svglib 0.9.3

A pure-Python library for reading and converting SVG

About

Svglib is a pure-Python library for reading SVG files and converting them (to a reasonable degree) to other formats using the ReportLab Open Source toolkit.

Used as a package you can read existing SVG files and convert them into ReportLab Drawing objects that can be used in a variety of contexts, e.g. as ReportLab Platypus Flowable objects or in RML. As a command-line tool it converts SVG files into PDF ones (but adding other output formats like bitmap or EPS is really easy and will be better supported, soon).

Tests include a huge W3C SVG test suite plus ca. 200 flags from Wikipedia and some selected symbols from Wikipedia (with increasingly less pointing to missing features).

Previous versions were hosted at https://bitbucket.org/deeplook/svglib.

Features

• convert SVG files into ReportLab Graphics Drawing objects

• handle plain or compressed SVG files (.svg and .svgz)

• allow patterns for output files on command-line

• install a Python package named svglib

• install a Python command-line script named svg2pdf

• provide a PyTest test suite with over 90% code coverage

• test entire W3C SVG test suite after pulling from the internet

• test all SVG flags from Wikipedia after pulling from the internet

• test selected SVG symbols from Wikipedia after pulling from the net

• run on Python 2.7 and Python 3.5, 3.6 and 3.7

Known limitations

• support for stylesheets is still experimental. Please report any bug or shortcoming on the svglib issue tracker.

• clipping is limited to single paths, no mask support

• color gradients are not supported

Examples

You can use svglib as a Python package e.g. like in the following interactive Python session:

>>> from svglib.svglib import svg2rlg
>>> from reportlab.graphics import renderPDF, renderPM
>>>
>>> drawing = svg2rlg("file.svg")
>>> renderPDF.drawToFile(drawing, "file.pdf")
>>> renderPM.drawToFile(drawing, "file.png", fmt="PNG")

Note that the second parameter of drawToFile can be any Python file object, like a BytesIO buffer if you don’t want the result to be written on disk for example.

In addition a script named svg2pdf can be used more easily from the system command-line. Here is the output from svg2pdf -h:

usage: svg2pdf [-h] [-v] [-o PATH_PAT] [PATH [PATH ...]]

svg2pdf v. 0.9.3
A converter from SVG to PDF (via ReportLab Graphics)

positional arguments:
  PATH                  Input SVG file path with extension .svg or .svgz.

optional arguments:
  -h, --help            show this help message and exit
  -v, --version         Print version number and exit.
  -o PATH_PAT, --output PATH_PAT
                        Set output path (incl. the placeholders: dirname,
                        basename,base, ext, now) in both, %(name)s and {name}
                        notations.

examples:
  # convert path/file.svg to path/file.pdf
  svg2pdf path/file.svg

  # convert file1.svg to file1.pdf and file2.svgz to file2.pdf
  svg2pdf file1.svg file2.svgz

  # convert file.svg to out.pdf
  svg2pdf -o out.pdf file.svg

  # convert all SVG files in path/ to PDF files with names like:
  # path/file1.svg -> file1.pdf
  svg2pdf -o "%(base)s.pdf" path/file*.svg

  # like before but with timestamp in the PDF files:
  # path/file1.svg -> path/out-12-58-36-file1.pdf
  svg2pdf -o {{dirname}}/out-{{now.hour}}-{{now.minute}}-{{now.second}}-%(base)s.pdf path/file*.svg

issues/pull requests:
    https://github.com/deeplook/svglib

Copyleft by Dinu Gherman, 2008-2019 (LGPL 3):
    http://www.gnu.org/copyleft/gpl.html

Dependencies

Svglib depends mainly on the reportlab package, which provides the abstractions for building complex Drawings which it can render into different fileformats, including PDF, EPS, SVG and various bitmaps ones. Other dependancies are lxml which is used in the context of SVG CSS stylesheets.

Installation

There are three ways to install svglib.

1. Using pip

With the pip command on your system and a working internet connection you can install the newest version of svglib with only one command in a terminal:

$ pip install svglib

You can also use pip to install the very latest version of the repository from GitHub, but then you won’t be able to conveniently run the test suite:

$ pip install git+https://github.com/deeplook/svglib

2. Using conda

If you use Anaconda or Miniconda you are surely using its respective package manager, Conda, as well. In that case you should be able to install svglib using these simple commands:

$ conda config --add channels conda-forge
$ conda install svglib

Svglib was kindly packaged for conda by nicoddemus. See here more about svglib with conda.

3. Manual installation

Alternatively, you can install a tarball like svglib-<version>.tar.gz after downloading it from the svglib page on PyPI or the svglib releases page on GitHub and executing a sequence of commands like shown here:

$ tar xfz svglib-<version>.tar.gz
$ cd svglib-<version>
$ python setup.py install

This will install a Python package named svglib in the site-packages subfolder of your Python installation and a script tool named svg2pdf in your bin directory, e.g. in /usr/local/bin.

Testing

The svglib tarball distribution contains a PyTest test suite in the tests directory. There, in tests/README.rst, you can also read more about testing. You can run the testsuite e.g. like shown in the following lines on the command-line:

$ tar xfz svglib-<version>.tar.gz
$ cd svglib-<version>
$ PYTHONPATH=. py.test
======================== test session starts =========================
platform darwin -- Python 3.7.3, pytest-5.0.1, py-1.8.0, pluggy-0.12.0
rootdir: /Users/dinu/repos/github/deeplook/svglib, inifile:
plugins: cov-2.4.0
collected 36 items

tests/test_basic.py ............................
tests/test_samples.py .s.s.s.s

=============== 32 passed, 4 skipped in 49.18 seconds ================

Bug reports

Please report bugs on the svglib issue tracker on GitHub (pull requests are also appreciated)! If necessary, please include information about the operating system, as well as the versions of svglib, ReportLab and Python being used!