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<!DOCTYPE html>

<title>Databases - Full Stack Python</title>

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<h1>Databases</h1>

<p>A database is an abstraction on top of an operating system's file system to

ease creating, reading, updating, and deleting persistent data. </p>

<h2>Why are databases necessary?</h2>

<p>At a high level web applications store data and present it to users in a

useful way. For example, Google stores data about roads and provides

directions to get from one location to another by driving through the

<a href="https://www.google.com/maps/">Maps</a> application. Driving directions are

possible because the data is stored in a structured way. </p>

<p>Databases make structured storage reliable and fast. They also give you a

mental framework for how the data should be saved and retrieved instead of

having to figure out what to do with the data every time you build a new

application.</p>

<h2>Relational databases</h2>

<p>The database storage abstraction most commonly used in Python web development

is sets of relational tables. Alternative storage abstractions are explained

in the <a href="../no-sql-datastore.html">NoSQL</a> section of this guide.</p>

<p>Relational databases store all data in a series of tables. Interconnections

between the tables are specified as <em>foreign keys</em>.</p>

<p>Databases storage implementations vary in complexity. SQLite, a database

included with Python, creates a single file for all data per database.

Other databases such as Oracle, PostgreSQL, and MySQL have more complicated

persistence schemes while offering additional advanced features that are

useful for web application data storage.</p>

<p><a href="http://www.postgresql.org/">PostgreSQL</a> and

<a href="http://www.mysql.com/">MySQL</a> are two of the most common open source

databases for storing Python web application data.</p>

<p><a href="http://www.sqlite.org/">SQLite</a> is a database that is stored in a single

file on disk. SQLite is built into Python but is only built for access

by a single connection at a time. Therefore is highly recommended to not

<a href="https://docs.djangoproject.com/en/dev/ref/databases/#database-is-locked-errors">run a production web application with SQLite</a>.</p>

<h2>PostgreSQL</h2>

<p>PostgreSQL is the recommended relational database for working with Python

web applications. PostgreSQL's feature set, active development and stability

contribute to its usage as the backend for millions of applications live

on the Web today.</p>

<h3>PostgreSQL resources</h3>

<ul>

<li>

<p>This post on

<a href="http://killtheyak.com/use-postgresql-with-django-flask/">using PostgreSQL with Django or Flask</a>

is a great quickstart guide for either framework.</p>

</li>

<li>

<p><a href="http://postgresweekly.com/">PostgreSQL Weekly</a> is a weekly newsletter of

PostgreSQL content from around the web.</p>

</li>

<li>

<p>Braintree wrote about their experiences <a href="https://www.braintreepayments.com/braintrust/scaling-postgresql-at-braintree-four-years-of-evolution">scaling PostgreSQL</a>.

The post is an inside look at the evolution of Braintree's usage of the database.</p>

</li>

<li>

<p>This post estimates the <a href="http://hans.io/blog/2014/02/19/postgresql_connection/index.html">costs of a PostgreSQL connection</a>.</p>

</li>

<li>

<p>There is no such thing as total security but this IBM article covers

<a href="http://www.ibm.com/developerworks/library/os-postgresecurity/">hardening a PostgreSQL database</a>. </p>

</li>

<li>

<p>Craig Kerstien's wrote a detailed post about <a href="http://www.craigkerstiens.com/2012/10/01/understanding-postgres-performance/">understanding PostgreSQL performance</a>.</p>

</li>

<li>

<p><a href="http://instagram-engineering.tumblr.com/post/40781627982/handling-growth-with-postgres-5-tips-from-instagram">Handling growth with Postgres</a>

provides 5 specific tips from Instagram's engineering team on how to scale

the design of your PostgreSQL database.</p>

</li>

<li>

<p><a href="http://patshaughnessy.net/2014/10/13/following-a-select-statement-through-postgres-internals">Following a Select Statement Through Postgres Internals</a>

provides a fascinating look into the internal workings of PostgreSQL

during a query.</p>

</li>

<li>

<p>This article explains how and why PostgreSQL can handle <a href="http://blog.lostpropertyhq.com/postgres-full-text-search-is-good-enough/">full text searching</a>

for many use cases.</p>

</li>

</ul>

<h2>MySQL</h2>

<p>MySQL is another viable open source database backend option for Python web

applications. MySQL has a slightly easier initial learning curve than

PostgreSQL. The database is deployed in production at some of the highest

trafficked sites such as

<a href="https://blog.twitter.com/2012/mysql-twitter">Twitter</a>,

<a href="https://www.facebook.com/notes/facebook-engineering/mysql-and-database-engineering-mark-callaghan/10150599729938920">Facebook</a>

and <a href="http://www.mysql.com/customers/">many others major organizations</a>.

However, since the company focused on MySQL development,

<a href="http://en.wikipedia.org/wiki/MySQL_AB">MySQL AB</a>, was

purchased by Sun Microsystems (which was in turn purchased by Oracle), there

have been major defections away from the database by

<a href="http://www.zdnet.com/wikipedia-moving-from-mysql-to-mariadb-7000008912/">Wikipedia</a>

and <a href="http://readwrite.com/2013/09/14/google-waves-goodbye-to-mysql-in-favor-of-mariadb">Google</a>.

MySQL remains a viable database option but I always recommend new Python

developers learn PostgreSQL if they do not already know MySQL.</p>

<h3>MySQL resources</h3>

<ul>

<li>

<p><a href="http://designm.ag/tutorials/28-beginners-tutorials-for-learning-about-mysql-databases/">28 Beginner's Tutorials for Learning about MySQL Databases</a>

is a curated collection on various introductory MySQL topics.</p>

</li>

<li>

<p>This tutorial shows how to install <a href="http://www.cs.wcupa.edu/rkline/index/mysql-lin.html">MySQL on Ubuntu</a>.</p>

</li>

<li>

<p><a href="http://moderndata.plot.ly/graph-data-from-mysql-database-in-python/">Graph Data From MySQL Database in Python</a>

is an interesting study with code of how to pull data out of MySQL and graph

the data with Plotly.</p>

</li>

</ul>

<h2>Connecting to a database with Python</h2>

<p>To work with a relational database using Python, you need to use a code

library. The most common libraries for relational databases are:</p>

<ul>

<li>

<p><a href="http://initd.org/psycopg/">psycopg2</a> for PostgreSQL</p>

</li>

<li>

<p><a href="https://pypi.python.org/pypi/MySQL-python/1.2.4">MySQLdb</a> for MySQL</p>

</li>

<li>

<p><a href="http://cx-oracle.sourceforge.net/">cx_Oracle</a> for Oracle</p>

</li>

</ul>

<p>SQLite support is built into Python 2.7+ and therefore a separate library

is not necessary. Simply "import sqlite3" to begin interfacing with the

single file-based database.</p>

<h2>Object-Relational Mapping</h2>

<p>Object-relational mappers (ORMs) allow developers to access data from a

backend by writing Python code instead of SQL queries. Each web

application framework handles integrating ORMs differently. </p>

<p>Django provides an ORM with its core functionality. Flask leaves using an

ORM up to an extension, such as

<a href="http://pythonhosted.org/Flask-SQLAlchemy/">Flask-SQLALchemy</a>. </p>

<p>Developers can also use ORMs without a web framework, such as when

creating a data analysis tool or a batch script without a user interface.

Currently, the most widely used stand-alone ORM written for Python is

<a href="http://www.sqlalchemy.org/">SQLAlchemy</a>.</p>

<p>If you're interested in the differences between SQLAlchemy and the Django

ORM I highly recommend reading

<a href="http://lucumr.pocoo.org/2011/7/19/sqlachemy-and-you/">SQLAlchemy and You</a>

by Armin Ronacher.</p>

<h2>Database third-party services</h2>

<p>Numerous companies run scalable database servers as a hosted service.

Hosted databases can often provide automated backups and recovery,

tightened security configurations and easy vertical scaling, depending on the

provider.</p>

<ul>

<li>

<p><a href="http://aws.amazon.com/rds/">Amazon Relational Database Service (RDS)</a>

provides pre-configured MySQL and PostgreSQL instances. The instances can

be scaled to larger or smaller configurations based on storage and performance

needs.</p>

</li>

<li>

<p><a href="https://developers.google.com/cloud-sql/">Google Cloud SQL</a> is a service

with managed, backed up, replicated, and auto-patched MySQL instances. Cloud

SQL integrates with Google App Engine but can be used independently as well.</p>

</li>

<li>

<p><a href="http://www.gobitcan.com/">BitCan</a> provides both MySQL and MongoDB hosted

databases with extensive backup services.</p>

</li>

</ul>

<h2>Database resources</h2>

<ul>

<li>

<p><a href="https://medium.com/@jeeyoungk/why-i-love-databases-1d4cc433685f">Why I Love Databases</a>

is a great read on the CAP Theorem, distributed systems and other topics

that are at the core of database theory and implementation. Well worth

the time to read.</p>

</li>

<li>

<p><a href="http://www.pg-versus-ms.com/">PostgreSQL vs. MS SQL Server</a> is one

perspective on the differences between the two database servers from a

data analyst.</p>

</li>

<li>

<p><a href="http://db-engines.com/en/ranking">DB-Engines</a> ranks the most popular

database management systems.</p>

</li>

<li>

<p><a href="http://dbweekly.com/">DB Weekly</a> is a weekly roundup of general database

articles and resources.</p>

</li>

<li>

<p><a href="http://www.pythoncentral.io/sqlalchemy-vs-orms/">SQLAlchemy vs Other ORMs</a>

provides a detailed comparison of SQLAlchemy against alternatives.</p>

</li>

<li>

<p><a href="http://blog.isotoma.com/2014/05/a-different-view/">A different view</a>

provides some perspective on the impedance mismatch between ORMs and

traditional SQL queries.</p>

</li>

<li>

<p><a href="https://julien.danjou.info/blog/2014/db-integration-testing-strategies-python">Databases integration testing strategies</a>

covers a difficult topic that comes up on every real world project.</p>

</li>

</ul>

<h2>Databases learning checklist</h2>

Install PostgreSQL on your server. Assuming you went with Ubuntu run

<code>sudo apt-get install postgresql</code>.</p>

Make sure the <a href="http://initd.org/psycopg/">psycopg2</a> library is part of your

application dependencies.</p>

Configure your web application to connect to the PostgreSQL instance.</p>

Create models in your ORM, either with Django's

<a href="https://docs.djangoproject.com/en/dev/topics/db/">built-in ORM</a> or

<a href="http://www.sqlalchemy.org/">SQLAlchemy with Flask</a>. </p>

Sync the ORM models with the PostgreSQL instance.</p>

Start creating, reading, updating and deleting data in the database from your

web application.</p>

<h3>What's next to get your app running?</h3>

What about non-relational data stores hipsters tell me to use?

</p>

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My app is running but looks awful. How do I style the interface?

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How do I log issues when they occur in my app?

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<div class="panel-heading"><h3 class="panel-head">Databases</h3></div>

<a href="/">Full Stack Python</a> is an open book that explains

each Python web application stack layer and provides the

best web resources for those topics.

<hr/>

There's a work-in-progress

<a href="/full-stack-python-map.pdf">subjects map (.pdf)</a>

that visually lays out each chapter in addition to the table of

contents found below.

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to see the daily changes.

</div>

<h3 class="panel-head">Table of Contents</h3>

</div>

<a href="/introduction.html" class="list-group-item smaller-item ">Introduction</a>

<a href="/web-frameworks.html" class="list-group-item smaller-item ">Web Frameworks</a>

<a href="/django.html" class="list-group-item smaller-item ">Django</a>

<a href="/flask.html" class="list-group-item smaller-item ">Flask</a>

<a href="/bottle.html" class="list-group-item smaller-item ">Bottle</a>

<a href="/morepath.html" class="list-group-item smaller-item ">Morepath</a>

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