README

.. image:: https://travis-ci.org/libvips/pyvips.svg?branch=master :alt: Build Status :target: https://travis-ci.org/libvips/pyvips

PyPI package:

https://pypi.python.org/pypi/pyvips

conda package:

https://anaconda.org/conda-forge/pyvips

We have formatted docs online here:

https://libvips.github.io/pyvips/

This module wraps the libvips image processing library:

https://libvips.github.io/libvips/

The libvips docs are also very useful:

https://libvips.github.io/libvips/API/current/

If you have the development headers for libvips installed and have a working C compiler, this module will use cffi API mode to try to build a libvips binary extension for your Python.

If it is unable to build a binary extension, it will use cffi ABI mode instead and only needs the libvips shared library. This takes longer to start up and is typically ~20% slower in execution. You can find out how pyvips installed with pip show pyvips.

This binding passes the vips test suite cleanly and with no leaks under python2.7 - python3.6, pypy and pypy3 on Windows, macOS and Linux.

How it works

Programs that use pyvips don't manipulate images directly, instead they create pipelines of image processing operations building on a source image. When the end of the pipe is connected to a destination, the whole pipeline executes at once, streaming the image in parallel from source to destination a section at a time.

Because pyvips is parallel, it's quick, and because it doesn't need to keep entire images in memory, it's light. For example, the libvips speed and memory use benchmark:

https://github.com/libvips/libvips/wiki/Speed-and-memory-use

Loads a large tiff image, shrinks by 10%, sharpens, and saves again. On this test pyvips is typically 3x faster than ImageMagick and needs 5x less memory.

There's a handy chapter in the docs explaining how libvips opens files, which gives some more background.

http://libvips.github.io/libvips/API/current/How-it-opens-files.md.html

conda Install

The conda package includes a matching libvips binary, so just enter:

.. code-block:: shell

$ conda install --channel conda-forge pyvips

Non-conda install

First, you need the libvips shared library on your library search path, version 8.2 or later, though at least version 8.9 is required for all features to work. On Linux and macOS, you can just install via your package manager; on Windows you can download a pre-compiled binary from the libvips website.

https://libvips.github.io/libvips/install.html

Next, install this package, perhaps:

.. code-block:: shell

$ pip install --user pyvips

On Windows, you'll need a 64-bit Python. The official one works well. You will also need to add vips-dev-x.y\bin to your PATH so that pyvips can find all the DLLs it needs. You can either do this in the Advanced System Settings control panel, or you can just change PATH in your Python program.

If you set the PATH environment variable in the control panel, you can use the vips command-line tools, which I find useful. However, this will add a lot of extra DLLs to your search path and they might conflict with other programs, so it's usually safer just to set PATH in your program.

To set PATH from within Python, you need something like this at the start:

.. code-block:: python

import os
vipshome = 'c:\\vips-dev-8.7\\bin'
os.environ['PATH'] = vipshome + ';' + os.environ['PATH']

Now when you import pyvips, it should be able to find the DLLs.

Example

This sample program loads a JPG image, doubles the value of every green pixel, sharpens, and then writes the image back to the filesystem again:

.. code-block:: python

import pyvips

image = pyvips.Image.new_from_file('some-image.jpg', access='sequential')
image *= [1, 2, 1]
mask = pyvips.Image.new_from_array([[-1, -1, -1],
                                    [-1, 16, -1],
                                    [-1, -1, -1]
                                   ], scale=8)
image = image.conv(mask, precision='integer')
image.write_to_file('x.jpg')

Notes

Local user install:

.. code-block:: shell

$ pip3 install -e .
$ pypy -m pip --user -e .

Run all tests:

.. code-block:: shell

$ tox 

Run test suite:

.. code-block:: shell

$ tox test

Run a specific test:

.. code-block:: shell

$ pytest-3 tests/test_saveload.py

Run perf tests:

.. code-block:: shell

$ cd tests/perf $ ./run.sh

Stylecheck:

.. code-block:: shell

$ tox qa

Generate HTML docs in doc/build/html:

.. code-block:: shell

$ cd doc; sphinx-build -bhtml . build/html

Regenerate autodocs:

.. code-block:: shell

$ cd doc; \
  python3 -c "import pyvips; pyvips.Operation.generate_sphinx_all()" > x 

And copy-paste x into the obvious place in doc/vimage.rst.

Update version number:

.. code-block:: shell

$ vi pyvips/version.py
$ vi doc/conf.py

Update pypi package:

.. code-block:: shell

$ python3 setup.py sdist
$ twine upload dist/*
$ git tag -a v2.1.12 -m "as uploaded to pypi"
$ git push origin v2.1.12