Psycopg 3 is the newest implementation of the most popular adapter for Python. For details on using psycopg3, see [Psycopg3 documentation](https://www.psycopg.org/psycopg3/docs/). For a tutorial on building a sample Python application that uses psycopg3, see [Connect an application](../postgres-psycopg3/). ## Fundamentals Learn how to perform common tasks required for Python application development using the PostgreSQL Psycopg3 driver. ### Download the driver dependency The quickest way to start developing with Psycopg 3 is to install the binary packages by running: ```sh pip install "psycopg[binary]" ``` This will install a self-contained package with all the libraries needed. You will need `pip 20.3` at least. If your platform is not supported, or if the `libpq` packaged is not suitable, you should proceed to a local installation or a pure Python installation. In order to perform a local installation you need some prerequisites: - a C compiler, - Python development headers (e.g. the `python3-dev` package). - PostgreSQL client development headers (e.g. the `libpq-dev` package). - The `pg_config` program available in the `PATH`. If your build prerequisites are in place you can run: ```sh pip install "psycopg[c]" ``` If you simply install: ```sh pip install psycopg ``` Without [c] or [binary] extras you will obtain a pure Python implementation. This is particularly handy to debug and hack, but it still requires the system libpq to operate (which will be imported dynamically via `ctypes`). ### Connect to YugabyteDB database Python applications can connect to and query the YugabyteDB database using the following: - Import the psycopg package. ```python import psycopg ``` - The Connection details can be provided as a string or a dictionary. Connection String ```python "dbname=database_name host=hostname port=port user=username password=password" ``` Connection Dictionary ```python user = 'username', password='xxx', host = 'hostname', port = 'port', dbname = 'database_name' ``` The following table describes the connection parameters required to connect to the YugabyteDB database | Parameters | Description | Default | | :-------------- | :------------------------- | :---------- | | host | hostname of the YugabyteDB instance | localhost | port | Listen port for YSQL | 5433 | database/dbname | Database name | yugabyte | user | User for connecting to the database | yugabyte | password | Password for the user | yugabyte The following is an example connection string for connecting to YugabyteDB. ```python conn = psycopg.connect(dbname='yugabyte',host='localhost',port='5433',user='yugabyte',password='yugabyte') ``` ### Executing queries Psycopg 3 exposes a few simple extensions which make the following pattern leaner: the Connection objects exposes an execute() method, equivalent to creating a cursor, calling its execute() method, and returning it. In Psycopg 2: ```python cur = conn.cursor() cur.execute(...) ``` In Psycopg 3: ```python cur = conn.execute(...) ``` ### Create tables Tables can be created in YugabyteDB by passing the `CREATE TABLE` DDL statement to the `conn.execute(statement)` method, using the following example: ```sql CREATE TABLE IF NOT EXISTS employee (id int PRIMARY KEY, name varchar, age int, language text) ``` ```python conn = psycopg.connect(dbname='yugabyte',host='localhost',port='5433',user='yugabyte',password='yugabyte') conn.execute('CREATE TABLE IF NOT EXISTS employee (id int PRIMARY KEY, name varchar, age int, language varchar)') ``` ### Read and write data #### Insert data To write data into YugabyteDB, execute the `INSERT` statement using the `conn.execute(statement)` method. For example: ```sql INSERT INTO employee VALUES (1, 'John', 35, 'Java') ``` ```python conn = psycopg.connect(dbname='yugabyte',host='localhost',port='5433',user='yugabyte',password='yugabyte') conn.execute('INSERT INTO employee VALUES (1, 'John', 35, 'Java')') ``` #### Query data In psycopg 3, the Cursor.execute() method returns self. This means that you can chain a fetch operation, such as fetchone(), to the execute() call: ```python # In Psycopg 2: cur.execute(...) record = cur.fetchone() cur.execute(...) for record in cur: ... # In Psycopg 3: record = cur.execute(...).fetchone() for record in cur.execute(...): ... ``` Using them together, in simple cases, you can go from creating a connection to using a result in a single expression: ```python print(psycopg.connect(DSN).execute("SELECT now()").fetchone()[0]) # 2025-06-27 18:15:10.706497+01:00 ```