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# Installation

In short, if you use a supported system:

    pip install --upgrade pip           # upgrade pip to at least 20.3
    pip install "psycopg[binary]"       # remove [binary] for PyPy

and you should be ready to start. Read further for alternative ways to install.

## Supported systems

The Psycopg version documented here has official and tested support for:

- Python: from version 3.7 to 3.12

  - Python 3.6 supported before Psycopg 3.1

- PyPy: from version 3.9 to 3.10

  - Note: Only the pure Python version is supported.

- PostgreSQL: from version 10 to 16

- OS: Linux, macOS, Windows

The tests to verify the supported systems run in Github workflows: anything that is not tested there is not officially supported. This includes:

- Unofficial Python distributions such as Conda;

- Alternative PostgreSQL implementation;

- macOS hardware and releases not available on Github workflows.

If you use an unsupported system, things might work (because, for instance, the database may use the same wire protocol as PostgreSQL) but we cannot guarantee the correct working or a smooth ride.

## Binary installation

The quickest way to start developing with Psycopg 3 is to install the binary packages by running:

    pip install "psycopg[binary]"

This will install a self-contained package with all the libraries needed. You will need pip 20.3 at least: please run `pip install --upgrade pip` to update it beforehand.

The above package should work in most situations. It will not work in some cases though.

If your platform is not supported you should proceed to a local installation or a pure Python installation.

See also

Did Psycopg 3 install ok? Great! You can now move on to the basic module usage to learn how it works.

Keep on reading if the above method didn’t work and you need a different way to install Psycopg 3.

For further information about the differences between the packages see pq module implementations.

Warning

The binary installation is not supported by PyPy.

## Local installation

A “Local installation” results in a performing and maintainable library. The library will include the speed-up C module and will be linked to the system libraries (`libpq`, `libssl`…) so that system upgrade of libraries will upgrade the libraries used by Psycopg 3 too. This is the preferred way to install Psycopg for a production site.

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`.

You must be able to troubleshoot an extension build, for instance you must be able to read your compiler’s error message. If you are not, please don’t try this and follow the binary installation instead.

If your build prerequisites are in place you can run:

    pip install "psycopg[c]"

Warning

The local installation is not supported by PyPy.

## Pure Python installation

If you simply install:

    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`).

In order to use the pure Python installation you will need the `libpq` installed in the system: for instance on Debian system you will probably need:

    sudo apt install libpq5

Note

The `libpq` is the client library used by psql, the PostgreSQL command line client, to connect to the database. On most systems, installing psql will install the `libpq` too as a dependency.

If you are not able to fulfill this requirement please follow the binary installation.

## Installing the connection pool

The Psycopg connection pools are distributed in a separate package from the `psycopg` package itself, in order to allow a different release cycle.

In order to use the pool you must install the `pool` extra, using `pip install "psycopg[pool]"`, or install the `psycopg_pool` package separately, which would allow to specify the release to install more precisely.

## Handling dependencies

If you need to specify your project dependencies (for instance in a `requirements.txt` file, `setup.py`, `pyproject.toml` dependencies…) you should probably specify one of the following:

- If your project is a library, add a dependency on `psycopg`. This will make sure that your library will have the `psycopg` package with the right interface and leaves the possibility of choosing a specific implementation to the end user of your library.

- If your project is a final application (e.g. a service running on a server) you can require a specific implementation, for instance `psycopg[c]`, after you have made sure that the prerequisites are met (e.g. the depending libraries and tools are installed in the host machine).

In both cases you can specify which version of Psycopg to use using requirement specifiers.

If you want to make sure that a specific implementation is used you can specify the `PSYCOPG_IMPL` environment variable: importing the library will fail if the implementation specified is not available. See pq module implementations.