nqbao

# Copyright (c) 2018 Bao Nguyen <[email protected]>
# 
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
# 
# The above copyright notice and this permission notice shall be included in all

tilakpatidar

# Run postgres instance
docker run --name postgres -p 5000:5432 debezium/postgres

# Run zookeeper instance
docker run -it --name zookeeper -p 2181:2181 -p 2888:2888 -p 3888:3888 debezium/zookeeper

# Run kafka instance
docker run -it --name kafka -p 9092:9092 --link zookeeper:zookeeper debezium/kafka

# Run kafka connect

ahopkins

from sanic import Sanic
import json
import asyncio


app = Sanic(__name__)
feeds = {}


class Feed(object):

rmoff

{
        "name": "jdbc_source_mysql_foobar_01",
        "config": {
                "_comment": "The JDBC connector class. Don't change this if you want to use the JDBC Source.",
                "connector.class": "io.confluent.connect.jdbc.JdbcSourceConnector",


                "_comment": "How to serialise the value of keys - here use the Json converter. We want to retain the schema in the message (which will generate a schema/payload JSON document) and so set schemas.enable=true",
                "key.converter": "org.apache.kafka.connect.json.JsonConverter",
                "key.converter.schemas.enable":"true",

blvz

#!/usr/bin/env bash

read -r -d '' usage << EOM
Usage:

  gh-deploy-clone user/repo [ENVIRONMENT]
EOM

[ -z "$1" ] && echo && echo "$usage" && echo && exit 1

innovia

#!/bin/bash
set -e
set -o pipefail

# Add user to k8s using service account, no RBAC (must create RBAC after this script)
if [[ -z "$1" ]] || [[ -z "$2" ]]; then
 echo "usage: $0 <service_account_name> <namespace>"
 exit 1
fi

stdlib.sh

aws_ecr_curl() {
  login_cmd=$(aws ecr get-login)
  username=$(echo "$login_cmd" | cut -d " " -f 4)
  password=$(echo "$login_cmd" | cut -d " " -f 6)
  endpoint=$(echo "$login_cmd" | cut -d " " -f 9)

  args=("$@")
  args_length=${#args[@]}
  args_last=${args[$args_length-1]}
  unset 'args[${args_length}-1]'

thomasdullien

"""
  Simple, hacked-up image similarity search using Tensorflow + the inception
  CNN as feature extractor and ANNoy for nearest neighbor search.

  Requires Tensorflow and ANNoy.

  Based on gist code under
    https://gist.github.com/david90/e98e1c41a0ebc580e5a9ce25ff6a972d
"""
from annoy import AnnoyIndex

kwotsin

import tensorflow as tf
from scipy.misc import imread, imresize
from mobilenet_preprocessing import preprocess_for_eval
import numpy as np
from scipy.misc import imread, imresize
import matplotlib.pyplot as plt
import time
plt.style.use('ggplot')
start_time = time.time()
#======DEFINE SOME ARGUMENTS===========

waichee

mkdir -p /work/

# Clone the source from Github
cd /work/ && git clone — recurse-submodules https://github.com/tensorflow/serving

# Pin the version of Tensorflow Serving and its submodule
TENSOR_SERVING_COMMIT_HASH=85db9d3
TENSORFLOW_COMMIT_HASH=dbe5e17
cd /work/serving && git checkout $TENSOR_SERVING_COMMIT_HASH