject()   


def ViewPatientRecord():
  Hid = st.text_input("Enter Unique Hospital Id of Patient")
  if st.button("View Records"):
    usds = pytezos.using(shell = 'https://rpc.tzkt.io/ghostnet').contract('KT1KvCVKiZhkPG8s9CCoxW3r135phk2HhZUV')
    #print (usds.storage())#debug
    #print(list(usds.storage().keys())[0])

    #if email is in storage... print record
    if Hid in list(usds.storage().keys()):
        st.text(usds.storage())
        #print(usds.storage())
        #st.text(list(usds.storage().keys())[0])
        #st.text(list(usds.storage().values()))
    else: 
        st.text('Not Found')
    #st.text(usds.storage[email]['Record']())
    
    
####################WIDGETS START ##################################

def filters_widgets(df, columns=None, allow_single_value_widgets=False):
    # Parse the df and get filter widgets based for provided columns
    if not columns: #if columns not provided, use all columns to create widgets
        columns=df.columns.tolist()
    if allow_single_value_widgets:
        threshold=0
    else:
        threshold=1
    widget_dict = {}
    filter_widgets = st.container()
    filter_widgets.warning(
        "After selecting filters press the 'Apply Filters' button at the bottom.")
    if not allow_single_value_widgets:
        filter_widgets.markdown("Only showing columns that contain more than 1 unique value.")
    with filter_widgets.form(key="data_filters"):
        not_showing = [] 
        for y in df[columns]:
            if str(y) in st.session_state: #update value from session state if exists
                selected_opts = st.session_state[str(y)]
            else: #if doesnt exist use all values as defaults
                selected_opts = df[y].unique().tolist()
            if len(df[y].unique().tolist()) > threshold: #checks if above threshold
                widget_dict[y] = st.multiselect(
                    label=str(y),
                    options=df[y].unique().tolist(),
                    default=selected_opts,
                    key=str(y),
                )
            else:#if doesnt pass threshold
                not_showing.append(y)
        if not_showing:#if the list is not empty, show this warning
            st.warning(
                f"Not showing filters for {' '.join(not_showing)} since they only contain one unique value."
            )
        submit_button = st.form_submit_button("Apply Filters")
    #reset button to return all unselected values back
    reset_button = filter_widgets.button(
        "Reset All Filters",
        key="reset_buttons",
        on_click=reset_filter_widgets_to_default,
        args=(df, columns),
    )
    filter_widgets.warning(
        "Dont forget to apply filters by pressing 'Apply Filters' at the bottom."
    )    

def reset_filter_widgets_to_default(df, columns):
    for y in df[columns]:
        if str(y) in st.session_state:
            del st.session_state[y]
            
####################WIDGETS END##################################
               
def main():
    
    st.set_page_config(page_title="Decentralised Health Vaccine Records")
   
    st.title("Blockchain Based Medical Records")
    st.markdown(
        """<div style="background-color:#e1f0fa;padding:10px">
                    <h1 style='text-align: center; color: #304189;font-family:Helvetica'><strong>
                    Vaccine Data </strong></h1></div><br>""",
        unsafe_allow_html=True,
    )


    st.markdown(
        """<p style='text-align: center;font-family:Helvetica;'>
                   This project greatly decreases any chances of misuse or the manipulation of the medical Records</p>""",
        unsafe_allow_html=True,
    )

    st.sidebar.title("Choose your entry point")
    st.sidebar.markdown("Select the entry point accordingly:")

    algo = st.sidebar.selectbox(
        "Select the Option", options=[
          "Register Patient",
          "View Patient Data"
          ]
    )

    if algo == "Register Patient":
        addUser()
    if algo == "View Patient Data":
        ViewPatientRecord()    
        
        
    st.write ('\n')
    st.write ('\n')
    st.write ('\n')

    
    #ledger start
    #get ledger data 
    
    st.subheader("Blockchain Ledger")
    st.write("Click to explore Blockchain ledger [link](https://ghostnet.tzkt.io/KT1KvCVKiZhkPG8s9CCoxW3r135phk2HhZUV/operations/)")
    
    
    ledger_data = pytezos.using(shell = 'https://rpc.tzkt.io/ghostnet').contract('KT1KvCVKiZhkPG8s9CCoxW3r135phk2HhZUV').storage() #.values()
    
    for x in ledger_data:
    	ledger = ledger_data.values()

    try:
    	df = pd.DataFrame(ledger, index=[0])
    	#filters_widgets(df)
    except:
        df = pd.DataFrame(ledger)#, index=[0])
        #filters_widgets(df)
    # Display the dataframe as a table
    st.write(df)	
    
    
    ############end table/ledger
   
if __name__ == "__main__":
  main()
  
  
#comments
      #ledger = {'age': 18, 'gender': 'Female', 'hospital': '', 'name': 'tesuser1', 'number': 41414, 'v1': False, 'v1Date': 0, 'v2': False, 'v2Date': 0}
    
#    data = [
#        {"Name": "Alice", "Age": 25, "City": "New York"},
#        {"Name": "Bob", "Age": 30, "City": "Paris"},
#        {"Name": "Charlie", "Age": 35, "City": "London"}
#    ]