zoid007's Stars
Kismuz/btgym
Scalable, event-driven, deep-learning-friendly backtesting library
nix1/bye
Backtesting Yield Estimator for Index&Stock Options. A tool for testing long-term option-based trading/investment strategies.
xrash/smetrics
String metrics library written in Go.
netbootxyz/netboot.xyz
Your favorite operating systems in one place. A network-based bootable operating system installer based on iPXE.
wboayue/ibapi
Interactive Brokers API - Go Implementation
gotd/td
Telegram client, in Go. (MTProto API)
Fmstrat/diy-ipmi
A DIY IPMI / IP KVM system utilizing the Raspberry Pi
thagrol/fakewake
Fakewake is a software and hardware project that allows network remote control of a PC's power and reset buttons. Wake-on-LAN allows remote start of a PC but has its limitations and does not provide a mechanism to shutdown or reboot the PC. Fakewake provides a web and WOL interface that allows remote power on, power off, and reset.
pawl/raspberry-pi-1u-server
A low power 1U Raspberry Pi cluster server for inexpensive colocation.
ssincan/kvm-ip-zynq
KVM over IP Gateway targeting Zynq-7000 SoC
Nihiue/open-ip-kvm
Build your own open-source ip-kvm device
Lightstreamer/Lightstreamer-example-StockList-client-python
This project contains a simple Python script that shows a minimal client-side implementation of the Lightstreamer Server Text mode Protocol
rinujk/Stock-Market-Analysis-from-Real-time-Tweets
This assignment consists of four parts: 1. Collecting data: In this assignment you need to collect data related to stock market from Twitter for one week. In Twitter, ticker symbols like #gold are used for stocks and companies. You are requested to collect the tweets with some specific keywords and store them in different files. The following keywords should be used: a. Altcoin b. Bitcoin c. Coindesk d. Cryptocurrency e. Gold f. APPL g. GOOG h. YHOO Each tweet is a json file with the following format: {"created_at":”……….”, "id":”………..”, "text":" Time to buy some ether!\n#ethereum #investing #cryptocurrency” “user_id”:”………..” … } 2. Saving data: You need to save the requested data into csv format of 8 files where data related to each keyword is saved. Each file consist of four columns: tweet id, time of tweet, user id and text. 3. Cleaning data: remove duplication, remove punctuations, remove numbers in tweets, and remove words with length less than 2. 4. Visualizing data: You need to present the daily number of tweets for each keyword as well as the daily number of users.
Daniel-Liu-c0deb0t/uwu
fastest text uwuifier in the west
microsoft/vscode-webview-ui-toolkit
A component library for building webview-based extensions in Visual Studio Code.
Almamu/linux-wallpaperengine
Wallpaper Engine backgrounds for Linux!
catsout/wallpaper-engine-kde-plugin
A kde wallpaper plugin integrating wallpaper engine
MoKee/android_packages_apps_WarpShare
seemoo-lab/opendrop
An open Apple AirDrop implementation written in Python
hadrianl/ibapi
Interactive Brokers API - GoLang Implement
alexpate/awesome-design-systems
💅🏻 ⚒ A collection of awesome design systems
jscarle/HyperV.NET
Simple Hyper-V Virtual Machine Management
jroimartin/gocui
Minimalist Go package aimed at creating Console User Interfaces.
sahilm/fuzzy
Go library that provides fuzzy string matching optimized for filenames and code symbols in the style of Sublime Text, VSCode, IntelliJ IDEA et al.
GorvGoyl/Clone-Wars
100+ open-source clones of popular sites like Airbnb, Amazon, Instagram, Netflix, Tiktok, Spotify, Whatsapp, Youtube etc. See source code, demo links, tech stack, github stars.
CodeEditApp/CodeEdit
CodeEdit App for macOS – Elevate your code editing experience. Open source, free forever.
ZENALC/algobot
Cryptocurrency trading bot with a graphical user interface with support for simulations, backtests, optimizations, and running live bots.