{
    "info": {
        "author": "Grzegorz Chilczuk",
        "author_email": "chgrzegorz@pm.me",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "License :: OSI Approved :: GNU General Public License v2 (GPLv2)",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7"
        ],
        "description": "# Influ\n[![pipeline status](https://gitlab.com/chgrzegorz/dyplom-code/badges/develop/pipeline.svg)](https://gitlab.com/chgrzegorz/dyplom-code/commits/develop)\nFinding influencers in social network\n\nAn application created as part of the project\n#### Kto na kogo wp\u0142ywa w sieci spo\u0142ecznej - aplikacja do wyszukiwania kluczowych w\u0119z\u0142\u00f3w\n#### Who influences whom in social network - an application for finding key nodes\nAuthor: **Grzegorz Chilczuk**\n\nSupervisor: **dr in\u017c. Rados\u0142aw Michalski**\n\n## Installation\nOnly Python 3.6 or higher are supported.\n\nIf you have satisfied dependencies the installation should be as simple as \n```bash\npip install influ\n```\n\n### Dependencies\nAll dependencies will be installed automatically.\nHowever one of most important dependencies is cool python library called [igraph](https://github.com/igraph/python-igraph/) which core is written in C.\nSometimes it may cause some problem, [igraph documentation](https://igraph.org/python/#pyinstall) should help.\n\nAnother problematic dependency is `pycairo`, here you can find precise [documentation](https://pycairo.readthedocs.io/en/latest/).\n##### Debian / Ubuntu and derivatives\nInstalling those dependencies should help with both igraph and pycairo:\n```bash\n sudo apt install build-essential python-dev libxml2 libxml2-dev zlib1g-dev \n sudo apt install libcairo2-dev pkg-config\n```\n##### Windows\nIf you are using Windows you have to download unofficial installer of igraph [here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#python-igraph)\nand install it by executing:\n```bash\npip install <python_igraph-[igraph-version]-[python-version]-[windows version]>.whl\n```\nDespite that's unofficial it's recommended by maintainers of igraph library. \n\nThe `pycairo` library on Windows need `Microsoft Visual C++ 14.0` to be installed.\n\n#### MacOS\nThere were no attempts to install `influ` on MacOS. Any information about it will be appreciated.\n\n## Konect Reader\nIn order to test your concepts quickly there is a `KonectReader` which simplifies downloading and extracting datasets and loading them into Graph object. \n```python\nfrom influ import reader\n\nkr = reader.KonectReader()\nprint(kr.list) # list available datasets\ngraph = kr.load('manufacturing_emails')  # load dataset\n```\nCurrently there is only few datasets available but you can provide your own config file with other datasets specified. Currently only datasets from [Konect](http://konect.uni-koblenz.de) are supported.\n\n#### Your own config file\n```yaml\n# Content of my_custom_config.yaml\nexample_dataset:  # name that will be used to access dataset\n  name: Example Dataset 1\n  url: http://konect.uni-koblenz.de/networks/dataset_examle  # url where dataset is described [optional]\n  download: http://konect.uni-koblenz.de/downloads/tsv/dataset_examle.tar.bz2  # url where dataset can be downloaded directly\n  file: out.dataset_example_example  # name of file with \n  directed: False  # does graph should be considered as directed?\n  edge_attributes:  # list of names attributes\n    - distance      # if this list will be empty or there will be more attributes\n    - another_attr  # it will be named `attrX` where X is index counted from 0\n  vertex_attributes:                # list of vertex attributes with files where they are stored\n    - name: alias                   # name of attribute\n      file: ent.vertex_alias_name   # file with attribute\n```\n\nLoading your custom config extends (does not override) those previously loaded.\n```python\nfrom influ import reader\n\nkr = reader.KonectReader('./my_custom_config.yaml')  # loading at creation time\nkr.add_config('./my_custom_config.yaml')      # adding config after creation\n```\n\n## Working example\n```python\nfrom influ import reader, finder\n\nkr = reader.KonectReader()\ngraph = kr.load('manufacturing_emails')\n\nsfinder = finder.SeedFinder(graph)\nsfinder.configure(number=5, unit='number')\nresult = sfinder.greedy(model=finder.Model.IndependentCascade, depth=1)\nsfinder.plot_influence(result, model=finder.Model.IndependentCascade, depth=1)\n```\n\n# \u2014\u2014\u2014\u2014\u2014\u2014\n# Change log\n\n## [0.3.0]\n### Added\n- User documentation\n\n### Changed\n- Changed License to GNU GPLv2\n\n## [0.2.0] - 2018-12-14\n\n### Added\n- Model enum\n- plot_influence function\n- Windows installation documentation\n\n### Changed\n- Fix influence models evaluation with seed of random function\n- Few minor fixes\n\n## [0.1.0] - 2018-12-01\n\n### Added\n- Loading graph from file\n- Finding key nodes in graph (SeedFinder)\n- Loading example datasets from http://konect.uni-koblenz.de\n\n\n",
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