Quickstart

Your first metadata extraction in under 5 minutes. No database credentials needed — we’ll use SQLite.

Step 1: Install

# From PyPI (released version)
pip install metapod-probes

# Or from local source (if you cloned the repo)
git clone https://github.com/mario-ambrosino/metapod.git
cd metapod && pip install -e "."

Step 2: Create a test database

python3 -c "
import sqlite3
conn = sqlite3.connect('demo.db')
conn.execute('CREATE TABLE customers (id INTEGER PRIMARY KEY, name TEXT, email TEXT)')
conn.execute('CREATE TABLE orders (id INTEGER PRIMARY KEY, customer_id INTEGER, amount REAL)')
conn.execute('INSERT INTO customers VALUES (1, \"Acme Corp\", \"acme@example.com\")')
conn.execute('INSERT INTO orders VALUES (1, 1, 150.00)')
conn.commit()
conn.close()
"

Step 3: Create config

cat > config.yaml << EOF
source:
  type: sqlite
  host: ./demo.db
EOF

Step 4: Extract

metapod run "sqlite.*" --config config.yaml

Output:

Running 2 probes matching 'sqlite.*'

  sqlite.metadata.tables  ━━━━━━━━━━━━━━━━━━━━ 2/2 0:00:00

┃ Probe                   ┃ Records ┃ Duration ┃ Status ┃
│ sqlite.metadata.columns │       5 │      1ms │ OK     │
│ sqlite.metadata.tables  │       2 │      0ms │ OK     │

Step 5: Inspect

cat output/sqlite/metadata/tables.json

{
  "envelope_version": "1.0",
  "probe": "sqlite.metadata.tables",
  "source": {"type": "sqlite", "id": "sqlite://./demo.db"},
  "records": [
    {"table_name": "customers", "type": "table"},
    {"table_name": "orders", "type": "table"}
  ],
  "record_count": 2,
  "duration_ms": 0
}

That’s it. Every probe produces a JSON envelope with this structure.

Next steps