{ "info": { "author": "Gertjan van den Burg", "author_email": "gertjanvandenburg@gmail.com", "bugtrack_url": null, "classifiers": [ "License :: OSI Approved :: MIT License", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: Implementation :: CPython", "Programming Language :: Python :: Implementation :: PyPy" ], "description": "==========\nlabella.py\n==========\n\n.. image:: https://travis-ci.org/GjjvdBurg/labella.py.svg?branch=master\n :target: https://travis-ci.org/GjjvdBurg/labella.py\n\n\nLabella.py is a Python 3 clone of `labella.js `_ \nwhich supports all the features of labella.js and addionally can generate TikZ PDF\nimages for use in LaTeX.\n\n**Note:** This package is for the most part a direct translation of the \noriginal `labella.js `_ code to Python \n3. All the credit for the labella code goes to Krist Wongsuphasawat (`@kristw \n`_), I only added the code which generates PDF \noutput. Labella.py also includes code from `d3 `_ \nfor axis scaling, and `WebCola `_ for the \nVPSC code (label placement optimization).\n\nWhy?\n====\nI wrote this for multiple reasons, the most important of which is that I \nwanted to incorporate label graphs like the ones generated by `labella.js \n`_ in PDF documents, but wasn't \nsatisfied with the PDF output generated by SVG-to-PDF converters. \nAdditionally, it seemed like a fun way to learn some more Javascript, and \nlearn about how `labella.js `_ works.\n\nScreenshots\n===========\nThese screenshots show the PDF output generated by labella.py (converted to \n.png)\n\nTime scale:\n\n.. image:: https://raw.githubusercontent.com/GjjvdBurg/labella.py/master/examples/timeline_kit_3.png\n :alt: Example of Labella.py output for a timeline\n :width: 100%\n :align: center\n\nLinear scale:\n\n.. image:: https://raw.githubusercontent.com/GjjvdBurg/labella.py/master/examples/timeline_kit_5.png\n :alt: Example of Labella.py output for a timeline\n :width: 100%\n :align: center\n\n\nUsage\n=====\nUsing labella.py is extremely similar to using \n`labella.js `_. See the \n`examples `_ directory \nfor examples of how to use labella.py. These examples are translations of the examples \nincluded in labella.js and in `d3kit-timeline `_.\n\nFor ease of use only the Timeline interface is implemented, which works \nsimilar to `d3kit-timeline `_. Here is \na minimal working example for exporting to PDF::\n\n >>> from labella.scale import LinearScale\n >>> from labella.timeline import TimelineTex\n >>> tl = TimelineTex([\n {'time': 1, 'text': 'Minimal'},\n {'time': 2, 'text': 'Working'},\n {'time': 3, 'text': 'Example'}\n ], options={'scale': LinearScale()})\n >>> tl.export('minimal.tex')\n\nSee also the documentation `here `_.\n\nInstallation\n============\n\nLabella.py is available through PyPi, so you can do::\n\n pip install labella\n\nto install it.\n\n**Note:** Labella.py requires a working LaTeX distribution for both SVG and \nPDF output (see also `the documentation `_), \nand has only been tested on Linux. If you run into problems, please open an issue on GitHub.\n\nAuthor\n======\n\nGertjan van den Burg (`@GjjvdBurg `_).\n\nLicensed under the `Apache License Version 2.0 `_.", "description_content_type": "text/x-rst", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/GjjvdBurg/labella.py", "keywords": "", "license": "Apache-2.0", "maintainer": "", "maintainer_email": "", "name": "labella", "package_url": "https://pypi.org/project/labella/", "platform": "", "project_url": "https://pypi.org/project/labella/", "project_urls": { "Homepage": "https://github.com/GjjvdBurg/labella.py" }, "release_url": "https://pypi.org/project/labella/0.9.3/", "requires_dist": null, "requires_python": ">=3.5.0", "summary": "Python clone of Labella.js that supports TikZ output", "version": "0.9.3" }, "last_serial": 5553371, "releases": { "0.9": [ { "comment_text": "", "digests": { "md5": "45228f0b68abc1bb75e7572939b96470", 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