Marton Trencseni - Tue 12 August 2025 • Tagged with lamport, byzantine, generals, python, flask, distributed
This follow-up factors Lamport’s Byzantine Generals algorithm into a generalized class that's independent of I/O and payloads. Any node can initiate a round (be "king"), values can be arbitrary strings, and multiple rounds can run concurrently.
Marton Trencseni - Wed 30 July 2025 • Tagged with lamport, byzantine, generals, python, flask, distributed
I discuss Lamport's Byzantine Generals problem and why it requires a total of N≥3M+1 nodes with M malicious nodes, and then implement the solution using Python with HTTP Flask servers.
Marton Trencseni - Sun 13 July 2025 • Tagged with distributed, mutual, exclusion, ricart, agrawala, python, flask
This post shows how to implement the Ricart–Agrawala Distributed Mutual Exclusion algorithm with Lamport's logical clocks using HTTP Flask servers.
Marton Trencseni - Fri 11 July 2025 • Tagged with lamport, bakery, python, flask, distributed
This post shows how to implement Lamport’s Bakery algorithm with Python HTTP Flask servers. The Python code is short and readable, helping newcomers grasp the algorithm’s logic without the syntactic overhead of C++. The asynchronous HTTP flow also generates plenty of overlap between workers, so the need for mutual exclusion is obvious. Exposing the variables through REST endpoints enables observation of ticket picking and critical section entry in real time, potentially making the flow of the algorithm easier to understand.
Marton Trencseni - Sun 06 October 2024 • Tagged with taboo, python, async
I built a simple Python-based Taboo game server using asyncio to provide a customizable multiplayer experience via Telnet. 
Marton Trencseni - Sat 15 June 2024 • Tagged with python, async, message, queue, unit, test
I write a small library of unit tests for the message queue servers.
Marton Trencseni - Wed 22 May 2024 • Tagged with python, async, message, queue
In this final post on the toy Python async message queue server implementation, I make further feature and code improvements.
Marton Trencseni - Sun 23 July 2023 • Tagged with mmm, marketing, mixed, model, lightweight_mmm, google, python
I describe the concept of Marketing Mix Modeling using Google's LightweightMMM library.
Marton Trencseni - Sun 07 May 2023 • Tagged with gpt, python, gnews, ai
I show how I used GNews and the OpenAI API to build GPT News Poet, a fun toy site showing silly AI poems based on today's news.
Marton Trencseni - Sun 05 March 2023 • Tagged with python, async, message, queue, chatgpt
I try to get ChatGPT to write the codes in the previous posts. It's able to write the basic message queue skeleton, but cannot implement more complicated features such as delivery semantics with caching.
Marton Trencseni - Thu 02 March 2023 • Tagged with python, async, message, queue
I write a somewhat more complicated, but still relatively simple async message queue server in Python.
Marton Trencseni - Mon 27 February 2023 • Tagged with python, async, message, queue
I write a simple, bi-directional async message queue server in Python.
Marton Trencseni - Wed 21 December 2022 • Tagged with similarity, python, word2vec, doc2vec, pytorch, tensorflow
I use Doc2Vec to try to find pairs of similar API functions between Pytorch and Tensorflow.
Marton Trencseni - Sat 10 December 2022 • Tagged with similarity, python, gensim, word2vec, doc2vec, pyml
In the previous posts, I used the Doc2Vec neural network architecture to compute the similarities between my blog posts, and explored the quality of the scores. In this final post, I show how I added the final Articles You May Like recommendation sections to the blog — it's live!
Marton Trencseni - Sun 04 December 2022 • Tagged with similarity, python, gensim, word2vec, doc2vec, pyml
In the previous post, I used the Doc2Vec neural network architecture to compute the similarities between my blog posts. In this second post I investigate the results further by examining clusters in graphs.
Marton Trencseni - Sat 03 December 2022 • Tagged with similarity, python, gensim, word2vec, doc2vec, pyml
One of the things I learned at Facebook is the power of recommendations. Examples are People You May Know (PYMK), Groups You May Like (GYML) and Pages You May Like (PYML). Inspired by these, I am planning to add an Articles You May Like widget to Bytepawn, based on the semantic similarity of blog posts. I use the Doc2Vec neural network architecture to compute the similarity between my blog posts, and return the top 3 recommendations for each page.
Marton Trencseni - Wed 30 November 2022 • Tagged with timeseries, prophet, darts, python
One of the most common Data Science tasks in a business setting is timeseries forecasting. I was curious what methods and libraries other Data Scientists use, so I posted an "Ask HN" on Hacker News. The post generated 89 comments, most of them high-quality. This is my summary of the discussion.
Marton Trencseni - Sun 22 May 2022 • Tagged with python, decorators
I show toy implementations of Python decorator patterns that may be useful for Data Scientists.
Marton Trencseni - Thu 12 May 2022 • Tagged with python, dataclass, decorator
I write a toy implementation of Python's @dataclass decorator to improve my Python fu and learn more about decorators and metaprogramming.
Marton Trencseni - Sun 08 May 2022 • Tagged with python, decorators
I show toy implementations of Python decorator patterns such as @measure, @repeat, @trace, @count, @singleton, and @app.route (made famous by Flask).