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ec478de 2e0982a 386acb3 ec478de 386acb3 ec478de 386acb3 ec478de 386acb3 ec478de 386acb3 ec478de 2e0982a 386acb3 ec478de | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 | from pyngrok import ngrok
import threading
import time
import os
# ----------------- Streamlit Dashboard Code ------------------
dashboard_code = """
import streamlit as st
import pandas as pd
import io
# Helper to normalize college name
def normalize_name(name):
if pd.isna(name):
return ""
return name.replace("(B)", "B").strip().lower()
# Transformation Logic
def transform_file(main_df, attendance_df):
# Normalize college names in both DataFrames
main_df['normalized_name'] = main_df.iloc[:, 2].apply(normalize_name)
attendance_df['normalized_name'] = attendance_df.iloc[:, 2].apply(lambda x: str(x).strip().lower())
# Create attendance lookup dictionary
attendance_lookup = attendance_df.set_index('normalized_name')
school_attendance_list = []
inter_attendance_list = []
for name in main_df['normalized_name']:
if name in attendance_lookup.index:
row = attendance_lookup.loc[name]
school_attendance_list.append(row.iloc[6]) # 7th column
inter_attendance_list.append(row.iloc[10]) # 11th column
else:
school_attendance_list.append(None)
inter_attendance_list.append(None)
# Construct final dataframe
new_df = pd.DataFrame({
'serial_no': main_df.iloc[:, 0],
'district': main_df.iloc[:, 1],
'college_name': main_df.iloc[:, 2],
'class': 'School',
'school_minority_sanction': main_df.iloc[:, 3],
'school_minority_admitted': main_df.iloc[:, 4],
'school_minority_vacancies': main_df.iloc[:, 3] - main_df.iloc[:, 4],
'school_non_minority_sanction': main_df.iloc[:, 5],
'school_non_minority_admitted': main_df.iloc[:, 6],
'school_non_minority_vacancies': main_df.iloc[:, 5] - main_df.iloc[:, 6],
'school_attendance': school_attendance_list,
'school_attendance_percentage': '', # Placeholder
'class_grade': 'Intermediate',
'inter_minority_sanction': main_df.iloc[:, 8],
'inter_minority_admitted': main_df.iloc[:, 9],
'inter_minority_vacancies': main_df.iloc[:, 8] - main_df.iloc[:, 9],
'inter_non_minority_sanction': main_df.iloc[:, 10],
'inter_non_minority_admitted': main_df.iloc[:, 11],
'inter_non_minority_vacancies': main_df.iloc[:, 10] - main_df.iloc[:, 11],
'inter_attendance': inter_attendance_list,
'inter_attendance_percentage': '' # Placeholder
})
return new_df
# Streamlit App
st.set_page_config(layout="wide", page_title="📝 File Format Converter")
st.title("📤 Upload Two Files to Convert Format")
uploaded_main = st.file_uploader("Upload Main File (Sanctions, Admissions)", type=["csv", "xlsx"], key="main")
uploaded_attendance = st.file_uploader("Upload Attendance File", type=["csv", "xlsx"], key="att")
if uploaded_main and uploaded_attendance:
try:
# Determine extension and read both files
ext1 = uploaded_main.name.split('.')[-1].lower()
ext2 = uploaded_attendance.name.split('.')[-1].lower()
if ext1 == 'csv':
main_df = pd.read_csv(uploaded_main, skiprows=4)
else:
main_df = pd.read_excel(uploaded_main, skiprows=4)
if ext2 == 'csv':
attendance_df = pd.read_csv(uploaded_attendance)
else:
attendance_df = pd.read_excel(uploaded_attendance)
st.success("✅ Both files uploaded and read successfully!")
new_df = transform_file(main_df, attendance_df)
st.dataframe(new_df.head())
output = io.BytesIO()
with pd.ExcelWriter(output, engine='xlsxwriter') as writer:
new_df.to_excel(writer, index=False, sheet_name='Sheet1')
worksheet = writer.sheets['Sheet1']
# Set wider column widths (20 characters)
for i, col in enumerate(new_df.columns):
worksheet.set_column(i, i, 20)
st.download_button("📥 Download Converted Excel File", output.getvalue(), file_name="converted_output.xlsx")
except Exception as e:
st.error(f"❌ Error while processing files: {e}")
"""
# ----------------- Save Streamlit Code -----------------------
with open("app_file_filter.py", "w") as f:
f.write(dashboard_code)
# ----------------- Ngrok Setup & Streamlit Launch ------------------
ngrok.set_auth_token("30VAe4T9qTjFG7urJrdYiwizPYO_3BVhHNvCaLGXkWDVAtnmu")
# Function to run Streamlit
def run():
os.system("streamlit run app_file_filter.py")
# Start Streamlit in background thread
thread = threading.Thread(target=run)
thread.start()
# Give Streamlit time to boot
time.sleep(5)
# Close existing tunnels if any
for tunnel in ngrok.get_tunnels():
ngrok.disconnect(tunnel.public_url)
# Open a new ngrok tunnel
public_url = ngrok.connect(addr=8501)
print("🔗 Public URL:", public_url) |