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1 | 1 | from distutils.core import setup
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| 2 | + |
2 | 3 | setup(
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3 |
| - name = 'topicnet', # How you named your package folder (MyLib) |
4 |
| - packages = ['topicnet', 'topicnet.cooking_machine', 'topicnet.cooking_machine.models', 'topicnet.cooking_machine.cubes', 'topicnet.viewers'], # Chose the same as "name" |
5 |
| - version = '0.5.0', # Start with a small number and increase it with every change you make |
6 |
| - license='MIT', # Chose a license from here: https://help.github.com/articles/licensing-a-repository |
7 |
| - description = 'TopicNet is a module for topic modelling using ARTM algorithm', # Give a short description about your library |
8 |
| - author = 'Machine Intelligence Laboratory', # Type in your name |
9 |
| - author_email = 'alex.goncharov@phystech.edu', # Type in your E-Mail |
10 |
| - url = 'https://github.com/machine-intelligence-laboratory/TopicNet', # Provide either the link to your github or to your website |
11 |
| - download_url = 'https://github.com/machine-intelligence-laboratory/TopicNet/archive/v0.5.0.tar.gz', |
12 |
| - keywords = ['ARTM', 'topic', 'modelling', 'visualization'], # Keywords that define your package best |
13 |
| - install_requires=[ # I get to this in a second |
14 |
| - 'numpy', |
15 |
| - 'six', |
16 |
| - 'scipy', |
17 |
| - 'numexpr', |
18 |
| - 'pytest', |
19 |
| - 'pandas', |
20 |
| - 'tqdm', |
21 |
| - 'dask', |
22 |
| - 'scikit_learn', |
23 |
| - 'typing', |
24 |
| - 'ipython', |
25 |
| - 'strictyaml', |
26 |
| - 'plotly', |
27 |
| - 'colorlover', |
28 |
| - ], |
29 |
| - classifiers=[ |
30 |
| - 'Development Status :: 4 - Beta', # Chose either "3 - Alpha", "4 - Beta" or "5 - Production/Stable" as the current state of your package |
31 |
| - 'Intended Audience :: Developers', # Define that your audience are developers |
32 |
| - 'Topic :: Scientific/Engineering :: Artificial Intelligence', |
33 |
| - 'Topic :: Scientific/Engineering :: Information Analysis', |
34 |
| - 'License :: OSI Approved :: MIT License', # Again, pick a license |
35 |
| - 'Programming Language :: Python :: 3.6', |
36 |
| - ], |
| 4 | + name = 'topicnet', |
| 5 | + packages = [ |
| 6 | + 'topicnet', |
| 7 | + 'topicnet.cooking_machine', |
| 8 | + 'topicnet.cooking_machine.cubes', |
| 9 | + 'topicnet.cooking_machine.models', |
| 10 | + 'topicnet.viewers' |
| 11 | + ], |
| 12 | + version = '0.5.0', |
| 13 | + license='MIT', |
| 14 | + description = 'TopicNet is a module for topic modelling using ARTM algorithm', |
| 15 | + author = 'Machine Intelligence Laboratory', |
| 16 | + author_email = 'alex.goncharov@phystech.edu', |
| 17 | + url = 'https://github.com/machine-intelligence-laboratory/TopicNet', |
| 18 | + download_url = 'https://github.com/machine-intelligence-laboratory/TopicNet/archive/v0.5.0.tar.gz', |
| 19 | + keywords = [ |
| 20 | + 'ARTM', |
| 21 | + 'topic modeling', |
| 22 | + 'regularization', |
| 23 | + 'multimodal learning', |
| 24 | + 'document vector representation' |
| 25 | + ], |
| 26 | + install_requires=[ |
| 27 | + 'bigartm', |
| 28 | + 'colorlover', |
| 29 | + 'dask', |
| 30 | + 'dill', |
| 31 | + 'ipython', |
| 32 | + 'numexpr', |
| 33 | + 'numpy', |
| 34 | + 'pandas', |
| 35 | + 'plotly', |
| 36 | + 'pytest', |
| 37 | + 'scikit-learn', |
| 38 | + 'scipy', |
| 39 | + 'six', |
| 40 | + 'strictyaml', |
| 41 | + 'tqdm', |
| 42 | + ], |
| 43 | + classifiers=[ |
| 44 | + 'Development Status :: 4 - Beta', |
| 45 | + 'Intended Audience :: Developers', |
| 46 | + 'Topic :: Scientific/Engineering :: Artificial Intelligence', |
| 47 | + 'Topic :: Scientific/Engineering :: Information Analysis', |
| 48 | + 'License :: OSI Approved :: MIT License', |
| 49 | + 'Programming Language :: Python :: 3.6', |
| 50 | + ], |
37 | 51 | )
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