pyots (PYthon OT Sanitizer)

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Python wrapper for OpenType Sanitizer, also known as just "OTS". It is similar to and partially based on ots-python, but builds OTS as a Python C Extension (instead of as an executable and calling through subprocess as ots-python does).

NOTE: Although this package is similar to ots-python, it is not a drop-in replacement for it, as the Python API is different.

Requirements

The project builds pip-installable wheels for Python 3.10, 3.11, 3.12, 3.13, or 3.14 under Mac, Linux, or Windows. It is possible this project will build and run with other Pythons and other operating systems, but it has only been tested with the listed configurations.

Installation with pip

If you just want to use pyots, you can simply run python -m pip install -U pyots (in one of the supported platforms/Python versions) which will install pre-built, compiled, ready-to-use Python wheels. Then you can skip down to the Use section.

Installation/setup for developing pyots

If you'd like to tinker with the pyots code, you will want to get your local setup ready:

  • clone this repo
  • run python setup.py download to download the OTS source (which is not included in this project). You can modify the version value in setup.cfg under [download] to specify a different version of OTS. You'll also need to change the sha256 hash value that corresponds to the OTS tar.xz package. Note that this scheme has some limitations: OTS sources older than 8.1.3 might not build correctly since they used different build systems. Also, versions newer than the one specified in this repo might require adjustments in order to build correctly. What can we say, we're dependent on ots...
  • to build and install pyots after downloading OTS, you can run python setup.py install or python -m pip install .
  • while iterating changes, you will want to delete the temporary build and src/ots/build folders.

Testing

There is a test suite defined for exercising the Python extension. It makes use (and assumes the presence of) the downloaded OTS library source's test font data in src/ots so ensure you have run python setup.py download and have the ots folder under src. Invoke the tests with python -m pytest.

If you wish to run tests comparing results from ots-python against pyots, be sure to python -m pip install opentype-sanitizer first, otherwise that set of tests will be skipped.

Use

Simplest case:

import pyots

result = pyots.sanitize("/path/to/font/file.ttf")

result is an OTSResult object with 3 attributes:

  • sanitized Boolean indicating whether the file was successfully sanitized
  • modified Boolean indicating whether the file was modified* during sanitization
  • messages Tuple of message strings generated during sanitization (may be empty)
  • Note: currently the back-end OTS code can modify fonts that are successfully sanitized, even when no changes are performed. Thus modified can sometimes be True when sanitized is True. Usually the modification is only to the modification date and related checksums. Thus, it might be possible to devise a better detection of modification, i.e. ignoring head.modified and other inconsequential modifications, but that was out-of-scope for this work.

Example: sanitizing a folder of font files

# sanitize a folder of fonts. Print messages for any that were not successfully sanitized.
import pyots
from pathlib import Path

for filename in Path("src/ots/tests/fonts/good").rglob("*"):
    result = pyots.sanitize(filename.absolute())
    if not result.sanitized:
        print(f"{filename}:\n{', '.join([m for m in result.messages])}")

Options for sanitize()

  • Specify keyword output=<path_to_output_file> to the sanitize() command and the sanitized file will be saved to that location
  • Use quiet=True for sanitize() to suppress messages
  • Specify font_index=<index_in_TTC> when sanitizing a Collection (OTC/TTC) file and you want to sanitize only a particular index within the Collection (otherwise all will be sanitized per OTS's default behavior)

Project links

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Credits

Author: Adobe Type team & friends

GitHub Statistics

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License expression

BSD-3-Clause
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Requires

Python >=3.10

Classifiers

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