This PostgreSQL Python section shows you how to work with the PostgreSQL database using the Python programming language.

Python has various database drivers for PostgreSQL. Currently, the psycopg is the most popular PostgreSQL database adapter for the Python language. The psycopg fully implements the Python DB-API 2.0 specification.

The current version of the psycopg is 2 or psycopg2. The psycopg2 database adapter implemented in C as a libpq wrapper resulting in both fast and secure. The psycopg2 provides many useful features such as client-side and server-side cursors, asynchronous notification and communication, COPY command support, etc.

Besides, the psycopg2 driver supports many Python types out-of-the-box. The psycopg2 matches Python objects to the PostgreSQL data types, e.g., list to the array, tuples to records, and dictionary to hstore. If you want to customize and extend the type adaption, you can use a flexible object adaption system.

amnesia wraps everything exposed by mnesia, from fragments to fragment hash, access and backup behaviors.

It provides a simplified table and database definition with some macros and allows you to use the nice Enum functions on tables by implementing the Enum.Iterator protocol.

Everything is documented and specced, even the unspecced and undocumented parts of mnesia that have been wrapped.

The documentation often refers to mnesia functions, I strongly suggest you read mnesia's documentation too, since it has a lot of valuable information.

At a high level, Mnesia is a Database Management System (DBMS) that is baked into OTP. Thus, if you are using Elixir or Erlang, you have the ability to leverage Mnesia out-of-the-box. No additional dependencies need to be installed and no separate systems need to be running. Before considering migrating everything from your existing database to Mnesia, let's discuss what Mnesia was designed for and what problems it aims to solve.

Mnesia was largely designed to solve the problems that existed in the telecommunications problem space. Specifically, some of the following requirements needed to be fulfilled (check out this research paper for more details):

• Fast key/value lookup times where you need soft real-time latency guarantees. A soft real-time system is one where the system should be able to service the majority of its requests within a given time frame and a failure to do so generally means degradation of service (i.e the data is no longer useful after the time frame has passed). A hard real-time system, on the other hand, is a system that must respond within a given time frame or else it is considered a system failure.

• The ability to perform complex queries (like you would in SQL for example), but without soft real-time latency guarantees

• A high level of fault tolerance

• Github: amnesia - mnesia wrapper for Elixir