PgConf.Russia 2019

Python may not be the fastest programming language on the CPU, but its fast and easy development saves a lot of costs between the keyboard and the chair. In this workshop we'll explore the most popular library for the access to the PostgreSQL server named "psycopg2" and write a short application using some of its useful features.

Sometimes there is a great desire to return the database to the past, for a day or two or more days. The reasons are diverse, but most often one is to see what has changed. Or to see if the application behaved incorrectly after the update. Or it was just a command from the boss. The classic way everyone knows is to keep full backups and sets of WAL-logs to be able to recover to an arbitrary moment. This method is a real headache for DBAs/administrators, and it will not work quickly. Sure, there are some ways to optimize this process, but downtime is inevitable. PostgresPro offers a new way — database snapshots and the ability to return to them.

One of the most soft after features of Postgres v10 is logical replication. In this presentation we will cover what Logical Replication is, how it compares to Binary (Streaming Replication), how Logical Replication works, configuring Logical Replication, Logical Replication limitations, gotchas, security and management. We will also discuss potential deployed architectures with Logical and Binary Replication and some neat features of the underlying technology.

At the end of this presentation an attendee with a reasonable understanding of how to manage Postgres will be able to configure Logical replication for use.

Python may not be the fastest programming language on the CPU, but its fast and easy development saves a lot of costs between the keyboard and the chair. Since database clients spend most of their time waiting for a response from the database server, Python's asynchronous functionality available in the recent versions (3.5+) may help to optimize the application's runtime considerably by working on something else while server's response is being prepared. The asynchronous interface between Python and PostgreSQL is called "asyncpg". In the workshop we'll explore this library and write a short application using some of its useful features.