A flexible CTF contest platform for coming PKU GeekGame events

Overview

Project Guiding Star: the Backend

A flexible CTF contest platform for coming PKU GeekGame events

Still in early development

Highlights

  • Not configurable is most customizable. Every contest has its unique rule, which is unlikely to be fully covered by a text file or SQL table. Our experience shows that these static configurations often disturb contest organizers when they want more customization. Instead, we trust them as decent programmers, leaving the customization to the logic in the source code that is easy to maintain and extend.
  • Pure Python Logic. The core logic that handles submissions, scoreboards, and users are written in plain old Python. Only basic Object-Oriented Programming skill is required before you can start customization. No preknowledge of heavy third-party frameworks is needed.
  • Type-checked. Every function in the codebase is type-annotated and checked by Mypy in strict mode. With type information, you can reliably auto-complete the code and check what breaks after a refactor in a capable IDE.
  • A flexible state machine. The logic splits into one reducer that updates the game state and multiple workers that power read-only APIs and pass actions to the reducer. The state synchronizes in real-time with ZeroMQ sockets. It is easy to attach different kinds of workers that handle push notifications or background jobs to the reducer.
  • Scalable performance. A bonus of the state machine architecture is that only raw submissions are in the database (so that the state can be restored after a service restart). The game state is kept in RAM, making it more performant when updating the scoreboard. The backend is also asynchronous, therefore a laggy OAuth provider will not block other requests.

Architecture

TODO

License

To be considered after the codebase is nearly complete. It may be GPL or something like that.

Currently, you should consider this project as all rights reserved.

Owner
PKU GeekGame
PKU GeekGame
Painless Machine Learning for python based on scikit-learn

PlainML Painless Machine Learning Library for python based on scikit-learn. Install pip install plainml Example from plainml import KnnModel, load_ir

1 Aug 06, 2022
This project used bitcoin, S&P500, and gold to construct an investment portfolio that aimed to minimize risk by minimizing variance.

minvar_invest_portfolio This project used bitcoin, S&P500, and gold to construct an investment portfolio that aimed to minimize risk by minimizing var

1 Jan 06, 2022
vortex particles for simulating smoke in 2d

vortex-particles-method-2d vortex particles for simulating smoke in 2d -vortexparticles_s

12 Aug 23, 2022
Uber Open Source 1.6k Dec 31, 2022
Open source time series library for Python

PyFlux PyFlux is an open source time series library for Python. The library has a good array of modern time series models, as well as a flexible array

Ross Taylor 2k Jan 02, 2023
Polyglot Machine Learning example for scraping similar news articles.

Polyglot Machine Learning example for scraping similar news articles In this example, we will see how we can work with Machine Learning applications w

MetaCall 15 Mar 28, 2022
A Python package to preprocess time series

Disclaimer: This package is WIP. Do not take any APIs for granted. tspreprocess Time series can contain noise, may be sampled under a non fitting rate

Maximilian Christ 57 Dec 17, 2022
Predicting Keystrokes using an Audio Side-Channel Attack and Machine Learning

Predicting Keystrokes using an Audio Side-Channel Attack and Machine Learning My

3 Apr 10, 2022
A collection of Scikit-Learn compatible time series transformers and tools.

tsfeast A collection of Scikit-Learn compatible time series transformers and tools. Installation Create a virtual environment and install: From PyPi p

Chris Santiago 0 Mar 30, 2022
Laporan Proyek Machine Learning - Azhar Rizki Zulma

Laporan Proyek Machine Learning - Azhar Rizki Zulma Project Overview Domain proyek yang dipilih dalam proyek machine learning ini adalah mengenai hibu

Azhar Rizki Zulma 6 Mar 12, 2022
Data from "Datamodels: Predicting Predictions with Training Data"

Data from "Datamodels: Predicting Predictions with Training Data" Here we provid

Madry Lab 51 Dec 09, 2022
Skoot is a lightweight python library of machine learning transformer classes that interact with scikit-learn and pandas.

Skoot is a lightweight python library of machine learning transformer classes that interact with scikit-learn and pandas. Its objective is to ex

Taylor G Smith 54 Aug 20, 2022
A toolkit for geo ML data processing and model evaluation (fork of solaris)

An open source ML toolkit for overhead imagery. This is a beta version of lunular which may continue to develop. Please report any bugs through issues

Ryan Avery 4 Nov 04, 2021
Self Organising Map (SOM) for clustering of atomistic samples through unsupervised learning.

Self Organising Map for Clustering of Atomistic Samples - V2 Description Self Organising Map (also known as Kohonen Network) implemented in Python for

Franco Aquistapace 0 Nov 16, 2021
Python Research Framework

Python Research Framework

EleutherAI 106 Dec 13, 2022
Python bindings for MPI

MPI for Python Overview Welcome to MPI for Python. This package provides Python bindings for the Message Passing Interface (MPI) standard. It is imple

MPI for Python 604 Dec 29, 2022
It is a forest of random projection trees

rpforest rpforest is a Python library for approximate nearest neighbours search: finding points in a high-dimensional space that are close to a given

Lyst 211 Dec 29, 2022
High performance implementation of Extreme Learning Machines (fast randomized neural networks).

High Performance toolbox for Extreme Learning Machines. Extreme learning machines (ELM) are a particular kind of Artificial Neural Networks, which sol

Anton Akusok 174 Dec 07, 2022
Stacked Generalization (Ensemble Learning)

Stacking (stacked generalization) Overview ikki407/stacking - Simple and useful stacking library, written in Python. User can use models of scikit-lea

Ikki Tanaka 192 Dec 23, 2022
Automated Machine Learning with scikit-learn

auto-sklearn auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. Find the documentation here

AutoML-Freiburg-Hannover 6.7k Jan 07, 2023