Psycopg 3 is a modern implementation of a PostgreSQL adapter for Python.
Quick version:
pip install --upgrade pip # upgrade pip to at least 20.3 pip install psycopg[binary,pool] # install binary dependencies
For further information about installation please check the documentation.
In order to work on the Psycopg source code you need to have the libpq
PostgreSQL client library installed in the system. For instance, on Debian
systems, you can obtain it by running:
sudo apt install libpq5
After which you can clone this repository:
git clone https://github.com/psycopg/psycopg.git cd psycopg
Please note that the repository contains the source code of several Python
packages: that's why you don't see a setup.py
here. The packages may have
different requirements:
- The
psycopg
directory contains the pure python implementation ofpsycopg
. The package has only a runtime dependency on thelibpq
, the PostgreSQL client library, which should be installed in your system. - The
psycopg_c
directory contains an optimization module written in C/Cython. In order to build it you will need a few development tools: please look at Local installation in the docs for the details. - The
psycopg_pool
directory contains the connection pools implementations. This is kept as a separate package to allow a different release cycle.
You can create a local virtualenv and install there the packages in development mode, together with their development and testing requirements:
python -m venv .venv source .venv/bin/activate pip install -e ./psycopg[dev,test] # for the base Python package pip install -e ./psycopg_c # for the C extension module pip install -e ./psycopg_pool # for the connection pool
Now hack away! You can use tox to validate the code:
pip install tox tox -p4
and to run the tests:
psql -c 'create database psycopg_test' export PSYCOPG_TEST_DSN="dbname=psycopg_test" tox -c psycopg -s tox -c psycopg_c -s
Please look at the commands definitions in the tox.ini
files if you want
to run some of them interactively: the dependency should be already in your
virtualenv. Feel free to adapt these recipes if you follow a different
development pattern.