garystafford

<?xml version="1.0" encoding="UTF-8"?>
<lexicon version="1.0"
  xmlns="http://www.w3.org/2005/01/pronunciation-lexicon"
  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.w3.org/2005/01/pronunciation-lexicon
 http://www.w3.org/TR/2007/CR-pronunciation-lexicon-20071212/pls.xsd" alphabet="ipa" xml:lang="en-US">
  <lexeme>
    <grapheme>OSI model</grapheme>
    <alias>o-s-i model</alias>
  </lexeme>
  <lexeme>

garystafford

<?xml version="1.0" encoding="UTF-8"?>
<lexicon version="1.0"
  xmlns="http://www.w3.org/2005/01/pronunciation-lexicon"
  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.w3.org/2005/01/pronunciation-lexicon
 http://www.w3.org/TR/2007/CR-pronunciation-lexicon-20071212/pls.xsd" alphabet="ipa" xml:lang="en-US">
  <lexeme>
    <grapheme>PaaS</grapheme>
    <alias>pass</alias>
  </lexeme>
  <lexeme>

bluet

Database Naming Convention and Data Warehouse Design Principles

• hackmd version: https://hackmd.io/1eeNAS1oQuSvMA0q6y_QuA?view
• gist version: https://gist.github.com/bluet/23e7697b86144561c4a3d804903d059d

[TOC]

ETL: From Data Lake to Data Warehouse

1. Extract 部份：取出要的資料、去雜訊、資料標準化、parsing...
2. Transform：aggregation、mapping 、combined、Change Data Types

Nxtra

import boto3
from pprint import pprint

client = boto3.client('sagemaker')


def main():
    model_names = []

    for key in paginate(client.list_models):

KayLerch

module.exports = Object.freeze({
    translation: {
        welcome: 'Howdy',
        images: [ 
            {
                background: 'https://image/en-US.png' 
            },
            {
                background: 'https://image/en-US2.png' 
            },

nafeu

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

"""Template for python3 terminal scripts.

This gist allows you to quickly create a functioning
python3 terminal script using argparse and subprocess.
"""

import argparse

Ryanb58

>>> docker exec -it CONTAINERID /bin/sh
/app # telnet
/bin/sh: telnet: not found

/app # apk update
fetch http://dl-cdn.alpinelinux.org/alpine/v3.7/main/x86_64/APKINDEX.tar.gz
fetch http://dl-cdn.alpinelinux.org/alpine/v3.7/community/x86_64/APKINDEX.tar.gz
v3.7.0-243-gf26e75a186 [http://dl-cdn.alpinelinux.org/alpine/v3.7/main]
v3.7.0-229-g087f28e29d [http://dl-cdn.alpinelinux.org/alpine/v3.7/community]

garystafford

#!/usr/bin/python

# copy and paste into GIMP Python Console
# scales, sharpens, strokes, and exports all open images as PNGs
# optimized for processing screen grabs
# Filters > Python-Fu > Console
# pip install importlib

import importlib

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",

jgautheron

      Tags:
      - Key: Name
        Value:
          !Join ['_', [ ec2, "Fn::ImportValue" : {"Fn::Sub":'${BaseStackName}-Environment'}, test2]]
          #This will create a name tag with value: ec2_<yourValueFromOtherStack>_test2