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Articles tagged: python

This year, I was so excited about doing a workshop about optimizing Python & Django apps with Postgres superpowers for the PyCon 2020 conference.

Working with other developers on performance is something I always find amazing. So props to the Python people at Microsoft who encouraged my team to create a workshop on Postgres for PyCon 2020. Thank you to Nina Zakharenko, Dan Taylor, & Crystal Kelch.

Alas, we had to change our plans and find other ways to share the PostgreSQL workshop content that we had prepared. So I created a video on the topic of database performance for Django developers, to help teach you the PostgreSQL tips and tricks that have served me well in optimizing my Django apps. These tips are what I call “Postgres superpowers.”

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When Django developer and Azure Postgres* engineer Louise Grandjonc confirmed that she could sit down with me for an interview in the days leading up to DjangoCon 2019, I jumped at the chance. Those of you who were in the room for Louise’s talk this week probably understand why. Louise explains technical topics in a way that makes sense—and she often uses unusual (and fun) examples, from crocodiles to owls, from Harry Potter to Taylor Swift.

And since I experience a bit of FOMO whenever I miss a fun developer conference like DjangoCon, I especially wanted to learn more about Louise’s DjangoCon talk: Postgres Index Types and where to find them.

Here’s an edited transcript of my interview with Louise Grandjonc of Microsoft (@louisemeta on Twitter.)

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Sai Krishna Srirampur

Scaling out your Django Multi-tenant App

Written byBy Sai Srirampur | November 14, 2017Nov 14, 2017

There are a number of data architectures you could use when building a multi-tenant app. Some, such as using one database per customer or one schema per customer, have trade-offs when it comes to larger scale. The other option is to build the notion of tenancy directly into the logic of your SaaS application. With django-multitenant and Citus, built-in tenancy becomes much easier to put in place for your application without having to re-invent the wheel yourself.

Our django-multitenant Python library, enables easy scale out of applications that are built on top of Django and follow a multi tenant data model. This Python library has evolved from our experience working with SaaS customers, scaling out their multi-tenant apps.

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Craig Kerstiens

Faster bulk loading in Postgres with copy

Written byBy Craig Kerstiens | November 8, 2017Nov 8, 2017

If you’ve used a relational database, you understand basic INSERT statements. Even if you come from a NoSQL background, you likely grok inserts. Within the Postgres world, there is a utility that is useful for fast bulk ingestion: \copy. Postgres \copy is a mechanism for you to bulk load data in or out of Postgres.

First, lets pause. Do you even need to bulk load data and what’s it have to do with Citus? We see customers leverage Citus for a number of different uses. When looking at Citus for a transactional workload, say as the system of record for some kind of multi-tenant SaaS app, your app is mostly performing standard insert/updates/deletes.

But when you’re leveraging Citus for real-time analytics, you may already have a separate ingest pipeline. In this case you might be looking at event data, which can be higher in volume than a standard web app workload. If you already have an ingest pipeline that reads off Apache Kafka or Kinesis, you could be a great candidate for bulk ingest.

Back to our feature presentation: Postgres \copy. Copy is interesting because you can achieve much higher throughput than with single row inserts.

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