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            "Development Status :: 3 - Alpha",
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            "License :: OSI Approved :: MIT License",
            "Natural Language :: English",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Scientific/Engineering :: Artificial Intelligence"
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        "description": "<p align=\"left\">\n<img width=15% src=\"https://dai.lids.mit.edu/wp-content/uploads/2018/06/Logo_DAI_highres.png\" alt=\u201cmit-d3m\u201d />\n<i>An open source project from Data to AI Lab at MIT.</i>\n</p>\n\n\n[![Travis](https://travis-ci.org/HDI-Project/mit-d3m.svg?branch=master)](https://travis-ci.org/HDI-Project/mit-d3m)\n[![PyPi Shield](https://img.shields.io/pypi/v/mit-d3m.svg)](https://pypi.python.org/pypi/mit-d3m)\n\n\n# mit-d3m\n\n- License: MIT\n- Documentation: https://HDI-Project.github.io/mit-d3m/\n- Homepage: https://github.com/HDI-Project/mit-d3m\n\n# Overview\n\nMIT tools to work with D3M datasets.\n\n# Install\n\n## Requirements\n\n**mit-d3m** has been developed and tested on [Python 3.5, 3.6 and 3.7](https://www.python.org/downloads/)\n\nAlso, although it is not strictly required, the usage of a\n[virtualenv](https://virtualenv.pypa.io/en/latest/) is highly recommended in order to avoid\ninterfering with other software installed in the system where **mit-d3m** is run.\n\nThese are the minimum commands needed to create a virtualenv using python3.6 for **mit-d3m**:\n\n```bash\npip install virtualenv\nvirtualenv -p $(which python3.6) mit-d3m-venv\n```\n\nAfterwards, you have to execute this command to have the virtualenv activated:\n\n```bash\nsource mit-d3m-venv/bin/activate\n```\n\nRemember about executing it every time you start a new console to work on **mit-d3m**!\n\n## Install with pip\n\nAfter creating the virtualenv and activating it, we recommend using\n[pip](https://pip.pypa.io/en/stable/) in order to install **mit-d3m**:\n\n```bash\npip install mit-d3m\n```\n\nThis will pull and install the latest stable release from [PyPi](https://pypi.org/).\n\n## Install from source\n\nAlternatively, with your virtualenv activated, you can clone the repository and install it from\nsource by running `make install` on the `stable` branch:\n\n```bash\ngit clone git@github.com:HDI-Project/mit-d3m.git\ncd mit-d3m\ngit checkout stable\nmake install\n```\n\nFor development, you can use `make install-develop` instead in order to install all\nthe required dependencies for testing and code linting.\n\n\n# History\n\n## 0.2.0\n\n* `disk_usage` fails on macOS/BSD with human=True\n* Support latest d3m schema versions\n* Support python 3.7+\n\n## 0.1.2\n\n* Set the d3mIndex column as a DataFrame column in the TabularLoader\n\n## 0.1.1\n\n* Removal of unnecessary dependencies\n* Separate `tabular` into `single_table` and `multi_table`\n* Improve datasets stats collection.\n\n## 0.1.0\n\n* D3M Dataset parser\n* Loaders by Data Modality\n* Dataset Stats generator\n* Dataset Configuration generator\n* Metrics functions\n* MongoDB connector\n\n\n",
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