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README.md
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README.md
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@ -262,17 +262,18 @@ Inspired by [awesome-php](https://github.com/ziadoz/awesome-php).
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*Libraries for building command-line application.*
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*Libraries for building command-line application.*
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* Command-line Application Development
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* Command-line Application Development
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* [asciimatics](https://github.com/peterbrittain/asciimatics) - A package to create full-screen text UIs (from interactive forms to ASCII animations).
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* [bashplotlib](https://github.com/glamp/bashplotlib) - Making basic plots in the terminal.
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* [cement](http://builtoncement.com/) - CLI Application Framework for Python.
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* [cement](http://builtoncement.com/) - CLI Application Framework for Python.
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* [click](http://click.pocoo.org/dev/) - A package for creating beautiful command line interfaces in a composable way.
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* [click](http://click.pocoo.org/dev/) - A package for creating beautiful command line interfaces in a composable way.
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* [cliff](https://docs.openstack.org/developer/cliff/) - A framework for creating command-line programs with multi-level commands.
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* [cliff](https://docs.openstack.org/developer/cliff/) - A framework for creating command-line programs with multi-level commands.
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* [clint](https://github.com/kennethreitz/clint) - Python Command-line Application Tools.
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* [clint](https://github.com/kennethreitz/clint) - Python Command-line Application Tools.
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* [colorama](https://pypi.python.org/pypi/colorama) - Cross-platform colored terminal text.
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* [docopt](http://docopt.org/) - Pythonic command line arguments parser.
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* [docopt](http://docopt.org/) - Pythonic command line arguments parser.
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* [Gooey](https://github.com/chriskiehl/Gooey) - Turn command line programs into a full GUI application with one line
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* [Gooey](https://github.com/chriskiehl/Gooey) - Turn command line programs into a full GUI application with one line.
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* [Python-Fire](https://github.com/google/python-fire) - A library for creating command line interfaces from absolutely any Python object.
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* [Python-Fire](https://github.com/google/python-fire) - A library for creating command line interfaces from absolutely any Python object.
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* [python-prompt-toolkit](https://github.com/jonathanslenders/python-prompt-toolkit) - A library for building powerful interactive command lines.
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* [python-prompt-toolkit](https://github.com/jonathanslenders/python-prompt-toolkit) - A library for building powerful interactive command lines.
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* Terminal Rendering
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* [asciimatics](https://github.com/peterbrittain/asciimatics) - A package to create full-screen text UIs (from interactive forms to ASCII animations).
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* [bashplotlib](https://github.com/glamp/bashplotlib) - Making basic plots in the terminal.
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* [colorama](https://pypi.python.org/pypi/colorama) - Cross-platform colored terminal text.
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* Productivity Tools
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* Productivity Tools
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* [aws-cli](https://github.com/aws/aws-cli) - A universal command-line interface for Amazon Web Services.
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* [aws-cli](https://github.com/aws/aws-cli) - A universal command-line interface for Amazon Web Services.
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* [cookiecutter](https://github.com/audreyr/cookiecutter) - A command-line utility that creates projects from cookiecutters (project templates).
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* [cookiecutter](https://github.com/audreyr/cookiecutter) - A command-line utility that creates projects from cookiecutters (project templates).
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@ -343,7 +344,7 @@ Inspired by [awesome-php](https://github.com/ziadoz/awesome-php).
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* [Open Mining](https://github.com/mining/mining) - Business Intelligence (BI) in Pandas interface.
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* [Open Mining](https://github.com/mining/mining) - Business Intelligence (BI) in Pandas interface.
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* [Orange](https://orange.biolab.si/) - Data mining, data visualization, analysis and machine learning through visual programming or scripts.
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* [Orange](https://orange.biolab.si/) - Data mining, data visualization, analysis and machine learning through visual programming or scripts.
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* [Pandas](http://pandas.pydata.org/) - A library providing high-performance, easy-to-use data structures and data analysis tools.
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* [Pandas](http://pandas.pydata.org/) - A library providing high-performance, easy-to-use data structures and data analysis tools.
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* [Optimus](https://github.com/ironmussa/Optimus) - Cleansing, pre-processing, feature engineering, exploratory data analysis and easy Machine Learning with a PySpark backend.
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* [Optimus](https://github.com/ironmussa/Optimus) - Cleansing, pre-processing, feature engineering, exploratory data analysis and easy Machine Learning with a PySpark backend.
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## Data Validation
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## Data Validation
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