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import streamlit as st
import pandas as pd
import sqlite3
import io
import base64
import os
from datetime import datetime
# Set page config
st.set_page_config(
page_title="Database Operations Tool",
page_icon="🗃️",
layout="wide",
initial_sidebar_state="expanded"
)
# Modern UI styling
st.markdown("""
<style>
.main {
padding: 1rem;
}
.stButton>button {
width: 100%;
background-color: #4CAF50;
color: white;
padding: 0.5rem;
border-radius: 5px;
border: none;
margin: 0.5rem 0;
}
.stButton>button:hover {
background-color: #45a049;
}
.reportview-container {
background: #fafafa;
}
.css-1d391kg {
padding: 1rem;
}
.stSelectbox {
margin: 1rem 0;
}
</style>
""", unsafe_allow_html=True)
def init_db():
"""Initialize SQLite database"""
if not os.path.exists('databases'):
os.makedirs('databases')
conn = sqlite3.connect('databases/main.db')
c = conn.cursor()
c.execute('''CREATE TABLE IF NOT EXISTS database_list
(name TEXT PRIMARY KEY, created_date TEXT)''')
conn.commit()
return conn
def get_database_names():
"""Get list of databases"""
conn = init_db()
c = conn.cursor()
c.execute("SELECT name FROM database_list")
databases = [row[0] for row in c.fetchall()]
conn.close()
return databases
def create_table(db_name, columns, column_types):
"""Create a new table with specified column types"""
conn = sqlite3.connect(f'databases/{db_name}.db')
c = conn.cursor()
columns_with_types = [f"{col} {type_}" for col, type_ in zip(columns, column_types)]
query = f'''CREATE TABLE IF NOT EXISTS data
({', '.join(columns_with_types)})'''
c.execute(query)
conn.commit()
conn.close()
def get_table_data(db_name):
"""Get table data"""
conn = sqlite3.connect(f'databases/{db_name}.db')
return pd.read_sql_query("SELECT * FROM data", conn)
def get_columns(db_name):
"""Get column names and types"""
conn = sqlite3.connect(f'databases/{db_name}.db')
c = conn.cursor()
c.execute("PRAGMA table_info(data)")
columns = [(row[1], row[2]) for row in c.fetchall()]
conn.close()
return columns
def delete_rows(db_name, condition_col, condition_val):
"""Delete rows based on condition"""
conn = sqlite3.connect(f'databases/{db_name}.db')
c = conn.cursor()
c.execute(f"DELETE FROM data WHERE {condition_col} = ?", (condition_val,))
deleted_count = c.rowcount
conn.commit()
conn.close()
return deleted_count
def update_row(db_name, condition_col, condition_val, update_col, update_val):
"""Update row based on condition"""
conn = sqlite3.connect(f'databases/{db_name}.db')
c = conn.cursor()
c.execute(f"UPDATE data SET {update_col} = ? WHERE {condition_col} = ?",
(update_val, condition_val))
updated_count = c.rowcount
conn.commit()
conn.close()
return updated_count
def bulk_import_data(db_name, df):
"""Bulk import data from DataFrame"""
conn = sqlite3.connect(f'databases/{db_name}.db')
df.to_sql('data', conn, if_exists='append', index=False)
conn.close()
def main():
st.title("🗃️ Database Operations Tool")
# Sidebar for database operations
with st.sidebar:
st.header("Database Operations")
# Create New Database
with st.expander("Create New Database", expanded=True):
new_db_name = st.text_input("Database Name")
columns_input = st.text_input("Column Names (comma-separated)")
column_types = st.multiselect("Column Types",
["TEXT", "INTEGER", "REAL", "BLOB", "DATE"],
["TEXT"])
if st.button("Create Database"):
if new_db_name and columns_input and column_types:
try:
columns = [col.strip() for col in columns_input.split(",")]
if len(columns) != len(column_types):
st.error("❌ Number of columns and types must match!")
return
conn = init_db()
c = conn.cursor()
c.execute("INSERT INTO database_list VALUES (?, ?)",
(new_db_name, datetime.now().strftime("%Y-%m-%d %H:%M:%S")))
conn.commit()
conn.close()
create_table(new_db_name, columns, column_types)
st.success("✅ Database created successfully!")
except sqlite3.IntegrityError:
st.error("❌ Database name already exists!")
else:
st.warning("⚠️ Please fill all fields")
# Main content area
databases = get_database_names()
if databases:
selected_db = st.selectbox("📁 Select Database", databases)
if selected_db:
df = get_table_data(selected_db)
columns = get_columns(selected_db)
tabs = st.tabs(["📝 Manage Data", "🔄 Update Data", "🗑️ Delete Data", "📥 Import/Export"])
# Data Management Tab
with tabs[0]:
st.subheader("Data Preview")
st.dataframe(df, use_container_width=True)
st.subheader("Add New Row")
new_row_data = {}
for col, type_ in columns:
if type_ == 'DATE':
new_row_data[col] = st.date_input(f"Enter {col}")
elif type_ == 'INTEGER':
new_row_data[col] = st.number_input(f"Enter {col}", step=1)
elif type_ == 'REAL':
new_row_data[col] = st.number_input(f"Enter {col}", step=0.1)
else:
new_row_data[col] = st.text_input(f"Enter {col}")
if st.button("Add Row"):
if all(str(val) != "" for val in new_row_data.values()):
conn = sqlite3.connect(f'databases/{selected_db}.db')
c = conn.cursor()
placeholders = ','.join(['?' for _ in columns])
query = f"INSERT INTO data VALUES ({placeholders})"
c.execute(query, list(new_row_data.values()))
conn.commit()
conn.close()
st.success("✅ Row added!")
st.rerun()
# Update Data Tab
with tabs[1]:
st.subheader("Update Records")
col1, col2 = st.columns(2)
with col1:
condition_col = st.selectbox("Select Column for Condition",
[col for col, _ in columns])
condition_val = st.text_input("Enter Value to Match")
with col2:
update_col = st.selectbox("Select Column to Update",
[col for col, _ in columns])
update_val = st.text_input("Enter New Value")
if st.button("Update Records"):
if condition_val and update_val:
updated = update_row(selected_db, condition_col,
condition_val, update_col, update_val)
st.success(f"✅ Updated {updated} records!")
st.rerun()
# Delete Data Tab
with tabs[2]:
st.subheader("Delete Records")
del_col = st.selectbox("Select Column for Deletion Condition",
[col for col, _ in columns])
del_val = st.text_input("Enter Value to Delete")
if st.button("Delete Records"):
if del_val:
deleted = delete_rows(selected_db, del_col, del_val)
st.success(f"✅ Deleted {deleted} records!")
st.rerun()
# Import/Export Tab
with tabs[3]:
st.subheader("Import Data")
uploaded_file = st.file_uploader("Choose a CSV file", type="csv")
if uploaded_file is not None:
import_df = pd.read_csv(uploaded_file)
if st.button("Import Data"):
bulk_import_data(selected_db, import_df)
st.success("✅ Data imported successfully!")
st.rerun()
st.subheader("Export Data")
export_format = st.selectbox("Select Format",
["CSV", "Excel", "JSON"])
if export_format == "CSV":
csv = df.to_csv(index=False)
st.download_button(
label="📥 Download CSV",
data=csv,
file_name=f"{selected_db}.csv",
mime="text/csv"
)
elif export_format == "Excel":
buffer = io.BytesIO()
df.to_excel(buffer, index=False)
st.download_button(
label="📥 Download Excel",
data=buffer.getvalue(),
file_name=f"{selected_db}.xlsx",
mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
)
else: # JSON
json_str = df.to_json(orient='records')
st.download_button(
label="📥 Download JSON",
data=json_str,
file_name=f"{selected_db}.json",
mime="application/json"
)
else:
st.info("👋 Welcome! Start by creating a new database using the sidebar.")
if __name__ == "__main__":
main() |