A quick adaptation of Nebri’s straightforward blog post is to first shortlist rain related codes into 15 of them and changing from forecast to latest measurement instead. Bridging Nebri and my smartwatch are Twitter and IFTTT recipe–the watch merely mirrored my phone, you don’t need it actually. Why (again) Twitter? Well, rather than the “then that” side–the watch enabler, the “if this” side of IFTTT for Twitter recipes is quite powerful given so many tweet filtering options.

Key-value pairs as trigger for event driven Nebri OS workflow

Many things already taken care by Nebri, hence unseasoned programmer should easily cope with writing simple Python rule and focus on the automation, nevertheless complex rule should also be accommodated. I was having trouble on using previous KVP from different PID though–moved them to comment in the script, but they seem to be working on it. Check their YWeather blog post on how the basics work and compare what I did in Github. I embed an example tweet from @twithujan below. Yahoo! Weather frequency of measurement and accuracy are of different topic by the way.

Bogor is Light Rain with temperature at 23 °C. Taken at Thu, 28 May 2015 7:00 pm WIT

— Twit Hujan (@twithujan) May 28, 2015

PS: “hujan” means “rain” in Indonesian

If this than that recipes alert for Commuter Train trouble

The ingredient is tweet, Twitter Search use case is no longer just sentiment analysis, its function extends to alert, even close to real time–I’m pretty optimistic given the number of Commuter Line users joining the conversation. Now, the no-code part of our recipe, a Twitter search query, that is

(to:krlmania OR @krlmania OR from:CommuterLine)
AND (gangguan OR pantograf OR wesel OR patah)
-semoga -smoga -moga

and a brief explanation is that it queries for some keywords for potential trouble within mentions/replies to @krlmania and official announcements of @CommuterLine. Exclusion added to the search, the sentiment part of tweets, expressing wishes to shoo trouble away–I’m sorry, but keep praying online anyway.

When Twitter launched Twitter Stories in 2011, I read about Ravi Pina running the crowd sourced @Caltrain. Later now I see that official accounts like @SMRT_Singapore is also a model of service disruption info center. We can go deeper to better stats from the API web service that shows real time position (an app is out there showing that the location data API is working), but until its open data status is known, crowd sourcing stays as the most reliable solution, independent to regulation, and easiest to implement. Does the recipe work? During the first week of testing, alerts were flooding–within limit of course–as trouble really happened. So, cook your own ingredients or get my recipes served here.

Snapshot of uploaded contact data from calendar (skycure.com)

There is not other way but to check my password against the combo_not.txt found via Filestube. People already posted howto check this, the easiest way is doing a single line in the shell:

$ printf bandito | openssl sha1 | cut -c10- | grep -f - combo_not.txt
00000d40df69b72328229d2425714f40d7d9a7a3

Bingo! a match there for the password “bandito” (I choose this randomly expecting some person out there is using it). Another way (for comparison as I’m no security expert) is by this short python script (slightly altered from Phobos Technology blog post):

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"""
Save this file as linkedin_hash.py and ensure it's
in the same folder as combo_not.txt
Usage: python linkedin_hash.py hunter2
"""
from hashlib import sha1
import sys
password = sys.argv[1]
hsh = sha1(password).hexdigest()
print "SHA-1: %s" % hsh
x = 0
for line in open('combo_not.txt','r'):
    if hsh == line.strip():
        x += 1
    elif "00000" + hsh[5:] == line.strip():
        x += 1
        print "Matching line: %s" % line
print "Number of matches: %d" % x

My verdict is: my password is on the list and I’m considering a leap of faith from devoted conspiracy believer.

PS: I don’t find that “password” or “123456″ as common passwords used by many people.
PPS: A side story: Indonesians are found to be using weakest passwords (as research over Yahoo ID revealed)