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At ep.io we built a Python hosting platform from the ground up, designed to run large numbers of web applications on a small number of physical machines both securely and in a reasonably scalable way. This talk will show you how we built our infrastructure - using Redis, eventlet, PostgreSQL and more - and what lessons we learnt from our first few thousand deploys.
See how we split services into multiple processes and greenthreads; the pains of building a cooperatively-multitasking PTY module; how Redis isn't the answer to everything, but is still very useful; how to persuade third-party software to work securely in a shared environment; and how important it is to have good logging, especially when you have more than five servers.
PostgreSQL (or “Postgres”) is an immensely powerful, incredibly extensible relational database, released under a permissive open source licence that is similar to that of CPython. PL/Python is one of PostgreSQL's standard server-side procedural languages, through which Python stored functions can be defined that can be called directly from SQL, quite seamlessly.
Play to the strengths of Postgres, by writing application business logic within the database in either Python 2 or Python 3. Enforce advanced business rules using Python, including constraints on both tables and database level datatypes (“domains”). By pushing the logic tier into the database, you can potentially greatly increasing your application's scalability by minimising the number of database roundtrips.
Includes case studies and topical coverage of PL/Python related enhancements in upcoming 9.1 release, and recent 9.0 release. The talk only assumes a very basic understanding of databases.
rdflib is a python library implementing a database with various triples back-end, parser, data serializers, SPARQL is a Python interface to extract/insert triples. We integrated it in Django reusing the database connection and exposing an ORM interface, along with full-text search on literals. This presentation shows a django-rdflib case study with a PostgreSQL backend in Brain Architecture Management System (http://brancusi1.usc.edu) - a neuroscientific project for the University of Southern California. Benefits of the flexible RDF structure will be shown, allowing researchers to insert free format data, making data public with a customizable serialization and use the powerful full-text search integrated in PostgreSQL.
Objective: show attendees an effective combination of RDF, PostgreSQL full-text search and Django ORM via django-rdflib.
Requirements: Django familiarity.
This talk is the updated and especially enhanced of the "Python and PostgreSQL - a match made in heaven" talk of EP 2006, CERN, Switzerland.
PostgreSQL and Python share more then the first letter: their communities have great similiarities; their development processes are really comparable; their licenses and their openness to academics AND business (on a technical and communitie perspective) are big pluses.
We will have a look at those similiarities and learn why PostgreSQL is really the database sister to Python. There will be an overview of PostgreSQL, information of how to connect PostgreSQL and Python; how PostgreSQL streaming replication works and what it can do for you, how PL/Python helps to have Web 2.5 JSON storage and handling right inside PostgreSQL. We will show that YESQL is also a valid answer to many data storage qeuestions.
PostgreSQL è un sistema open-source per la gestione di database molto avanzato ed estremamente versatile che si integra perfettamente con Python. E' sviluppato da una comunità internazionale molto attiva ed è distribuito secondo la licenza in stile BSD denominata "PostgreSQL License".
Le funzionalità di classe enterprise (come la conformità con lo standard SQL, le transazioni ACID, la disaster recovery, l'alta disponibilità o HA, la replica, il partizionamento e in generale l'estensibilità) rendono PostgreSQL particolarmente adatto per quegli ambienti business-critical che intendono ridurre il costo di proprietà totale (TCO) delle loro soluzioni di database senza alterarne i requisiti funzionali. PostgreSQL 9.0, rilasciato nel settembre del 2010, è stata la prima versione di PostgreSQL con Hot Standby, un meccanismo nativo per la replica master/slave. Al consueto e collaudato meccanismo di replica secondo la tecnica del log shipping (usata precedentemente per scopi di HA con Warm Standby) è stata aggiunta la replica in streaming.
La versione 9.1, attesa per la seconda parte del 2011, aggiungerà la replica sincrona a PostgreSQL, rendendolo il primo DBMS in grado di permettere a sviluppatori e utenti di controllare la strategia di replica a livello di singola transazione.
Partecipa al talk per scoprire tutte le altre funzionalità principali che saranno incluse in PostgreSQL 9.1, fra le quali: gestione delle estensioni, writable common table expression, ecc.
PostgreSQL is an advanced, versatile open-source database management system that integrates perfectly with Python. It is developed by a very active international community and is distributed under the BSD-like PostgreSQL License.
Enterprise-class features (including SQL standard compliance, ACID transactions, disaster recovery, high availability, replication, partitioning and general extensibility) make PostgreSQL suitable for business critical environments seeking to reduce the TCO of their database solutions without altering their functional needs. PostgreSQL 9.0, released in September 2010, was the first version of PostgreSQL with Hot Standby, a built-in master/slave replication mechanism. Asynchronous replication through the standard and consolidated log shipping technique (previously used with Warm Standby for high availability) has been enhanced with streaming replication.
Version 9.1, expected to be out later in 2011, will add synchronous replication to PostgreSQL, making it the first DBMS that allows developers and users to control the replication strategy at transactional granularity.
Come to the talk and discover all the major new features of PostgreSQL 9.1, including extensions management, writable common table expressions (WCTE), etc.
Hands-on training session on how to develop applications with Python for and inside a PostgreSQL database
PostgreSQL nowadays represents the perfect choice for an RDBMS for Python developers, given its compliance to the SQL standards and its integration with the Python language. PostgreSQL offers you as a Python developer two flexible approaches for writing their applications:
NOTE: This is a professional training given by certified instructors of our sponsor 2nd Quadrant. It is provided as a preview of their professional training services, and requires a separate registration fee of €100 (20% VAT included). You can buy a ticket for this training directly from this website.
In todays world, nobody (should) deploy a web application facing the
internet without having a proper caching system in place. There are
many different solutions to choose from, from manual use of memcached
through framework integrated caching to external caches like Squid or
Varnish. Most modern frameworks come with integrated functionality for
at least one of these methods, and often more than one.
However, they often relies on all traffic going through the same
framework to work properly - a caching layer in Rails is hard to share
with one in Django. This talk will show a way to break the design
rules of these frameworks just a little, and have the database help
solve this problem.
This talk will use a small application written in Python using Django
to illustrate the examples, but the method is language independent.
Unsurprisingly, the database used is PostgreSQL.
20th–26th June 2011