{ "info": { "author": "Paul Butler", "author_email": "penkit@paulbutler.org", "bugtrack_url": null, "classifiers": [], "description": "``penkit-optimize`` is a command-line tool for optimizing and visualizing the drawing order of SVG graphics for pen plotting. For more information, `see this post `_.\n\nInstallation\n~~~~~~~~~~~~\n\nThis package has a non-Python dependency, ``libspatialindex``. The easiest way to install it is by installing the ``rtree`` Python package via Conda::\n\n conda install rtree\n\nOnce this is installed, ``penkit-optimize`` can be installed via ``pip``::\n\n pip install penkit-optimize\n\nUsage\n~~~~~\n\nTo see CLI options::\n\n penkit-optimize -h\n usage: penkit-optimize [-h] [--greedy] [--noopt] [--runtime RUNTIME]\n [--merge-paths [MERGE_PATHS]] [--vis-output VIS_OUTPUT]\n input_file [output_file]\n\n positional arguments:\n input_file\n output_file\n\n optional arguments:\n -h, --help show this help message and exit\n --greedy, -g Run greedy optimization only.\n --noopt, -n Don't run any optimization.\n --runtime RUNTIME, -t RUNTIME\n Maximum runtime (in seconds) of optimization stage.\n --merge-paths [MERGE_PATHS], -m [MERGE_PATHS]\n Merge paths that start/end near each other. You may\n optionally specify a threshold distance (in document\n units) after this parameter.\n --vis-output VIS_OUTPUT, -v VIS_OUTPUT\n If provided, save a visualization of the path to this\n SVG file.\n\nExamples\n~~~~~~~~\n\nGenerate optimized SVG with default options (up to 5 minute runtime), and save to ``input-optimized.svg``::\n\n penkit-optimize input.svg\n\nDon't optimize anything, just visualize the transits::\n\n penkit-optimize input.svg -n -v noopt-vis.svg\n\n``noopt-vis.svg``:\n\n.. image:: examples/noopt-vis.svg\n\nRun greedy optimization (only), save the file, and save a visualization of the result::\n\n penkit-optimize input.svg output.svg -g -v greedy-vis.svg\n\n``greedy-vis.svg``:\n\n.. image:: examples/greedy-vis.svg\n\nRun the full optimization and write a visualization of the result::\n\n penkit-optimize input.svg output.svg -v opt-vis.svg\n\n``opt-vis.svg``:\n\n.. image:: examples/opt-vis.svg\n\nRun the full optimization and merge paths that start/end within 1.5 units::\n\n penkit-optimize input.svg -m 1.5", "description_content_type": "", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/paulgb/penkit/optimizer", "keywords": "", "license": "", "maintainer": "", "maintainer_email": "", "name": "penkit-optimize", "package_url": "https://pypi.org/project/penkit-optimize/", "platform": "", "project_url": "https://pypi.org/project/penkit-optimize/", "project_urls": { "Homepage": "https://github.com/paulgb/penkit/optimizer" }, "release_url": "https://pypi.org/project/penkit-optimize/0.0.2/", "requires_dist": null, "requires_python": "", "summary": "Experimental SVG optimizer using or-tools.", "version": "0.0.2" }, "last_serial": 3706284, "releases": { "0.0.1": [ { "comment_text": "", "digests": { "md5": "edf95008d0888bc06d12672c240685fe", "sha256": "0e0ab945e5a54157b366bf951c4f0cafc75873ceaf7374cca2fcd50e46845266" }, "downloads": -1, "filename": "penkit-optimize-0.0.1.tar.gz", "has_sig": false, "md5_digest": "edf95008d0888bc06d12672c240685fe", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 5629, "upload_time": "2018-03-26T11:51:50", "url": "https://files.pythonhosted.org/packages/6e/e8/d55936122b58a7392b1e6d66149d9626db5ef5830e462c0d0cc7c7a85966/penkit-optimize-0.0.1.tar.gz" } ], "0.0.2": [ { "comment_text": "", "digests": { "md5": "bc9ed2799897622c3a4af2f1bdc7a2a7", "sha256": "f48a954b13382d142f245763395f56a233958c130e7141dd0cc3292480e52494" }, "downloads": -1, "filename": "penkit-optimize-0.0.2.tar.gz", "has_sig": false, "md5_digest": "bc9ed2799897622c3a4af2f1bdc7a2a7", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 6671, "upload_time": "2018-03-26T12:23:48", "url": "https://files.pythonhosted.org/packages/5e/37/f57a4d749f55e2e497a1af811f253d5963268fcac414b666c8e6f23129de/penkit-optimize-0.0.2.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "bc9ed2799897622c3a4af2f1bdc7a2a7", "sha256": "f48a954b13382d142f245763395f56a233958c130e7141dd0cc3292480e52494" }, "downloads": -1, "filename": "penkit-optimize-0.0.2.tar.gz", "has_sig": false, "md5_digest": "bc9ed2799897622c3a4af2f1bdc7a2a7", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 6671, "upload_time": "2018-03-26T12:23:48", "url": "https://files.pythonhosted.org/packages/5e/37/f57a4d749f55e2e497a1af811f253d5963268fcac414b666c8e6f23129de/penkit-optimize-0.0.2.tar.gz" } ] }