Using Postgres schemas to separate data of your SaaS application in Django
EuroPython, July 18, 2025

Every SaaS will come against the same issue at one point - how to make sure to only show a customer's data to only that specific customer? And it's not just a security problem, but a performance problem as well. At scale, even with indexes, selecting just the appropriate data can become slow on massive tables.
The "naive" approach is to have a table of customers, and link every other table using foreign keys, and always filter based on the current customer. This approach works fine, and with the library django-scope is pretty safe, but the filter still always needs to be provided and all the data is still in the same physical database table.
Database segregation to the rescue! PostgreSQL has a feature called schemas, which almost acts like a database within a database - each has its own tables and indexes, and you can have many different schemas within one database. In this talk I will introduce you to the django-tenants library, which utilizes these schemas to implement tenanting.
Django-tenants introduces two types of apps, shared apps containing data accessible for all tenants, and tenanted apps specific to one tenant. The data in the tenanted app is only available while the tenant is active, usually based on a subdomain. The django models then work exactly like before, but only the correct data will be returned without any filtering.
In the talk, after walking through a simplified setup of the problem, we'll look at how much simpler django-tenants can make our life while implementing a SaaS application, but also look at certain new and more exciting problems it can bring.

Good practices for making reproducible open source code
UCL Photonics Society Transferable Skills Workshop Series, November 28, 2024
Cambridge Photonics Society, March 25, 2025

Learn how to make good quality reproducible code using the good practices and tools of open-source software development.

Aggregating data in Django using database views
EuroPython, July 10, 2024

Aggregating information is a common Django task, but using the aggregate method can be a bit cumbersome and in the case of large database tables, pretty slow as well. I will introduce the library django-pgviews-redux, which adds first-class support for database views (with Postgres), making that task much simpler.
With that library, database views are wrapped around models, meaning you get many of the features you rely on with models for free, like querysets and filtering on those, admin, and any other feature which works with models. Defining a view is almost as simple as defining a model, by specifying what fields there are for the model and defining the SQL.
This talk will walk through examples of aggregation in Django, and then show how one could simplify those examples using the library. Finally, we will get to materialized views as well, which stores the aggregation almost like a table in the database, providing big speed improvements on aggregation on large tables.

Pytest: The Case For Using Classes
PyCon CZ, September 16, 2023

There's many reasons why people love pytest – the simple asserts, modular test setup, easy barrier to entry, the plugin ecosystem. But at scale, only using function-based tests becomes hard to maintain, and slow to run. At Xelix, our main Django monolith has about ten thousand tests and about four thousand fixtures, so speed and maintainability is of paramount importance.
In this talk I will present several reasons why we love to use classes to organise our tests, and to share fixtures. Using class based tests allows you to be more explicit, in what fixtures are available to a set of tests, and allows sharing fixtures between tests not in the same folder. Using classes enables using fixture scope to greatly speed up your tests, while keeping the fixture namespace clear. And finally, using test classes allows you to do interesting things with inheritance and parametrisation, which would be a pain to do with functions only.

Xelix
Staff Engineer
August 2023 ‒ Ongoing

Lead Data Engineer
October 2022 ‒ July 2023

In addition to all the responsibilities of my previous role lead a small team with responsibility over the pipeline of data coming to Xelix, importing data from customer systems and running processing and analysis on it. This included writing & orchestrating the pipeline, implementing algorithms and ML models, and performing the technical part of customer setup. Line managed two team members directly, and mentoring other team members. Communicated often with the product, customer success and implementation teams. As a senior member of the tech team I was also involved in hiring and strategic planning. Later in this role started focusing heavily on developer experience, making improvements to the codebase, processes, infrastructure, and testing.

Software developer
October 2019 ‒ September 2022

Developing the backend of the Xelix platform using Django. Wrote features, refactored or rewrote large parts of the codebase, scaling from a few customers to many more with much more data. Introduced linting, and better dependency management early on. Focused on testing, writing custom tools, owning them running fast & reliably. Did with DevOps as well, using Terraform in AWS. Implemented data science team's algorithms and ML models.

Eluvia (formerly SparkTECH)
Full-stack developer
May 2014 ‒ September 2019

Part-time. Developing commissioned and in-house systems in Django and AngularJS. Gained experience with building new systems and maintaining older ones, reviewing code and being the owner of projects. In later years involved with DevOps, pioneering CI, handling automatic deployments and loadbalancing using GitLab CI, AWS and custom-made tools.

Red Hat Czech
Associate software engineer ‒ junior
October 2017 ‒ June 2018

Part-time. Supported by Red Hat to work on my bachelor's thesis to help the Czech Python community. The website naucse.python.cz, enhanced by my thesis focuses on materials for teaching or learning Python.

Eleveo (formally ZOOM International)
Testcase writer
April 2012 ‒ May 2013

Part-time. Writing manuals on how to test complicated call centre applications, and testing them before new releases.

University College London
2018 ‒ 2019, MSc Web Science and Big Data Analytics

A data science degree with a focus on the web and related concepts and technologies. Core modules focused on the structure of the web and retrieving information from it, elective modules focused on data analytics and machine learning, including neural networks. Graduated with distinction.

Faculty of Information Technology,
Czech Technical University in Prague
2015 ‒ 2018, Bc Informatics

A general introduction to computer science, with a later specialisation in Web and Software Engineering, which included technologies used on the web, Big Data databases, searching in web and multimedia, information retrieval and other web techniques. Graduated with distinction and was awarded the Dean's Award for an excellent thesis.

Archbishop Grammar School in Prague
2007 ‒ 2015

General education, but with a great computer science education as well, in elective subjects and after-school activities, mostly in Python, basics of graph and graphics algorithms, intro to logic programming, language design, interpreters, and C++.

django-custom-commands
Source
2024 ‒ 2025

A Django package which allows specifying custom paths to load managenent commands from.

pytest-unused-fixtures
Source
2023 ‒ 2025

Pytest plugin for identifying unused fixtures.

pytest-xdist-worker-stats
Source
2023 ‒ 2025

Pytest plugin for collecting statistics about xdist workers.

P4A Portal
Source
2022 ‒ 2025

Calculating statistics for the Project For Awesome charity livestream.

modbus2tcp-reader
Source
2018 ‒ 2021

A small project for reading and storing data from electricity meters. Originally for my father's school, ended up being deployed to analyse consumption of several buildings.

BetterSubBox
Source
2014 ‒ 2019

A discontinued tool for YouTube power-users, extending the YouTube subscriptions with extra functionality, originally my graduation project in high school. Written in Python and CoffeeScript, backend in Django, frontend in Angular. Involved work with YouTube's API, asynchronous actions with celery, and optimising cache for performance.

Arca
Source
2018 ‒ 2019

Additional development of the tool Arca which was the principal part of my bachelor's thesis.