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py-bft-crdt

The first JSON-like Byzantine Fault Tolerant CRDT in Python

pybitmex

Websocket and REST client library for BitMEX implemented in Python.

pygun

GUN (GunDB) transpiled to Python

pyspeedtest

Speedtest.net python script

python-jsonrpc-server

A Python 2 and 3 asynchronous JSON RPC server

python-otr

Off-The-Record Messaging protocol implementation for Python

python-proxy

HTTP/Socks4/Socks5/Shadowsocks/ShadowsocksR/SSH/Redirect/Pf TCP/UDP asynchronous tunnel proxy implemented in Python 3 asyncio.

python-socks

Core proxy client (SOCKS4, SOCKS5, HTTP) functionality for Python

python_app_mac_app_store

pywarpgun

python gundb server and client implementation

quillman

A chat app that transcribes audio in real-time, streams back a response from a language model, and synthesizes this response as natural-sounding speech.

rawr-specification

An alternative to STUN and TURN ICE protocols for Web RTC which works with traversing symmetrical NAT.

realtime-py

A Python Client for Phoenix Channels

redismod

A Docker image with select Redis Labs modules

rest-replay

PHP-CLI script for replaying REST connections.

sample-python

⛵ App Platform sample Python application.

servereless-runpod-ggml

serverless-webrtc

A demo of using WebRTC with no signaling server.

shadowproxy

A proxy server that implements Socks5/Shadowsocks/Redirect/HTTP (tcp) and Shadowsocks/TProxy/Tunnel (udp) protocols.

simple-stock-predictor-xgboost-knn-

Stock prediction using xgboost and knn classification done in R

snapgraph

speed-profiler

Accurate speed profiler for Python code using perf_counter.

sqlsessions.nim

Cookie-based sessions for Jester via SQL backend.

stockast

Predict stock market pricing over 180 minutes using Black-Scholes stocastic modelling and parallel Monte-Carlo simulations.

stockprediction

Data and code of my Medium story on stock prediction with TensorFlow

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.

streamingspeakerdiarization

Official open source implementation of the paper "Overlap-aware low-latency online speaker diarization based on end-to-end local segmentation"

subscriptionspice

UserSpice4 + Stripe Subscriptions

supabase-realtime-client

Listen to your supabase database events.

superagi

<⚡️> SuperAGI - A dev-first open source autonomous AI agent framework. Enabling developers to build, manage & run useful autonomous agents quickly and reliably.