Terminal

A Terminal User Interface (TUI) for automated trading with Komodo Platform’s AtomicDEX-API

A Terminal User Interface (TUI) for automated trading with Komodo Platform’s AtomicDEX-API sudo apt install wget curl jq git python3-pip git clone https://github.com/smk762/pytomicDEX_makerbot/ cd pytomicDEX_makerbot pip3 install -r requirements.txt ./makerbot.py Use this with small amounts you are comfortable with and be conscious of your risk tolerance. Always make a secure offline backup of your seed phrase. GitHub View Github    

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Scheduling

Liquid scheduler for python

Intro Clepsydra is a mini framework for task scheduling All parts are designed to be replaceable. Main ideas are: No pickle! Tasks are stored in readable format, so can be used outside of framework Task creator doesn’t need to know how tasks are implemented or executed Persistence may be implemented All workers must follow same async style: be either sync or async functions Currently project is in the design stage and any APIs are to be changed How to use: […]

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Tracking

Keyhole Imaging: Non-Line-of-Sight Imaging and Tracking of Moving Objects Along a Single Optical Path

Code associated with the paper “Keyhole Imaging: Non-Line-of-Sight Imaging and Tracking of Moving Objects Along a Single Optical Path” by Chris Metzler, David Lindell, and Gordon Wetzstein. Abstract Non-line-of-sight (NLOS) imaging and tracking is an emerging technology that allows the shape or position of objects around corners or behind diffusers to be recovered from transient, time-of-flight, measurements. However, existing NLOS approaches require the imaging system to scan a large area on a visible surface, where the indirect light paths of […]

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Telegram

A telegram bot does not allow channels to send messages to the telegram supergroup

Getting started $ git clone https://github.com/AbhijithNT/GroupChannelHandler.git $ cd ChannelMessageHandler Virtual Environment Optional $ pip install virtualenv $ virtualenv venv $ source venv/bin/activate $ pip install -r requirements.txt $ python bot.py Require environment variables Follow the links BOT_TOKEN BotFather Heroku Deploy Built With Contributing Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us. Authors See also the list of contributors who participated in this project. Telegram Channel Join the News channel. […]

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Chess

j-chess implementation in python

This repository aims to be a starting point for implementing a chess ai for the j-chess-server in python. To start, you can copy this repository and add an Ai that extends from BaseAi and call the client with it and you should be ready to go. To regenerate the classes from the xsd, call xsdata .xsdjChessMessage.xsd –package j-chess-generated GitHub View Github    

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Assistant

Used python functional programming to make this Ai assistant

I have used python functional programming to make this Ai assistant. we have seen in our daily life goggle assistant siri Alexa , I was pretty much interested to know how this things are working . So I had worked on this project to learn how they are working . I want to make more personalized ai assistant, so I had created this one. pyttsx3 (python text to speach): to convert text in voice ; datetime: for get the info […]

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Ansible

This collection is to provide an easier way to interact with Juniper

Overview The goal of this collection is to provide an easier way to interact with Juniper’s Apstra solution. While nothing will stop you from using the built-in module, you may find that working with pre-packaged modules can help simplify the development of your playbook, or it may just be easier to support as a team. 📋 Ansible version compatibility There are significant changes to Ansible within version 3.x, and while those changes get worked out we will continue to test […]

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Machine Learning

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

ONNX Runtime is a cross-platform inference and training machine-learning accelerator. ONNX Runtime inference can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms. Learn more → ONNX Runtime training can accelerate the […]

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