ajbouh

#!/bin/sh
#
# Compiles a static xvfb for the Heroku platform.
#
# This script is a conglomeration of:
#   * https://github.com/ddollar/heroku-buildpack-apt
#   * http://stackoverflow.com/questions/14845291/compile-static-linked-binary-of-xvfb
#   * gumption

set -e # fail fast

ajbouh

load("@io_bazel_rules_docker//container:providers.bzl", "BundleInfo", "ImageInfo")
load("//deployment/docker:image_name.bzl", "image_name")
load(":providers.bzl", "DigestInfo", "RepoInfo")

def _bundle_impl(target, ctx):
    bundle_info = target[BundleInfo]
    return RepoInfo(image_digests = {
        image_name(bundle_info, x[ImageInfo]): x[DigestInfo]
        for x in ctx.rule.attr.image_targets
    })

ajbouh

<style>

.container :global(.deprecated) {
    font-weight: bold;
    color: crimson;
}

.container :global(.deprecated p) {
    margin-top: 0;
}

ajbouh

Forecasting timeseries with the Metered Prophet API

Forecasting timeseries

Forecasting timeseries is a common problem in data science/machine learning. It asks, given a set of observations of the past, what the future will look like.

Some real world applications of timeseries forecasting include:

• Sales/demand forecasting: Say you're an ice cream chain. You might expect that sales will be much higher in the summer and lower in the winter, but trend higher year-over-year overall because you're investing in advertising. The sales forecasts would be useful for things like setting quota for your salespeople, financial disclosure/valuation, and inventory planning.
• Capacity planning: In a software context, capacity planning refers to ensuring enough compute resources to serve expected traffic. More broadly, capacity planning asks, how many servers, employees, meals, parking spaces, etc

ajbouh

set -ex

REGISTRY_INGRESS_IP=10.73.177.23
REGISTRY_INGRESS_REGISTRY_INGRESS_HOSTNAME=registry.$REGISTRY_INGRESS_IP.xip.io

# if [ ! -e $REGISTRY_INGRESS_HOSTNAME.key ]; then
#   echo '{"CN":"'$REGISTRY_INGRESS_HOSTNAME'","hosts":[""],"key":{"algo":"rsa","size":2048}}' | cfssl gencert -config=ca-config.json -ca=ca.pem -ca-key=ca-key.pem -hostname="$REGISTRY_INGRESS_HOSTNAME" - | cfssljson -bare $REGISTRY_INGRESS_HOSTNAME
# fi

# juju ssh easyrsa/0

ajbouh

// Client-side parser for .npy files
// See the specification: http://docs.scipy.org/doc/numpy-dev/neps/npy-format.html
var NumpyLoader = (function () {
    function asciiDecode(buf) {
        return String.fromCharCode.apply(null, new Uint8Array(buf));
    }

    function readUint16LE(buffer) {
        var view = new DataView(buffer);
        var val = view.getUint8(0);

ajbouh

set -ex

REGISTRY_INGRESS_IP=10.73.177.23
REGISTRY_INGRESS_HOSTNAME=registry.$REGISTRY_INGRESS_IP.xip.io

REQ_CN=10.73.177.126

# if [ ! -e $REGISTRY_INGRESS_HOSTNAME.key ]; then
#   echo '{"CN":"'$REGISTRY_INGRESS_HOSTNAME'","hosts":[""],"key":{"algo":"rsa","size":2048}}' | cfssl gencert -config=ca-config.json -ca=ca.pem -ca-key=ca-key.pem -hostname="$REGISTRY_INGRESS_HOSTNAME" - | cfssljson -bare $REGISTRY_INGRESS_HOSTNAME
# fi

ajbouh

This gist is extracted from the README.rst for https://github.com/ajbouh/tfi

If you encounter problems, please file an issue https://github.com/ajbouh/tfi/issues/new

If you extend the above code to another pre-trained model, please fork this gist and share it!

ajbouh

#!/usr/bin/env ruby

require 'json'
require 'uri'

USAGE = <<-EOF
Usage: #{File.basename($0)} file suffixformat prefix_field bson_date_field [limit]

TODO(adamb) make prefix_field detect a constant (prefix) vs a field (.prefix)
TODO(adamb) make bson_date_field detect a constant (date) vs a field (.date)