Quickstart
==========

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

Step 1: Install
---------------

.. code-block:: bash

   # 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
------------------------------

.. code-block:: bash

   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
---------------------

.. code-block:: bash

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

Step 4: Extract
---------------

.. code-block:: bash

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

Output:

.. code-block:: text

   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
---------------

.. code-block:: bash

   cat output/sqlite/metadata/tables.json

.. code-block:: 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
----------

- :doc:`usage` — config.yaml reference, glob patterns, all CLI commands
- :doc:`delta-engine` — incremental extraction (only changed records)
- :doc:`standalone` — output formats, pandas integration, CSV conversion
- :doc:`integrations` — push to DataHub, OpenMetadata, Purview, Kafka
- :doc:`probes/index` — browse all 197 probes across 49 sources