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Added database upload feature (db_uploader) Allows user to upload .db/.sqlite or schema.json files and extract schema automatically. #3

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Added database upload feature (db_uploader) Allows user to upload .db/.sqlite or schema.json files and extract schema automatically. #3

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c8900d7
feat: add Streamlit database uploader and schema extractor feature
taghreed1kh Nov 9, 2025
c71d1d3
fix: correct import path for db_fetcher
taghreed1kh Nov 9, 2025
3d376eb
feat: enable database upload & SQL query testing in Streamlit
taghreed1kh Nov 10, 2025
ed3a6fe
feat: secure DB uploader (save to data) + SQL tester
taghreed1kh Nov 10, 2025
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Empty file added streamlit_app/__init__.py
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155 changes: 78 additions & 77 deletions db_fetcher.py → streamlit_app/db_fetcher.py
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Original file line number Diff line number Diff line change
@@ -1,77 +1,78 @@
import streamlit as st
import sqlite3
import tempfile
import os
import json

st.set_page_config(page_title="Database Fetcher", layout="wide")
st.title("Database Fetcher (Upload schema.json or DB file)")

def extract_schema_from_sqlite(path):
conn = sqlite3.connect(path)
cur = conn.cursor()
cur.execute("SELECT name FROM sqlite_master WHERE type='table' AND name NOT LIKE 'sqlite_%'")
tables = [r[0] for r in cur.fetchall()]
schema = {"tables": []}

for t in tables:
cur.execute(f"PRAGMA table_info('{t}')")
cols = []
pks = []
for cid, name, ctype, notnull, dflt, pk in cur.fetchall():
cols.append({
"name": name,
"type": ctype,
"nullable": notnull == 0,
"default": dflt
})
if pk:
pks.append(name)

cur.execute(f"PRAGMA foreign_key_list('{t}')")
fks = [
{
"column": fk[3],
"referred_table": fk[2],
"referred_columns": [fk[4]]
}
for fk in cur.fetchall()
]

schema["tables"].append({
"name": t,
"columns": cols,
"primary_key": pks,
"foreign_keys": fks
})

conn.close()
return schema


tab1, tab2 = st.tabs(["Upload DB", "Upload Schema JSON"])

with tab1:
db_file = st.file_uploader("Upload SQLite file (.db or .sqlite)", type=["db", "sqlite"])
if db_file:
with tempfile.NamedTemporaryFile(delete=False, suffix=".sqlite") as tmp:
tmp.write(db_file.read())
tmp_path = tmp.name

schema = extract_schema_from_sqlite(tmp_path)
os.remove(tmp_path)
st.success("Schema extracted successfully")
st.json(schema)
st.download_button(
"Download schema.json",
json.dumps(schema, indent=2).encode("utf-8"),
"schema.json",
"application/json"
)

with tab2:
schema_file = st.file_uploader("Upload schema.json", type=["json"])
if schema_file:
schema = json.load(schema_file)
st.success("Schema loaded successfully")
st.json(schema)
import streamlit as st
import sqlite3
import tempfile
import os
import json

st.set_page_config(page_title="Database Fetcher", layout="wide")
st.title("Database Fetcher (Upload schema.json or DB file)")

def extract_sqlite_schema(path):

conn = sqlite3.connect(path)
cur = conn.cursor()
cur.execute("SELECT name FROM sqlite_master WHERE type='table' AND name NOT LIKE 'sqlite_%'")
tables = [r[0] for r in cur.fetchall()]
schema = {"tables": []}

for t in tables:
cur.execute(f"PRAGMA table_info('{t}')")
cols = []
pks = []
for cid, name, ctype, notnull, dflt, pk in cur.fetchall():
cols.append({
"name": name,
"type": ctype,
"nullable": notnull == 0,
"default": dflt
})
if pk:
pks.append(name)

cur.execute(f"PRAGMA foreign_key_list('{t}')")
fks = [
{
"column": fk[3],
"referred_table": fk[2],
"referred_columns": [fk[4]]
}
for fk in cur.fetchall()
]

schema["tables"].append({
"name": t,
"columns": cols,
"primary_key": pks,
"foreign_keys": fks
})

conn.close()
return schema


tab1, tab2 = st.tabs(["Upload DB", "Upload Schema JSON"])

with tab1:
db_file = st.file_uploader("Upload SQLite file (.db or .sqlite)", type=["db", "sqlite"])
if db_file:
with tempfile.NamedTemporaryFile(delete=False, suffix=".sqlite") as tmp:
tmp.write(db_file.read())
tmp_path = tmp.name

schema = extract_schema_from_sqlite(tmp_path)
os.remove(tmp_path)
st.success("Schema extracted successfully")
st.json(schema)
st.download_button(
"Download schema.json",
json.dumps(schema, indent=2).encode("utf-8"),
"schema.json",
"application/json"
)

with tab2:
schema_file = st.file_uploader("Upload schema.json", type=["json"])
if schema_file:
schema = json.load(schema_file)
st.success("Schema loaded successfully")
st.json(schema)
45 changes: 45 additions & 0 deletions streamlit_app/db_uploader.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,45 @@
import streamlit as st
import sqlite3
import os
import pandas as pd

st.set_page_config(page_title="Database Uploader", layout="wide")
st.title("Database Uploader & SQL Tester")

DATA_DIR = "data"
os.makedirs(DATA_DIR, exist_ok=True)

ACCESS_KEY = "SDAIA2025"
key_input = st.text_input("Enter access key:", type="password")

if key_input == ACCESS_KEY:
st.success("Access granted")

uploaded = st.file_uploader("Upload SQLite database (.db / .sqlite)", type=["db", "sqlite"])
if uploaded:
save_path = os.path.join(DATA_DIR, uploaded.name)
with open(save_path, "wb") as f:
f.write(uploaded.getbuffer())
st.success(f"File saved to: {save_path}")

db_files = [f for f in os.listdir(DATA_DIR) if f.endswith((".db", ".sqlite"))]
if db_files:
selected_db = st.selectbox("Select a database:", db_files)
db_path = os.path.join(DATA_DIR, selected_db)

query = st.text_area("SQL query:", "SELECT name FROM sqlite_master WHERE type='table';", height=100)
if st.button("Run Query"):
try:
conn = sqlite3.connect(db_path)
df = pd.read_sql_query(query, conn)
st.dataframe(df, use_container_width=True)
conn.close()
except Exception as e:
st.error(f"SQL Error: {e}")
else:
st.info("No databases found in /data.")
else:
st.warning("Enter a valid access key to enable uploader.")