{ "info": { "author": "Makhmudov Evgeniy", "author_email": "john_16@list.ru", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Intended Audience :: Developers", "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", "Programming Language :: Python", "Topic :: Software Development :: Libraries" ], "description": "=======\nSummary\n=======\n\nLaminated provide dictionary like object with the layers support. The\ngeneral suppose is a data set with fluctuations in differents pieces.\n\n--------------\nQuick Examples\n--------------\n\nExample 1\n---------\n\n.. code:: python\n\n from laminated import Laminated\n\n # The company FOO has employeers with this paymenths in month\n inition_employee_pay = {\n 'John': 120000,\n 'Mike': 150000,\n 'Sara': 80000,\n 'David': 60000,\n }\n\n l = Laminated()\n l.add_layer(\n name='2017-01',\n data=inition_employee_pay,\n )\n\n # John have increase pays in february\n l.add_layer(\n name='2017-02',\n data={\n 'John': 130000,\n },\n )\n\n # March have no any differences, that layer is empty\n l.add_layer({}, '2017-03')\n\n # In April Sara groing up\n l.add_layer(\n name='2017-04',\n data={\n 'Sara': 100000,\n },\n )\n\n # how many company FOO spend money on they workers by months\n amount = 0\n for month in l.get_layers_names():\n for employee in l:\n amount += l.get_value_at_layer(month, employee)\n\n # the result will be 1690000\n print('Total amount of pays is {}'.format(amount))", "description_content_type": null, "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/EvgeniyMakhmudov/laminated", "keywords": "dict dictionary layers", "license": "MIT", "maintainer": "", "maintainer_email": "", "name": "laminated", "package_url": "https://pypi.org/project/laminated/", "platform": "", "project_url": "https://pypi.org/project/laminated/", "project_urls": { "Homepage": "https://github.com/EvgeniyMakhmudov/laminated" }, "release_url": "https://pypi.org/project/laminated/0.1.2.1/", "requires_dist": null, "requires_python": "", "summary": "Dictionary like object with layers support", "version": "0.1.2.1" }, "last_serial": 3453367, "releases": { "0.1": [ { "comment_text": "", "digests": { "md5": "3362dec90dde550c30b48a3ff9c524dd", "sha256": "811f46eb449cab3c091a731b935df90dee144e388e5d4bccdc38ecbffd083c2d" }, "downloads": -1, "filename": "laminated-0.1-py2.py3-none-any.whl", "has_sig": false, "md5_digest": "3362dec90dde550c30b48a3ff9c524dd", "packagetype": "bdist_wheel", "python_version": "py2.py3", "requires_python": null, "size": 4100, "upload_time": "2017-10-25T22:00:57", "url": "https://files.pythonhosted.org/packages/f7/d9/e4d493a34af5f0ac2f630741ed75580a04cc5e74511ad051767232fc5779/laminated-0.1-py2.py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "23269cd2e730fda146c42ac861f6d452", "sha256": "2276678284fc8a1c42cae07b4b3c45e77675e6e4790aa25c1820eb08baeed66a" }, "downloads": -1, "filename": "laminated-0.1.tar.gz", "has_sig": false, "md5_digest": "23269cd2e730fda146c42ac861f6d452", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 2606, "upload_time": "2017-10-25T22:00:58", "url": "https://files.pythonhosted.org/packages/c8/72/f5a586b70e0e58f3076d672e3b9e3af9d67f993f6717dce1fc8333fcd3af/laminated-0.1.tar.gz" } ], "0.1.2": [ { "comment_text": "", "digests": { "md5": "35df62c03affddf132eaef9bfeaeac79", "sha256": "6ee9c41a8a724157b3eaca677bbceb13343566a8b7bc83f9da100b4832ed18f0" }, "downloads": -1, "filename": "laminated-0.1.2.linux-x86_64.tar.gz", "has_sig": false, "md5_digest": "35df62c03affddf132eaef9bfeaeac79", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 3283, "upload_time": "2017-12-31T15:35:21", "url": "https://files.pythonhosted.org/packages/c4/ae/d453d9a75f89c64894cb54e2139611af9affe1d37dfd557d887bc9d1842d/laminated-0.1.2.linux-x86_64.tar.gz" } ], "0.1.2.1": [ { "comment_text": "", "digests": { "md5": "0715af538c0e6125a8bc71fb42146f0d", "sha256": "a95c830d8c5217e73d58bbe18e5367cb6cfcade48d88d109dea6304d29cc70b0" }, "downloads": -1, "filename": "laminated-0.1.2.1.tar.gz", "has_sig": false, "md5_digest": "0715af538c0e6125a8bc71fb42146f0d", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 2650, "upload_time": "2017-12-31T15:39:12", "url": "https://files.pythonhosted.org/packages/1d/ba/bd9aae4e3d249aefa4291938ab3b2203d0806c8082cf02555271cff1cb62/laminated-0.1.2.1.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "0715af538c0e6125a8bc71fb42146f0d", "sha256": "a95c830d8c5217e73d58bbe18e5367cb6cfcade48d88d109dea6304d29cc70b0" }, "downloads": -1, "filename": "laminated-0.1.2.1.tar.gz", "has_sig": false, "md5_digest": "0715af538c0e6125a8bc71fb42146f0d", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 2650, "upload_time": "2017-12-31T15:39:12", "url": "https://files.pythonhosted.org/packages/1d/ba/bd9aae4e3d249aefa4291938ab3b2203d0806c8082cf02555271cff1cb62/laminated-0.1.2.1.tar.gz" } ] }