ktmud

from redis_store import store


PRED_EXPIRE_SEC = 120


@store.cache(expire=PRED_EXPIRE_SEC)
def predict(model, photo_id):
    """Predict labels for one photo"""
    # each thread uses a different learner cache

ktmud

license: mit

ktmud

#!/usr/bin/env python3 -W ignore::DeprecationWarning
# -*- coding: utf-8 -*-
"""
Sync GIS data from a PostgreSQL server to another
"""
import os
import click

from io import StringIO
from sqlalchemy import create_engine

ktmud

library(future)
library(tidyverse)
library(datasets)
library(randomForest)
library(tictoc)

plan(multisession, workers = 10)

calc_imp <- function(idx) {
  Sys.sleep(1)

ktmud

This is for launching and debugging Redash Flask app in VSCode.

We couldn't use the default Flask runner, because Redash implemented its own cli command manager.

We must use "program": "${workspaceFolder}/manage.py" instead of "module": "manage" because the relative path will cause some path issue, and result in template file not found errors.

ktmud

This Gist demonstrates how to enable Okta/OpenID Connect login for Superset (and with slight modifications, other Flask-Appbuilder apps).

All you need to do is to update superset_config.py as following and make sure your Cliend ID (OKTA_KEY) and Secret (OKTA_SECRET) are put into the env.

ktmud

from datetime import datetime, timedelta

ONE_DAY = timedelta(days=1)

def datetime_between(start, end, interval=timedelta(days=1),
                     ret_dtype='datetime'):
    """All datetime between start and end.
       Default interval: 1 day"""
    start = datetime.strptime(start.replace('-', ''), '%Y%m%d')
    end = datetime.strptime(end.replace('-', ''), '%Y%m%d')

ktmud

Tensorflow 1.7 with CUDA on macOS Sierra 10.12.6, Anaconda, and Python 3.6

Largely based on the Tensorflow 1.6 gist, this should hopefully simplify things a bit. Mixing homebrew python2/python3 with pip ends up being a mess, so here's an approach to uses the built-in python27.

Requirements

• NVIDIA Web-Drivers 378.05.05 for 10.12.6
• CUDA 9.0 Toolkit
• cuDNN 7.0.5 (latest release for mac os)
• Python 3.6

ktmud

Step 1: Install Python 3.6

I use anaconda:

wget https://repo.anaconda.com/archive/Anaconda3-5.3.0-MacOSX-x86_64.sh
bash ./Anaconda3-5.3.0-MacOSX-x86_64.sh
conda create -n idp intelpython3_full python=3
source activate idp

ktmud

var dispatch = d3.dispatch("dataLoaded", "stationHovered", "nodesUpdated");

d3.json("stations.json", function(error, stations)
{
    var data = {};
    data.nodes = stations.nodes;
    data.links = stations.links;

    for(var i = 0; i < data.nodes.length; i++)
    {