Category: Technology

On Fred Wilson’s blog post about Raise Cache and HackNY, someone asked a very legitimate question:

Why are we raising money to benefit CS students from top programs around the country? Why are we raising money to help companies like Business Insider and bit.ly hire interns?

The event looks like fun but I’ve been trying to understand hackNY and don’t understand why it’s a charitable cause.

And, I wrote a response — providing some anecdotal information about how Parse.ly benefited from HackNY, and why it matters in a city flush with gold-plated Wall St. internships.

Let me give you a hint why HackNY is somewhat charitable: Wall Street firms pay between $15-$30k/summer for technical interns in NYC. Most startups — especially early-stage ones — simply can’t compete with that.

You may not think startups like bit.ly and Business Insider need any help (and with their $13-15M in capital funding raised, maybe you are right), but in 2010, when Parse.ly sought a summer intern, we had no funding and a < $3K/mo. burn rate. You can read our testimonial about HackNY here: http://hackny.org/a/2011/01/st... That said, it'd probably be good to have more truly early-stage (pre-funding) companies on the roster -- one of the problems with this, though, is that a lot of pre-funding companies are in such a fragile state that the internship might be over a couple weeks into the summer. Also, pre-funding companies aren't typically "buzzworthy". The first two years of HackNY has been partially about creating some buzz about NYC tech among university students, something at which it has succeeded spectacularly. Both of our HackNY interns (2010 + 2011) have commented about how one of the interesting parts of the program is that it simply raises awareness of the different stages of companies. Since the HackNY interns all live together in university housing, they share stories -- and you'll have folks working on >100-person teams at places like Gilt Group and folks working on <10-person teams at places like Parse.ly. Also, the program’s lecture series does a good job of encouraging students to consider entrepreneurship or startup work as a post-graduation option. This is a countervailing force to the professional HR/recruiting teams employed by Wall Street and other Fortune 500s to market their positions to top students.

from Raise Cache at AVC.com.

I came across this wonderful piece of historical retelling by David Beazley, one of my favorite Pythonistas and the author of Python Essential Reference. Here is a man who conquered C++ in just about every way, but ultimately found himself trapped in its byzantine complexity, only to escape by way of Python.

Swig grew a fully compatible C++ preprocessor that fully supported macros. A complete C++ type system was implemented including support for namespaces, templates, and even such things as template partial specialization. Swig evolved into a multi-pass compiler that was doing all sorts of global analysis of the interface. Just to give you an idea, Swig would do things such as automatically detect/wrap C++ smart pointers.It could wrap overloaded C++ methods/function. Also, if you had a C++ class with virtual methods, it would only make one Python wrapper function and then reuse across all wrapped subclasses.

Under the covers of all of this, the implementation basically evolved into a sophisticated macro preprocessor coupled with a pattern matching engine built on top of the C++ type system […] This whole pattern matching approach had a huge power if you knew what you were doing […]

In hindsight however, I think the complexity of Swig has exceeded anyone’s ability to fully understand it (including my own). For example, to even make sense of what’s happening, you have to have a pretty solid grasp of the C/C++ type system (easier said than done). Couple that with all sorts of crazy pattern matching, low-level code fragments, and a ton of macro definitions, your head will literally explode if you try to figure out what’s happening. So far as I know, recent versions of Swig have even combined all of this type-pattern matching with regular expressions. I can’t even fathom it.

Sadly, my involvement was Swig was an unfortunate casualty of my academic career biting the dust. By 2005, I was so burned out of working on it and so sick of what I was doing, I quite literally put all of my computer stuff aside to go play in a band for a few years. After a few years, I came back to programming (obviously), but not to keep working on the same stuff. In particularly, I will die quite happy if I never have to look at another line of C++ code ever again. No, I would much rather fling my toddlers, ride my bike, play piano, or do just about anything than ever do that again.

From this Swig mailing list entry.

It’s hard to find me gushing more unapologetically than when I talk about the virtues of my favorite programming language, Python.

Indeed, my life for the last 3 years has been dominated by the language. In many ways, pursuing a startup and enduring the associated financial hardship was partially because I had become frustrated with using Java in my full-time work and wanted to convert hobby projects I was building outside of work hours into full-fledged projects.

Continue reading import this: learning the Zen of Python with code and slides

And, sadly, our top engineering graduates don’t always become engineers. They move into finance or management consulting — both of which pay far higher salaries than engineering. I have seen the dilemma that my engineering students at at Duke University have faced. Do they take a job in civil engineering that pays $70,000, or join big Wall Street financial firm and make $120,000? With the hefty student loans that hang over their heads, most have made the financially sensible decision. In some years, half of our graduates have ended up taking jobs outside of engineering. Instead of developing new types of medical devices, renewable energy sources and ways to sustain the environment, my most brilliant students are designing new ways to help our investment banks engineer the financial system.

[…] We also need to make the engineering profession “cool” again, with the same sense of excitement and urgency in engineering and science that we saw during the Sputnik days. Back then, engineering was considered essential to the nation’s survival. Engineers and scientists were national heroes. It’s not that we don’t have problems to solve. The economy is in dire straits. Natural resources such as food, water, and crude oil are becoming scarce. Drug-resistant bacteria threaten us with doomsday plagues. But we’re not offering our best minds incentive to solve them.

From Mr. President, there is no engineer shortage.

Luckily this is happening already in high tech in NYC, thanks to awesome programs like HackNY and collabraCode (both of which my startup Parse.ly formally supported). As much as it pains me to say it, I also think The Social Network may be seen as a cultural catalyst for software engineers becoming “cool”.

But high tech is only a small piece of the puzzle — we need the same active marketing for students’ minds in biotech, education, medical research, civil engineering, etc.

I’ve been quite busy with work lately, so haven’t had time to send a few posts toward my blog. However, I have been working on some spare time and work-related projects that I’d love to share with everyone here.

Among them:

• Lifehacking through standing desks. I have created a standing desk setup for my home office, and my investors in Parse.ly have created a healthy startup office in NYC. I have some thoughts about this as it applies engineering and hacking to the thing many of us do most: sit in a desk chair all day.
• 2-day Python Training Course. I have created a 2-day Python training course that helps existing programmers learn Python by comparing it very directly to languages they may already know, like C and Java. I gave this course to a group of government employees a few months ago. It has some interesting characteristics: I designed the whole course using ReStructured Text (ReST) and compiled it into a web-based presentation. This means that the entire course has the potential to be “open source” — exercises, slides, and all. I plan to release this to the public. For now, I am just clearing a few of the images I used in the course to make sure I don’t inadvertently infringe copyright. After that, I will open to the public.
• Groovy/JavaScript articles go public domain. Some articles I wrote for GroovyMag and JSMag last year are now able to be published in the public domain. These include one about RESTful services with Groovy, one that talks about functional programming with JavaScript, and finally one that discusses a design for “metagrids” in ExtJS 3.x. I will put all three articles up on this blog once they are reformatted.

Stay tuned!

I was a bona fide Java programmer for 5 years before I started working on Aleph Point and Parse.ly. I truly believe that Python and JavaScript are fundamentally better languages than Java for a variety of reasons born out of experience with each of them. (Note: Before this gets marked as flamebait, please notice that not only was I Java programmer for more than 5 years, but I was also a Java open source contributor!) I have enormous respect for the Java open source community, which has produced some of the highest quality modules available anywhere.

Now, don’t get me wrong — Python also has batteries included, and usually, when I think that I’m missing a great module I used to use in Java, it already exists in a much more powerful form in Python’s Standard Library or the wealth of modules on PyPI, GitHub, and Bitbucket. However, I believe in not reinventing the wheel, and so if a great open source tool exists in Java, I will want to interact with it.

One of these modules which we use extensively at Parse.ly is Apache Solr, and its surrounding Lucene project modules. Lucene is an extremely mature framework for document indexing, and Solr is a powerful server-ization of that technology that fits well into complex, mixed language distributed systems. I know there are efforts — like Whoosh — to build fast search engines atop the Python language. And I applaud these efforts — more projects means more competition, and more competition means better products. However, I still believe that you go with the best of breed tools available for production software, and you try not to let religious arguments about programming language get in the way.

Lately, I have come across more and more Java open source projects that have no equivalent in Python, and which I would like to access. Knowing that I wanted to feel comfortable incorporating Java open source projects — beyond Solr, which was already nicely wrapped as a web service — I, at first, thought that I’d be forced to still live among the weeds of complex class and interface definitions, cumbersome Java IDEs, XML configuration files, and (IMO) time-wasting rabbit holes like dependency injection, configuration management, and classpath hell. And then I found Groovy.

Continue reading Groovy, the Python of Java

Early on during this startup adventure, a person I trust told me, “Watch out — startups aren’t for the faint of heart.” Looking back on my personal net income graph from 2009 to present, I can see what he meant.

May 2009 is when I entered Dreamit Ventures to begin working on what would become Parse.ly. That’s when I plunged my “savings buffer” into the company. The few months after that had me frantically trying to recover from the realization that startup progress is measured in months and years, not days and weeks.

Sachin and I switched gears from targeting consumers with a free product to targeting large online content properties with a paid product, and bootstrapped the company with side consulting gigs. We didn’t tell anyone we did the side consulting work (unless they specifically asked). We watched other entrepreneurs go into credit card debt and borrow money from trusting friends and relatives. We didn’t believe in that, so we took the hard road of “earning our survival”.

However, our costs were going up, not down, as we pursued a more ambitious product with more demanding clients. Also, my expenses skyrocketed as COBRA disappeared for my health insurance and I had to pay for horribly overpriced sole proprietorship plans. (Fact: America’s broken healthcare system is harmful to entrepreneurs.) I knew I needed to do something to “stop the bleeding” on my financial situation — so, I took on more consulting gigs…

Continue reading Startups: Not for the faint of heart

Let’s say that you want to make some money at the horse tracks. The guy behind the booth gives you the following choice:

1. The Bet. You can place a bet now, before the race starts, on the horse with, in your view, the best odds of winning.
2. The Option. Instead of betting now, he will sell you an option. The option gives you the right to bet on any horse during the race, up until 5 seconds before the first horse crosses the finish line. However, there’s a small catch: everyone else who owns this option has the same right, and only 3 gamblers are allowed per horse during the race. If all the spots fill up, you simply get your money back. Further, each other gambler’s choice will be made publicly available to others during the race.

Most people, even if they don’t know much about horse betting, will rightfully think The Option is the way to go. No matter how much information you might have about each of the horses and riders before the race, the information you gather during the race is much more valuable. A top-ranked horse might break a leg, or its rider might trip up on the start. Even if you pick a favorite before the race begins, once it gets going and you see him lagging behind, the economic reality put in front of you will override your speculative capacities.

Continue reading It’s easier to play the option than the bet

Pythonic isn’t just idiomatic Python — it’s tasteful Python. It’s less an objective property of code, more a compliment bestowed onto especially nice Python code. The reason Pythonistas have their own word for this is because Python is a language that encourages good taste; Python programmers with poor taste tend to write un-Pythonic code.

This is highly subjective, but can be easily understood by Pythonistas who have been with the language for awhile.

Here’s some un-Pythonic code:

def xform(item):
    data = {}
    data["title"] = item["title"].encode("utf-8", "ignore")
    data["summary"] = item["summary"].encode("utf-8", "ignore")
    return data

This code is both un-Pythonic and unidiomatic. There’s some code duplication which can very easily be factored out. The programmer hasn’t used concise, readability-enhancing facilities that are available to him by the language. Even lazy programmers will recognize this code’s clear downsides.

Continue reading Pythonic means idiomatic and tasteful

Last summer, we got our company, Parse.ly, off the ground at DreamIt Ventures incubator program in Philadelphia. Since then, we’ve talked to a lot of founders about our experience in the program. Many founders are data-driven people who are looking for concrete advice about how to optimize their experience at these programs. One of the most successful runway-extending pieces of advice we have given has been to keep food costs low. We were able to get our food cost down to $4/person/day through some simple planning during that summer, and each of us also lost 10-15 pounds in the process. We felt great, were productive, and made our DreamIt investment last. I think this might be one of the core reasons for our company’s survival and success. This is the story behind “The Startup Diet”.

DreamIt Ventures had just cut us a check for $20K to get our startup off the ground. But my cofounder Sachin and I were worried. $20K seems like a lot of money, but it’s actually not that much. Not when you’re using it for both living expenses and to hire other people to get your company off the ground. So we started planning our spend and rationing the money immediately.

We knew we’d use some of the money for our living expenses. We had just arrived in Philadelphia, and we were living in a startup house with Matt and Burak, the founders of Tidal Labs, and Jack, one of the founders of SeatGeek. It turns out that rent wasn’t that expensive in Philly, especially in this arrangement. Instead, our number one cost, we determined, was going to be food.

Continue reading The Startup Diet