text: # Copyright (C) 2019-2020 Moez Ali <moez.ali@queensu.ca>
  # License: MIT, moez.ali@queensu.ca
  
  """
    
  PyCaret - An end-to-end open source machine learning library
  
  Module Author:
  --------------
  pycaret.anomaly, Moez Ali <moez.ali@queensu.ca>
  pycaret.classification, Moez Ali <moez.ali@queensu.ca>
  pycaret.clustering, Moez Ali <moez.ali@queensu.ca>
  pycaret.datasets, Moez Ali <moez.ali@queensu.ca>
  pycaret.nlp, Moez Ali <moez.ali@queensu.ca>
  pycaret.preprocess, Fahad Akbar <M.akbar@queensu.ca>
  pycaret.regression, Moez Ali <moez.ali@queensu.ca>
  
  """
  
  from setuptools import setup
  
  def readme():
      with open('README.md') as f:
          README = f.read()
      return README
  
  
  setup(
      name="pycaret",
      version="0.0.38",
      description="A Python package for supervised and unsupervised machine learning.",
      long_description=readme(),
      long_description_content_type="text/markdown",
      url="https://github.com/pycaret/pycaret",
      author="Moez Ali",
      author_email="moez.ali@queensu.ca",
      license="MIT",
      classifiers=[
          "License :: OSI Approved :: MIT License",
          "Programming Language :: Python :: 3",
          "Programming Language :: Python :: 3.7",
      ],
      packages=["pycaret"],
      include_package_data=True,
      install_requires=["pandas", "numpy", "seaborn", "matplotlib", "IPython", "joblib", 
                       "scikit-learn==0.22", "shap==0.32.1", "ipywidgets", "yellowbrick==1.0.1", "xgboost==0.90",
                       "wordcloud", "textblob", "plotly==4.4.1", "cufflinks==0.17.0", "umap-learn",
                       "lightgbm==2.3.1", "pyLDAvis", "gensim", "spacy", "nltk", "mlxtend",
                       "pyod", "catboost==0.20.2", "pandas-profiling==2.3.0", "kmodes==0.10.1",
                       "datefinder==0.7.0", "datetime", "DateTime==4.3", "tqdm==4.36.1", "awscli"]
  )