If you're interested in a Close Segment Destination, please email [email protected]. We're actively working on a Segment integration and are looking for testers in the near future. If you need something immediately you can try writing code in Functions using the code below as a starting point.
If you use Segment's Google Analytics server-side integrations, even if you follow all of their documentation / recommendation, it is impossible to properly track your visitors/sessions in GA from anonymous through identified.
This means that if you use Segment like this, you cannot do very basic things in GA like understanding attribution of your product's sign ups. In GA, a brand new session is created for the identified users, which is not correct.
This problem applies to using Segment on the web with analytics.js when the Google Analytics Destination is set to Cloud Mode, or when using a true server-side Source such as Python/Ruby/Node.
-- breakdown revenue per country | |
-- we store billing address only in the Charge object | |
-- NOTE this is rough and there are 2 different country columns to consider here | |
with | |
-- transactions table is what we want since we can sum it all up and that will subtract out refunds | |
-- however we have to join to each Source separately so we can pull out the charge_id for all types of transactions | |
-- because the charge is what we need for the address, since it doesn't exist on the Customer, nor on the e.g. refund |
In Raspberry Pi, create a docker-compose.yml
file grabbed from here: https://github.com/pi-hole/docker-pi-hole/#quick-start. Tweak timezone.
Then I went to http://rpi.local and saw a Pi-Hole message.
Then I saw that I could login to rpi.local/admin with the password found from sudo docker-compose logs pihole
In Pi-Hole Admin:
- Settings > DNS
Set this up as an "Origin Response" Cloudfront Trigger.
See redirects.json
to define or update redirects.
Example for redirects.json
{
Setup Homebridge to run via Docker on a Raspberry Pi.
Assume source of truth for files is on laptop, and you want to "deploy" them to Pi upon changes.
- In this directory, rename
config.tpl.json
toconfig.json
for Homebridge (bigger sample here) and change theusername
andpin
to something unique). - Add any Homebridge plugins to
package.json
andconfig.json
javascript: | |
document.querySelectorAll('.dashboard-path-global-graph-component,header,.dashboard-path-container-component,.dashboard-loan-card-component,.dashboard-global-sidebar-component,footer,.dashboard-external-account-external-account-card-component-action-links-container,[data-testid=autopilot-learn-more],[aria-label="Link an account"],[data-testid="add-an-account-btn"]').forEach((x) => { | |
x.remove() | |
}); | |
document.querySelectorAll('button[title=goals]')[0]?.parentElement?.parentElement?.remove() | |
document.querySelectorAll('.dashboard-path-global-graph-header-component-retirement-value-label-text')[0]?.parentElement?.parentElement?.remove(); | |
/* | |
accountsData = []; | |
document.querySelectorAll('.dashboard-external-account-external-account-card-component,.dashboard-wealthfront-account-card-component').forEach((acct) => { |
- Download & install VirtualBox for OS X
- Acquire a Windows 10 environment. Easiest way:
- Use a maintained fork of ievms, like this:
curl -s https://raw.githubusercontent.com/amichaelparker/ievms/master/ievms-node.sh | env IEVMS_VERSIONS="EDGE" bash
- Start Windows instance in VirtualBox.
- The password for the default Windows IEUser is
Passw0rd!
(mentioned here)
#!/bin/bash | |
set -e | |
CONTENTS=$(tesseract -c language_model_penalty_non_dict_word=0.8 --tessdata-dir /usr/local/share/ "$1" stdout -l eng | xml esc) | |
hex=$((cat <<EOF | |
<?xml version="1.0" encoding="UTF-8"?> | |
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd"> | |
<plist version="1.0"> |