segestic/HealthBlock
1
1import streamlit as st2from pytezos import pytezos3import pandas as pd4 5pytezos = pytezos.using(shell = 'https://rpc.tzkt.io/ghostnet', key='edsk3MrRkoidY2SjEgufvi44orvyjxgZoy4LhaJNTNcddWykW6SssL')6contract = pytezos.contract('KT1KvCVKiZhkPG8s9CCoxW3r135phk2HhZUV')7 8def welcome():9 return "Welcome To Decentralised Medical Records"10 11def addUser():12 name = st.text_input("Enter Full Name of the Patient")13 email = st.text_input("Enter Email of the Patient")14 number = st.number_input("Enter the Contact Number", step=1, min_value=1)15 age = st.number_input("Enter Age", step=1, min_value=18)16 gender = st.radio("Enter Gender", ('Male', 'Female'))17 #Hid = st.text_input("Enter your Unique Hospital Id")18 #hospital=st.text_input("Enter the Hospital details")19 20 21 if st.button("Register Patient"):22 a = pytezos.using(shell = 'https://rpc.tzkt.io/ghostnet', key='edsk3MrRkoidY2SjEgufvi44orvyjxgZoy4LhaJNTNcddWykW6SssL')23 contract = a.contract('KT1KvCVKiZhkPG8s9CCoxW3r135phk2HhZUV')24 25 contract.addUser(email = email, name = name, age = age, gender = gender, number = number).with_amount(0).as_transaction().fill().sign().inject() 26 27 28def ViewPatientRecord():29 Hid = st.text_input("Enter Unique Hospital Id of Patient")30 if st.button("View Records"):31 usds = pytezos.using(shell = 'https://rpc.tzkt.io/ghostnet').contract('KT1KvCVKiZhkPG8s9CCoxW3r135phk2HhZUV')32 #print (usds.storage())#debug33 #print(list(usds.storage().keys())[0])34 35 #if email is in storage... print record36 if Hid in list(usds.storage().keys()):37 st.text(usds.storage())38 #print(usds.storage())39 #st.text(list(usds.storage().keys())[0])40 #st.text(list(usds.storage().values()))41 else: 42 st.text('Not Found')43 #st.text(usds.storage[email]['Record']())44 45 46####################WIDGETS START ##################################47 48def filters_widgets(df, columns=None, allow_single_value_widgets=False):49 # Parse the df and get filter widgets based for provided columns50 if not columns: #if columns not provided, use all columns to create widgets51 columns=df.columns.tolist()52 if allow_single_value_widgets:53 threshold=054 else:55 threshold=156 widget_dict = {}57 filter_widgets = st.container()58 filter_widgets.warning(59 "After selecting filters press the 'Apply Filters' button at the bottom.")60 if not allow_single_value_widgets:61 filter_widgets.markdown("Only showing columns that contain more than 1 unique value.")62 with filter_widgets.form(key="data_filters"):63 not_showing = [] 64 for y in df[columns]:65 if str(y) in st.session_state: #update value from session state if exists66 selected_opts = st.session_state[str(y)]67 else: #if doesnt exist use all values as defaults68 selected_opts = df[y].unique().tolist()69 if len(df[y].unique().tolist()) > threshold: #checks if above threshold70 widget_dict[y] = st.multiselect(71 label=str(y),72 options=df[y].unique().tolist(),73 default=selected_opts,74 key=str(y),75 )76 else:#if doesnt pass threshold77 not_showing.append(y)78 if not_showing:#if the list is not empty, show this warning79 st.warning(80 f"Not showing filters for {' '.join(not_showing)} since they only contain one unique value."81 )82 submit_button = st.form_submit_button("Apply Filters")83 #reset button to return all unselected values back84 reset_button = filter_widgets.button(85 "Reset All Filters",86 key="reset_buttons",87 on_click=reset_filter_widgets_to_default,88 args=(df, columns),89 )90 filter_widgets.warning(91 "Dont forget to apply filters by pressing 'Apply Filters' at the bottom."92 ) 93 94def reset_filter_widgets_to_default(df, columns):95 for y in df[columns]:96 if str(y) in st.session_state:97 del st.session_state[y]98 99####################WIDGETS END##################################100 101def main():102 103 st.set_page_config(page_title="Decentralised Health Vaccine Records")104 105 st.title("Blockchain Based Medical Records")106 st.markdown(107 """<div style="background-color:#e1f0fa;padding:10px">108 <h1 style='text-align: center; color: #304189;font-family:Helvetica'><strong>109 Vaccine Data </strong></h1></div><br>""",110 unsafe_allow_html=True,111 )112 113 114 st.markdown(115 """<p style='text-align: center;font-family:Helvetica;'>116 This project greatly decreases any chances of misuse or the manipulation of the medical Records</p>""",117 unsafe_allow_html=True,118 )119 120 st.sidebar.title("Choose your entry point")121 st.sidebar.markdown("Select the entry point accordingly:")122 123 algo = st.sidebar.selectbox(124 "Select the Option", options=[125 "Register Patient",126 "View Patient Data"127 ]128 )129 130 if algo == "Register Patient":131 addUser()132 if algo == "View Patient Data":133 ViewPatientRecord() 134 135 136 st.write ('\n')137 st.write ('\n')138 st.write ('\n')139 140 141 #ledger start142 #get ledger data 143 144 st.subheader("Blockchain Ledger")145 st.write("Click to explore Blockchain ledger [link](https://ghostnet.tzkt.io/KT1KvCVKiZhkPG8s9CCoxW3r135phk2HhZUV/operations/)")146 147 148 ledger_data = pytezos.using(shell = 'https://rpc.tzkt.io/ghostnet').contract('KT1KvCVKiZhkPG8s9CCoxW3r135phk2HhZUV').storage() #.values()149 150 for x in ledger_data:151 ledger = ledger_data.values()152 153 try:154 df = pd.DataFrame(ledger, index=[0])155 #filters_widgets(df)156 except:157 df = pd.DataFrame(ledger)#, index=[0])158 #filters_widgets(df)159 # Display the dataframe as a table160 st.write(df) 161 162 163 164if __name__ == "__main__":165 main() #streamlit-start166 import subprocess167 import uvicorn168 169 subprocess.run("uvicorn api.main:app --host 0.0.0.0 --port 7860", shell=True) 170 171 172 173 ############end table/ledger174 175#if __name__ == "__main__":176 #main()177 178 179 180#comments181 #ledger = {'age': 18, 'gender': 'Female', 'hospital': '', 'name': 'tesuser1', 'number': 41414, 'v1': False, 'v1Date': 0, 'v2': False, 'v2Date': 0}182 183# data = [184# {"Name": "Alice", "Age": 25, "City": "New York"},185# {"Name": "Bob", "Age": 30, "City": "Paris"},186# {"Name": "Charlie", "Age": 35, "City": "London"}187# ]188