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
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
Metric learning algorithms in Python

metric-learn: Metric Learning in Python metric-learn contains efficient Python implementations of several popular supervised and weakly-supervised met

1.3k Dec 28, 2022
Simulation of early COVID-19 using SIR model and variants (SEIR ...).

COVID-19-simulation Simulation of early COVID-19 using SIR model and variants (SEIR ...). Made by the Laboratory of Sustainable Life Assessment (GYRO)

José Paulo Pereira das Dores Savioli 1 Nov 17, 2021
Retrieve annotated intron sequences and classify them as minor (U12-type) or major (U2-type)

(intron I nterrogator and C lassifier) intronIC is a program that can be used to classify intron sequences as minor (U12-type) or major (U2-type), usi

Graham Larue 4 Jul 26, 2022
Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.

Python Extreme Learning Machine (ELM) Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.

Augusto Almeida 84 Nov 25, 2022
The easy way to combine mlflow, hydra and optuna into one machine learning pipeline.

mlflow_hydra_optuna_the_easy_way The easy way to combine mlflow, hydra and optuna into one machine learning pipeline. Objective TODO Usage 1. build do

shibuiwilliam 9 Sep 09, 2022
Classification based on Fuzzy Logic(C-Means).

CMeans_fuzzy Classification based on Fuzzy Logic(C-Means). Table of Contents About The Project Fuzzy CMeans Algorithm Built With Getting Started Insta

Armin Zolfaghari Daryani 3 Feb 08, 2022
Distributed Computing for AI Made Simple

Project Home Blog Documents Paper Media Coverage Join Fiber users email list Uber Open Source 997 Dec 30, 2022

Project to deploy a machine learning model based on Titanic dataset from Kaggle

kaggle_titanic_deploy Project to deploy a machine learning model based on Titanic dataset from Kaggle In this project we used the Titanic dataset from

Vivian Yamassaki 8 May 23, 2022
This machine-learning algorithm takes in data from the last 60 days and tries to predict tomorrow's price of any crypto you ask it.

Crypto-Currency-Predictor This machine-learning algorithm takes in data from the last 60 days and tries to predict tomorrow's price of any crypto you

Hazim Arafa 6 Dec 04, 2022
Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber

Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber

EconML/CausalML KDD 2021 Tutorial 124 Dec 28, 2022
Sleep stages are classified with the help of ML. We have used 4 different ML algorithms (SVM, KNN, RF, NN) to demonstrate them

Sleep stages are classified with the help of ML. We have used 4 different ML algorithms (SVM, KNN, RF, NN) to demonstrate them.

Anirudh Edpuganti 3 Apr 03, 2022
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
Simple structured learning framework for python

PyStruct PyStruct aims at being an easy-to-use structured learning and prediction library. Currently it implements only max-margin methods and a perce

pystruct 666 Jan 03, 2023
CVXPY is a Python-embedded modeling language for convex optimization problems.

CVXPY The CVXPY documentation is at cvxpy.org. We are building a CVXPY community on Discord. Join the conversation! For issues and long-form discussio

4.3k Jan 08, 2023
Decision Weights in Prospect Theory

Decision Weights in Prospect Theory It's clear that humans are irrational, but how irrational are they? After some research into behavourial economics

Cameron Davidson-Pilon 32 Nov 08, 2021
Combines MLflow with a database (PostgreSQL) and a reverse proxy (NGINX) into a multi-container Docker application

Combines MLflow with a database (PostgreSQL) and a reverse proxy (NGINX) into a multi-container Docker application (with docker-compose).

Philip May 2 Dec 03, 2021
Educational python for Neural Networks, written in pure Python/NumPy.

Educational python for Neural Networks, written in pure Python/NumPy.

127 Oct 27, 2022
A machine learning web application for binary classification using streamlit

Machine Learning web App This is a machine learning web application for binary classification using streamlit options this application contains 3 clas

abdelhak mokri 1 Dec 20, 2021