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Provide an overview in the README
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README.md

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# modernpython
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Code use in Modern Python videos
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Modern Python: Big ideas, Little Code
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=====================================
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This code is offered as an accompaniment to a Python Video course
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by Raymond Hettinger.
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Raymond runs an international Python training and consulting
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company and is available for basic, intermediate, and advanced
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python training.
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Getting Setup
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-------------
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1) Install the latest Python 3.6 (at least 3.6.1) from
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https://www.python.org
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2) Setup and activate a virtual environment:
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$ python3.6 -m venv modernpython
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$ source modernpython/bin/activate
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3) Install the packages used in the code
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(modernpython) $ pip install pyflakes
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(modernpython) $ pip install bottle
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(modernpython) $ pip install pytest
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(modernpython) $ pip install hypothesis
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(modernpython) $ pip install mypy
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Resampling
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----------
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This code demonstrates simulations, resampling, bootstrapping,
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hypothesis testing, and estimating confidence intervals.
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Machine Learning
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----------------
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The `kmeans.py` file implements k-means from scratch. The
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`congress_data` directory has CSV files with the voting histories
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of senators in the 114th U.S. Congress. The `congress.py` file
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demonstrates ETL (extract-transfrom-load) and unsupervised
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machine learning (k-means) to analyze the voting clusters.
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Publisher Subscriber
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--------------------
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This code implements a simple publisher-subscriber notification
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service. The `pubsub.py` implements the data model and core
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services. The `session.py` loads sample data. The `webapp.py`
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file runs a webserver for the application. The `views` directory
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has the Bottle templates and the `static` directory has the
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static resources (icons and photos).
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To start the service, run:
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(modernpython) $ python webapp.py
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Then point your browser to `http://localhost:8080/`
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The login information is in the `session.py` file.
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Testing
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-------
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The `quadratic.py` file is a module with a simple function to
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demonstrate various approaches to testing included in
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`test_quadratic.py`.
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Validation
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----------
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The `pricing_tool.py` file is used to demonstrate the descriptor
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based data validation tools in `validators.py`
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