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content/pages/02-development-environments/06-jupyter-notebook.markdown

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* [mapboxgl-jupyter](https://github.com/mapbox/mapboxgl-jupyter) library along
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with the
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[quickstart](https://github.com/mapbox/mapboxgl-jupyter/blob/master/docs-markdown/viz.md)
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[quickstart](https://github.com/mapbox/mapboxgl-jupyter/blob/master/docs/viz.md)
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show you how to visualize geospatial data within your notebooks.
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* [Reproducible Data Analysis in Jupyter](https://jakevdp.github.io/blog/2017/03/03/reproducible-data-analysis-in-jupyter/)

content/pages/02-development-environments/14-pymux.markdown

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<div class="well see-also">Pymux is an implementation of the <a href="/terminal-multiplexers.html">terminal multiplexers</a> concept. Learn more in the <a href="/development-environments.html">development environments</a> chapter or view the <a href="/table-of-contents.html">table of contents</a> for all topics.</div>
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### Pymux resources
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* [Pymux, tmux clone in Python](http://blog.yjl.im/2016/01/pymux-tmux-clone-in-python.html)
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* [Pymux and tmux performance comparison](http://blog.yjl.im/2016/01/pymux-and-tmux-performance-comparison.html)
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* [Pymux discussion on Hacker News](https://news.ycombinator.com/item?id=10831149)

content/pages/02-development-environments/20-source-control.markdown

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disadvantages of common approaches used in both small and large
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organizations.
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* [In which I discuss Monorepos](https://storify.com/samnewman/in-which-i-discuss-monorepos)
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provides detail behind a series of tweets that explains source control
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monorepos.
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### Git distributed source control system
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[Git](/git.html) is the most widely-used source control system currently

content/pages/03-data/02-postgresql.markdown

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* [How to speed up tests in Django and PostgreSQL](http://nemesisdesign.net/blog/coding/how-to-speed-up-tests-django-postgresql/)
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explains some hacks for making your schema migration-backed run quicker.
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* [Full Text Search in Django using Database Back-Ends](http://www.machinalis.com/blog/full-text-search-on-django-with-database-back-ends/)
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provides code for both PostgreSQL and [MySQL](/mysql.html) for adding simple
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full text search into your application.
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* [Records](https://pypi.python.org/pypi/records/) is a wrapper around the psycopg2
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driver that allows easy access to direct SQL access. It's worth a look if
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you prefer writing SQL over using an
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past five years. It's amazing to see how far this project has come and
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how it continues to evolve.
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* [PostgreSQL: The Nice Bits](https://russ.garrett.co.uk/talks/postgres-gds/) is a
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good overview slideshow of why PostgreSQL is a great relational database.
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* [PostgreSQL Weekly](http://postgresweekly.com/) is a weekly newsletter of
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PostgreSQL content from around the web.
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content/pages/03-data/04-sqlite.markdown

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[object-relational mapper (ORM)](/object-relational-mappers-orms.html)
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to implement virtual tables and aggregates on top of SQLite.
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* [Using SQLite with Flask](http://flask.pocoo.org/docs/0.10/patterns/sqlite3/)
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explains how Flask code can directly query a SQLite database without an ORM.
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* [Use SQLite with Django On AWS Lambda with Zappa](https://blog.zappa.io/posts/use-sqlite-with-django-on-aws-lambda-with-zappa)
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provides an example `dev_settings.py` file for
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locally testing a [Django](/django.html) application intended for

content/pages/03-data/21-bokeh.markdown

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covers buildings two types of useful visualizations into your applications
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using Bokeh.
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* [Integrating Pandas, Django REST Framework and Bokeh](http://www.machinalis.com/blog/pandas-django-rest-framework-bokeh/)
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has a full example of integrating a
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[web API](/application-programming-interfaces.html) with a Bokeh
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front end visual.
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* [Interactive Visualization of Australian Wine Ratings](http://pbpython.com/wine_visualization.html)
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builds a non-trivial visualization with a nice sample set of data based
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on wine ratings.
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* [Visualization with Bokeh](http://www.blog.pythonlibrary.org/2016/07/27/python-visualization-with-bokeh/)
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* [Using Bokeh at NIST](https://www.continuum.io/blog/developer-blog/using-bokeh-nist)
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contains a real-world example of building an interactive visual to show
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firefighter gear data.
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* [Drawing a Brain with Bokeh](http://merqur.io/2015/10/02/drawing-a-brain-with-bokeh/)
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is a fun example of a chord diagram that represents neural connections in
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the brain.

content/pages/04-web-development/02-django.markdown

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contains a couple of good starter projects such as a live blog and a
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chat application to use as base code.
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* Channnels currently use Django's existing authentication scheme, but
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this blog post [JSON Web Tokens authentication on Django Channels](http://www.machinalis.com/blog/jwt-django-channels/)
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shows how to use a custom [JSON Web Token (JWT)](https://jwt.io/)
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implementation in Django Channels instead.
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* [Offloading work using Django Channels](http://www.machinalis.com/blog/offloading-work-using-django-channels/)
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is a short post that builds on a previous example to add a shared
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canvas with group updates via Channels, which would otherwise be difficult
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to accomplish in a Django web app without a persistent data transfer
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mechanism.
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## Django testing
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* [Integrating Front End Tools with Django](https://lincolnloop.com/blog/integrating-front-end-tools-your-django-project/)

content/pages/04-web-development/03-flask.markdown

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* [Flask Blueprint templates](http://fewstreet.com/2015/01/16/flask-blueprint-templates.html)
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shows a way of structuring your `__init__.py` file with
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[blueprints](http://flask.pocoo.org/docs/0.10/blueprints/) for expanding
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[blueprints](http://flask.pocoo.org/docs/latest/blueprints/) for expanding
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projects into many files and modules.
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* If you're not sure why `DEBUG` should be set to `False` in a production

content/pages/04-web-development/05-pyramid.markdown

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## Open source Pyramid example apps
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* [pyramid\_blogr](https://github.com/Pylons/pyramid_blogr) is an example
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project that shows how to build a blog with Pyramid modeled on the
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[Flaskr](http://flask.pocoo.org/docs/0.10/tutorial/introduction/) tutorial.
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[Flaskr](http://flask.pocoo.org/docs/latest/tutorial/introduction/) tutorial.
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* [pyramid\_appengine](https://github.com/twillis/pyramid_appengine)
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provides a project skeleton for running Pyramid on

content/pages/04-web-development/31-rq-redis-queue.markdown

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* [Flask by Example - Implementing a Redis Task Queue](https://realpython.com/blog/python/flask-by-example-implementing-a-redis-task-queue/)
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explains how to install and use RQ in a [Flask](/flask.html) application.
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* [Task Queues and Python RQ](http://blog.ashnab.com/task-queues-and-python-rq/)
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provides a good explanation for how to use RQ in a [Django](/django.html)
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project.
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* [rq-dashboard](https://github.com/eoranged/rq-dashboard) is an awesome
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[Flask](/flask.html)-based dashboard for viewing queues, workers and
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other critical information when using RQ.

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