The subject line is a bit of a lie. It's not a well-mannered daemon so much as it is a well-mannered cronjob. But it's more fun to say daemon.
I had to make a new cronjob. As is occasionally the way with things, NetFlix saw fit to remove their AtHomeRSS feeds. I used that feed at my lifestream, so I needed a replacement.
I rebuilt the AtHomeRSS feed, and I made the complete source code available. Disclaimer, it's code that was written between 11:00pm and 2:00am over a couple of nights. You get what you paid for.
The point of the repository over there at GitHub is the new script that makes an RSS feed by scraping email. But still, I thought it was interesting how much code was dedicated to making the cronjob be well-mannered. I expect my daemons and cronjobs to have the following attributes:
Do the job quietly, and write a short status report on how it went. No need to interrupt me if things went fine. But I do want to be able to check-in on it, and know if anything interesting happened. My cronjob writes a line (or more) to a status file every time it checks the email. It also trims away really old entries from the file, keeping it short.
If it does encounter a problem, I want it to let me know right away. That's not something to just put in the status report. It should ask for help and email me with any problems that it doesn't know how to handle itself.
When I need to give the cronjob new instructions, it should be easy. It shouldn't fastidiously insist on writing reports or sending me emails as I'm in the process of giving it new directives. This cronjob allows me to quickly test changes with a --debug flag.
This last trait is mostly just thrown in there. It automatically applies to all software, since you only have to write it once, and all things working correctly, it'll do what you tell it to. Still, that's what's beautiful about software. Any time I find myself repeating a task, I find myself wondering, could I just automate this?
There's an interesting description that accompanies the photo that I used as the header for this image. The photo is of "Machine with Concrete." Ars Electronica writes, "Arthur Ganson (US) reminds those partaking of it that the human being is the only creature on Earth to build machines that (are meant to) outlive their creator." My daemons and cronjobs are meant to outlive me.
I've long been a "true believer" in remote computing. I didn't distinguish between an internet cloud and a single remote server. What mattered to me was that all I needed near me was some sort of device to send and receive data. The smaller and thinner the local device, the better.
Ever since I'd heard that John Gage, the Chief Researcher and Vice President of the Science Office for Sun, say that "the network is the computer", I thought that the future was clear. He and I both knew where we were headed.
As soon as the first Chromebook came out, I was interested. But I didn't buy. When I spend my own discretionary money, I'm merely cutting edge, as opposed to bleeding edge. So I waited...
When ChromeOS vesion 19 and the Samsung Series 5 550 came out, it was time for me to buy. I figured they'd gotten most of the kinks out, and the device would be eminently usable.
The Chromebook arrived and I loved it. The laptop itself didn't disappoint at all. The battery life, the screen, the keyboard and touchpad - all of it was great.
I returned the Chromebook because of small missing features in ChromeOS. I knew that ChromeOS didn't support Java. I should have known that ChromeOS wouldn't support QuickTime. I could have lived with those two missing features. The third missing feature: ChromeOS doesn't support SSL VPN solutions. That means I can't even use my Chromebook for connecting to my work's network.
So, I couldn't run Java applications. I couldn't watch PATV, and I couldn't work from home. It's with a heavy heart that I realize that the state of technology isn't quite there yet, and I returned the Chromebook.
Dear Google: I'm still watching and hoping. Get to the point where I can access the networks I need on your portable network device, and you'll get my money. You're so close.
I made a web page that predicts where I'm going. It was a fun little academic exercise, and I thought some of the challenges were interesting.
Ever since it came out that Apple was tracking and keeping location data on everyone's iPhones, and owners could get to that data my curiosity was piqued. Apple was quick to stop tracking so much data and to limit access to the database, but I saved off my phone's database of locations while I could. Later, I installed a new app, OpenPaths, that intentionally and continuously logs my phone's locations and makes that data available to me.
Now that I was logging my phone's locations in the background, I could ask myself what I wanted to do with the data. I knew what I wanted to do right away! I wanted the computer to answer the following question:
Given where I've been, where am I probably going now?
I'd make a webpage whose only job it was to display its answer to that question. It's a simple web page to look at, but the devil's in the details.
The human brain is wonderfully better at answering that sort of question than the computer. It's a matter of pattern recognition across at least three dimesions: time and two-dimensional space.
I started with the way I'd think about answering that question:
If there aren't any notable exceptions, like travelling for work or vacation, then I follow a bi-weekly schedule more closely than a weekly schedule. So I'd look at where I was at this time of day two weeks ago.
To translate that into an algorithm for the webpage a few things need to happen. I have to codify what a "notable exception" is. Perhaps it's being more than 100 miles away from home for more than a day or two. Or, if I'm currently away on vacation, then the program shouldn't be looking at what I've been doing two weeks ago at home.
Here's the algorithm that the computer uses:
- If I was near here two weeks ago, consider where I was going back then at this time.
- Otherwise, consider where I was at this day of the week last week.
- If I was away on each of those occasions, then how about where I was yesterday at this time?
Simple enough. But the question of "two weeks ago at this time of day" itself is a bit ambiguous. Two things get in the way of that that the human brain just automatically figures out. One, time-of-day is local. If I am in California today, but I was in Hawaii two weeks ago, I can pretty easily calculate "breakfast time" for either. But the computer would have to first translate latitude and longitude coordinates into time-zones on the Earth. Then it'd be able to calculate relative time-of-day for either week at either location. The other issue, daylight savings time throws off the way a program might naïvely calculate "two weeks ago."
Account for daylight savings time
"Two weeks ago at this time of day" is a loaded phrase. The naïve approach for a computer that keeps track of time by incrementing seconds would be to subtract the number of seconds in a day, and do that 14 times. But that doesn't account for daylight savings time, which would throw off the results for 4 weeks out of a year.
My program uses Python, which has a library to translate time from epoch timestamps (which are used by OpenPath's library) to a calendar date and time-of-day format that's more native to the human mind. So the actual code calculates "number-of-seconds to this time-of-date two weeks ago" as follows:
now - time.mktime( (datetime.fromtimestamp( now ) - timedelta( days = 14, hours=0 )).timetuple() )
Huh, that's sort of wordy compared to the naïve alternative, but the important thing is that this approach is always correct. Once we've figured out when "two weeks ago" actually is, then we can calculate what "where" and "how far" actually mean...
If you're near the equator, then calculating short distances using latitude and longitude can be approximated by an equation based on Pythagorean Theorem. What's funny is that if you search the web looking for the algorithm in Python, you'll usually see something like the following function:
def distance(p1, p2): return math.sqrt((p1 - p2)**2 + (p1 - p2)**2)
But as long as you're importing the math module anyway, it'd be even more direct if you just used math's own "hypot" (short for "hypotenuse") function:
def distance(p1, p2): return math.hypot(p1 - p2, p1 - p2)
But that calculates planar distance, and we're not on a plane. We're essentially on a sphere. So it's better to use the Haversine formula if we want to get an accurate distance between two points defined by latitude/longitude coordinates.
Now that timedelta and the Haversine formula handle the "when" and "where" in my fuzzy algorithm, it's time to take a look at the presentation of the data.
The Webpage Itself
So much for the algorithm. What about the quality of the webpage itself?
It's a small webpage. So it's only sensible and intuitive that it'd be a quick and responsive webpage, too. But the webpage wouldn't work without making relatively long queries to two remote services.
- Retrieve new location data from the remote OpenPaths API service.
- Retrieve specific map data from the Google Maps API service.
In between the two big remote queries, the program needs to perform the actual prediction for where I'm going to be based on the OpenPaths data, and send the predicted points to Google Maps. There's no way to avoid the fact that the webpage is going to take a few seconds to do all its work.
The best work-around for that is two things:
- Ajax. The web server can quickly serve a simple HTML web page to the client which'll get displayed for the user right away. Then the browser can make another request to the server for just the data that takes a long time to calculate and retrieve.
- Caching. Once I've retrieved raw datapoints and made the prediction calculations, then that prediction shouldn't change for a few minutes. I can save off my prediction and immediately hand it back the next time the webpage is requested, if it's requested relatively soon.
It's critical to me that the webpage be small and simple. It has to get to the point as quickly as possible. But it's also important to me that I give credit to the tools and services I used to make it possible. That called for some credits to be put in a footer.
I wanted the footer to be relative to the browser's window viewing the page. But if that window was too short, then the footer would end up overwriting or being overwritten by the map or the text above the map. The fix for that was some clever CSS that put the footer at the bottom of the window, but never let it cover up the important part of the page, the map.
So far so good. But then I discovered something unexpected...
Sadly OpenPaths seems to collect bad data from my phone occasionally while it's at rest. All of the recorded and predicted movement in the map below is due to bogus data from OpenPaths.
All of the points along the same angle that extends to the south east are bad data. The phone didn't go anywhere all that time. I have no idea why it sometimes pretends to travel to that part of town, but I don't like it. This called for another interesting algorithm that's better suited for a human brain:
If the datapoints smell fishy, don't use them.
It's really easy for me to detect which datapoints are bad, and not only just because I know where my phone's been. It's because there's a certain pattern, the angle and distance traveled by the bogus points. So I've got a work-in-progress algorithm the elides points that smell fishy.
A Secret Mode
The main point to the site was the prediction. But as long as I had all this historical data, it seemed like a shame if I couldn't easily look it up, too. So there's a secret mode, impossible to find and discover. (Since nowadays people don't read long blogs or actually type in the URL bar of their browsers.)
If you add an HTTP "GET" parameter, t, to the URL, the website will return a corresponding location history instead of a prediction of where it thinks I'm going to be. t can take one of three different forms, a UNIX timestamp, an RFC 2822 date and time, or a negative number of days to look back. Here are some examples:
I flew in to Los Angeles on that day. Timestamps are good if you're already dealing with them or want a relatively short token to represent an absolute time. Otherwise, they're an epoch fail waiting to happen.
Took the kids to Disneyland that day. Fun! That date format is handy if you want to browse my location history and are thinking in terms of calendar dates.
What'd I do last week? This is handy if I don't need an absolute time and date, but just want an offset from the current time and date.
Finally, I've got a micro site that was really fun to build and with which I'm quite pleased.
An infuriating design decision of the Kindle Touch was to put the power button on the slick and slightly angled bottom of the device. This design decision confounds most attempts to stand up the Kindle on a hard surface and lean it against something so that the user can do his reading with his hands free.
Two things usually go wrong when you try to stand up an unmodded Kindle Touch for reading with your hands free.
One: The Kindle is likely to slide down, since the bottom surface of the Kindle is relatively slick.
Two: Once you balance the Kindle just right, you're balancing it on the power button, depressing it continuously, putting the Kindle into a reboot mode.
The fix for this is to cut little sections of vinyl bumper surface guards, and adhere them on the flat bottom of the Kindle Touch. The best part of the vinyl bumper to cut is the molding around the actual bumpers. It's just the right height to protect the power button from being accidentally depressed.
Even better, the vinyl has a high coefficient of friction, so the Kindle Touch won't slide down when you try to stand it up anymore. Both problems are fixed by this one simple mod!
I'm burying my parents' ashes this week. I miss them. I miss them individually, and I miss them as a pair. And my missing of them is an active, conscious thing, not a passive background thing. I remember them vividly, and I could use their advice and love now, if they were here. This is going to be a hard week.
It's been a hard couple of months.
I'm not sure what the difference between grieving and depression is. What I mean is, I don't know where "the line" is, and how not to cross it. I know that what happened is the natural order of things. We are supposed to survive our parents. I also know that I'm working through this.
Rie Fu's song, "Life is like a Boat," came on while I was playing a favorite playlist. It's a love song, but it also touches on the hardships of life, and working your way through them to the other side. In the song, we "are all rowing the boat of fate / the waves keep on comin' and we can't escape."
The next part resonates with me:
You make me wanna strain at the oars
And soon I will see the shore
When will I see the shore?
At the same time she writes about fate and not being able to escape it, she sings about never giving up her effort. She doesn't see the shore, but she'll strain at the oars in the hopes that she soon will.
I'm straining at the oars, too.