xlam's Stars
hyprwm/Hyprland
Hyprland is an independent, highly customizable, dynamic tiling Wayland compositor that doesn't sacrifice on its looks.
XTLS/Xray-install
Easiest way to install & upgrade Xray.
osmandapp/OsmAnd
OsmAnd
xtekky/gpt4free
The official gpt4free repository | various collection of powerful language models
ai-forever/ru-dalle
Generate images from texts. In Russian
ppb/pursuedpybear
A python game engine.
xlam/CyberBiology
Проект "Искусственная жизнь"
XiozZe/XioScript
XioScript
ets-labs/python-dependency-injector
Dependency injection framework for Python
pavel-fokin/py-dependency-inversion-study
Study of Dependency Inversion Principle
public-api-lists/public-api-lists
A collective list of free APIs for use in software and web development 🚀
joke2k/faker
Faker is a Python package that generates fake data for you.
dolfinus/setuptools-git-versioning
Use git repo data (latest tag, current commit hash, etc) for building a version number according PEP-440
micronull/JOSM-Russia-address-helper-plugin
Плагин JOSM для загрузки адресов из ЕГРН
leotrubach/osmwalkthrough
LukeSmithxyz/LARBS
Luke's Auto-Rice Bootstrapping Scripts: Installation Scripts for My Arch Linux Meta-Distribution
cuemacro/finmarketpy
Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians)
ranaroussi/qtpylib
QTPyLib, Pythonic Algorithmic Trading
Emsu/prophet
Financial markets analysis framework for programmers
bukosabino/ta
Technical Analysis Library using Pandas and Numpy
kernc/backtesting.py
:mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.
ematvey/pybacktest
Vectorized backtesting framework in Python / pandas, designed to make your backtesting easier — compact, simple and fast
mementum/backtrader
Python Backtesting library for trading strategies
sonaam1234/DeepLearningInFinance
aniruddhachoudhury/Stock-Market-Analysis
Stock Market Analysis with RNN and Time Series
borisbanushev/stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
ocirne23/Reflection-Entity-Component-System
A high performance, low memory cost entity-component-system with a clean interface
Chakazul/Lenia
Lenia - Mathematical Life Forms
Ku3mi41/OpenVirtaHelper
Opensource calculator for Virtonomica
junkdog/artemis-odb
A continuation of the popular Artemis ECS framework