> ## Documentation Index
> Fetch the complete documentation index at: https://docs.risingwave.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Python

> Describes how to use third-party Python drivers to interact with RisingWave.

To interact with RisingWave from Python applications, we recommend using the [`risingwave-py`](https://pypi.org/project/risingwave-py/) SDK.
This SDK provides a simple way to perform ad-hoc queries, subscribe to changes, and define event handlers for tables and materialized views, making it easier to integrate real-time data into applications. For details, see [Python SDK](../python-sdk/intro).

As RisingWave is wire-compatible with PostgreSQL, you can also use third-party PostgreSQL drivers like `psycopg2` and `sqlalchemy` to interact with RisingWave from your Python applications.

## Use `psycopg2` to connect to RisingWave

In this section, we use the [`psycopg2`](https://pypi.org/project/psycopg2/) driver to connect to RisingWave.

### Run RisingWave

To learn about how to run RisingWave, see [Run RisingWave](/get-started/quickstart).

### Install the `psgcopg2` driver

For information about how to install `psycopg` and the difference between `psycopg` and `psycopg-binary`, see the [official psycopg documentation](https://www.psycopg.org/docs/install.html).

### Connect to RisingWave

To connect to RisingWave via `psycopg2`:

```python theme={null}
import psycopg2

conn = psycopg2.connect(host="127.0.0.1", port=4566, user="root", dbname="dev")
```

### Create a source

The code below creates a source `walk` with the `datagen` connector. The `datagen` connector is used to generate mock data. The `walk` source consists of two columns, `distance` and `duration`, which respectively represent the distance and the duration of a walk. The source is a simplified version of the data that is tracked by smart watches.

```python theme={null}
import psycopg2

conn = psycopg2.connect(host="localhost", port=4566, user="root", dbname="dev") # Connect to RisingWave.
conn.autocommit = True # Set queries to be automatically committed.

with conn.cursor() as cur:
    cur.execute("""
CREATE TABLE walk(distance INT, duration INT)
WITH (
    connector = 'datagen',
    fields.distance.kind = 'sequence',
    fields.distance.start = '1',
    fields.distance.end  = '60',
    fields.duration.kind = 'sequence',
    fields.duration.start = '1',
    fields.duration.end = '30',
    datagen.rows.per.second='15',
    datagen.split.num = '1'
) FORMAT PLAIN ENCODE JSON""") # Execute the query.

conn.close() # Close the connection.
```

<Note>All the code examples in this guide include a section for connecting to RisingWave. If you perform multiple actions within one connection session, you do not need to repeat this section.</Note>

### Create a materialized view

The code in this section creates a materialized view `counter` to capture the latest total distance and duration.

```python theme={null}
import psycopg2

conn = psycopg2.connect(host="localhost", port=4566, user="root", dbname="dev")
conn.autocommit = True

with conn.cursor() as cur:
    cur.execute("""CREATE MATERIALIZED VIEW counter
    AS SELECT
    SUM(distance) as total_distance,
    SUM(duration) as total_duration
    FROM walk;""")

conn.close()
```

### Query a materialized view

The code in this section queries the materialized view `counter` to get real-time data.

```python theme={null}
import psycopg2

conn = psycopg2.connect(host="localhost", port=4566, user="root", dbname="dev")
conn.autocommit = True

with conn.cursor() as cur:
    cur.execute("SELECT * FROM counter;")
    print(cur.fetchall())
conn.close()
```

## Use `sqlalchemy` to connect to RisingWave

In this section, we use the [SQLAlchemy](https://www.sqlalchemy.org) driver to connect to RisingWave.

### Run RisingWave

To learn about how to run RisingWave, see [Run RisingWave](../get-started/quickstart).

### Install necessary Python packages

Ensure you have Python3 installed.

For more information about `sqlalchemy`, see the [SQLAlchemy](https://www.sqlalchemy.org). Refer to the documentation version that corresponds to the version of SQLAlchemy that you run.

For information about how to install `psycopg-binary`, see the [official psycopg documentation](https://www.psycopg.org/docs/install.html).

```terminal theme={null}
pip3 install SQLAlchemy sqlalchemy-risingwave psycopg2-binary
```

### Connect to RisingWave

To connect to RisingWave via `sqlalchemy`:

```python theme={null}
DB_URI = 'risingwave+psycopg2://root@risingwave-standalone:4566/dev'

engine = create_engine(DB_URI)
```

Note that RisingWave does not provide direct compatibility with `sqlaclehmy-postgres` so `risingwave+psycopg2` is used as the URI scheme. The rest of the URL follows the same format as the PostgreSQL driver.

### Create a source

The code below creates a table `users` using the engine created in the previous section.

```python theme={null}
with engine.connect() as conn:
    conn.execute("""CREATE TABLE IF NOT EXISTS users (
    id INTEGER PRIMARY KEY,
    name VARCHAR,
    age INTEGER)""")
```

You can create materialized views and query from materialized views using the same format shown above.