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content/pages/03-data/15-data-analysis.markdown

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a data analysis job and convert dirty data into a more consistent,
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structured format.
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* [9 obscure Python libraries for data science](https://opensource.com/article/18/11/python-libraries-data-science)
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presents several lesser-known but still very useful libraries for
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performing data analysis such as
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[fuzzywuzzy](https://github.com/seatgeek/fuzzywuzzy)
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and
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[gym](https://github.com/openai/gym).

content/pages/04-web-development/24-react.markdown

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<div class="well see-also">React is an implementation of the <a href="/javascript.html">JavaScript frameworks</a> concept. Learn how these pieces fit together in the <a href="/web-development.html">web development</a> chapter or view the <a href="/table-of-contents.html">table of contents</a> for all topics.</div>
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### Beginner React tutorials
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Generally before you start working with React you will want to learn how
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to build your Python backend with a [web framework](/web-framework.html)
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such as [Django](/django.html), [Flask](/flask.html) or
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[Pyramid](/pyramid.html). Once you get comfortable with the
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[web development](/web-development.html) basics with one of those frameworks
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as well as [JavaScript](/javascript.html) then it will be much easier to
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tack on React to build your client-side user interfaces.
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* [JavaScript fundamentals before learning React](https://www.robinwieruch.de/javascript-fundamentals-react-requirements/)
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provides a gut check that you have the prerequisite knowledge to avoid
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getting impossibly stuck while trying to learn React.
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* The [official React tutorial](https://reactjs.org/tutorial/tutorial.html)
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is one of the best ways to start using React because many other tutorials
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quickly fall out of date while this one tends to stick to the basics
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that are relevant to beginners.
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* [Django REST with React (Django 2.0 and a sprinkle of testing)](https://www.valentinog.com/blog/tutorial-api-django-rest-react/)
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combines a [Django](/django.html) plus
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[Django REST Framework (DRF)](/django-rest-framework-drf.html) backend
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with React on the front end and shows how to stich it all together.
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* [Build a Simple CRUD App with Python, Flask, and React](https://developer.okta.com/blog/2018/12/20/crud-app-with-python-flask-react)
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shows how to combine a [Flask](/flask.html) backend with React.
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* [Learn React app](https://github.com/tyroprogrammer/learn-react-app)
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is a Git repository with a code tutorial and instructions for how to
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follow along, as well as exercises to ensure you are tested as you go.
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* [9 things every React.js beginner should know](https://camjackson.net/post/9-things-every-reactjs-beginner-should-know)
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is not a tutorial but instead the author gives some strong opinions for
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what beginners should know as they start learning React.
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### Other React resources
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* [React interview questions](https://tylermcginnis.com/react-interview-questions/)
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is a good quiz to see what you know or still need to learn about the
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fundamentals of using React.
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* [Building a Serverless Stripe Analytics Dashboard](https://statsbot.co/blog/building-serverless-stripe-analytics-dashboard/)
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shows how to work with the [Stripe](/stripe.html) API to build a
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dashboard in React then serve the static assets from AWS S3.
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* [Under-the-hood-ReactJS](https://bogdan-lyashenko.github.io/Under-the-hood-ReactJS/)
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examines the React codebase itself rather than teaching you how to use it.

content/pages/05-deployment/01-hosting.markdown

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* [VPS $5 Showdown - October 2018 - DigitalOcean vs. Lightsail vs. Linode vs. Vultr](https://joshtronic.com/2018/10/15/vps-showdown-october-2018/)
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compares and contrasts the cheapest options for four popular virtual
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private server providers.
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* [VPS comparisons](https://github.com/joedicastro/vps-comparison) uses
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[Ansible](/ansible.html) to get some data around provisioning speed
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and system performance. The whole
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[README](https://github.com/joedicastro/vps-comparison/blob/master/README.org)
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file in that repository has a ton of useful information and summaries
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of the tested providers.

content/pages/05-deployment/07-digitalocean.markdown

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# DigitalOcean
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DigitalOcean is a virtual private server provider and deployment
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platform that can be used for running Python applications.
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<a href="https://do.co/fsp" style="border: none;"><img src="/img/logos/digitalocean.png" width="100%" alt="Official DigitalOcean logo. Copyright DigitalOcean." class="shot" style="padding: 12px 0 12px 0"></a>
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### DigitalOcean examples
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* [Creating a Kubernetes Cluster on DigitalOcean with Python and Fabric](https://testdriven.io/blog/creating-a-kubernetes-cluster-on-digitalocean/)
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shows how to configure a three node Kubernetes cluster using
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[Ubuntu](/ubuntu.html) 16.04 LTS.
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* [Setting up a Digital Ocean server for Selenium, Chrome, and Python](http://jonathansoma.com/lede/algorithms-2017/servers/setting-up/)
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gives the code and instructions for setting up a testing server
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that uses Selenium for executing user interface tests.
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* The [digitalocean tag](https://github.com/topics/digitalocean) on GitHub
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has a slew of open source projects such as
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[digitalocean-developer-firewall](https://github.com/ErlendEllingsen/digitalocean-developer-firewall)
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to make it easier to configure firewalls and other services on your
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droplets.

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