wow... congrats to Guido and everyone else involved.

get it here:

Posting a link to your email address on your website is inviting spiders to grab it and spam you.  I get around this by using a JavaScript snippet so my email address link renders on the client but not in the actual HTML source.

While I'm sure there are much better ways to do this, this has been successful for me so far.

This script creates a "mailto" link for my email address:

<script type="text/javascript">
    <!--
    var name = "corey"
    var emailHost = "goldb.org"
    document.write("<a href=" + "mail" + "to:" + name + "@" + emailHost + ">"
        + name + "@" + emailHost + "</a>")
    //-->
</script>

(this post is completely off-topic. stay tuned for regularly scheduled software and technology stuff)

With the rough weeks in US markets (subprime fiasco, credit crunch.. ouch), I thought it would be a good time to talk about the only investment strategy that really works.  Yes, it is easy. Yes, it is boring.  Yes, it works.

Ever since I finished my Bachelor's in Economics (10 years ago), I have been consumed with following financial markets and investing any shred of money I come upon.  I've had ups and downs, but I like to consider myself a pretty savvy investor.  My career as a software engineer has also kept me close to finance.  I worked in institutional financial services for 8 years as a developer/tester.  I helped develop trading platforms, market research databases, quantitative analysis tools, buy-side/sell-side communication platforms, pre-trade negotiation messaging, etc.  I like to think that I have a pretty good idea of how markets work.

So in this huge multi-billion dollar game, how is the personal investor supposed to navigate his way to profit?

Well.. actually it's quite easy.

There are 2 simple questions you must first answer:
1. What is the time-frame in which you need access to your money? (next week? next year? 10 years? retirement?)
2. How much risk and volatility are you comfortable with?

The Answer:
Asset Allocation

... not fundamental analysis, not technical analysis, not market trending, not tips from brokers and analysts ... but straight up asset allocation.

There are numerous ways to allocation your assets:  Equities (Large Cap, Small Cap, Value/Growth, Domestic/International), Fixed Income, REITs, Money Instruments, etc.  How you choose to allocate depends on your answers to the questions above.

All The Reading You Need:

I've read dozens of investment books.  The majority of them are garbage.  If you want a good recommendation, pick one of the following books to read and study it thoroughly... it's as simple as that.

• A Random Walk Down Wall Street (Burton G. Malkiel)
• The Four Pillars of Investing (William J. Bernstein)

They are essentially the same book. They cover nearly identical material, history, commentary, and strategy.  They both highly favor the random walk theory and passive index investing.  Both authors are excellent, so just pick one or both.  Study these closely and you have all the information you will ever need.

and one parting tip:
If you are constantly worrying about the stock market, you are over-invested. Sell until you can sleep at night.

(Pylot is the open source web performance/load test tool that I am developing)

When a test run is finished, a report is automatically generated to summarize the test results. It includes various statistics and graphs on response times and throughput from the run. A sample of the results report can be seen here:

http://www.pylot.org/samples/results/results.html

Pylot also writes results to CSV files so you can import them into your favorite spreadsheet to crunch numbers, generate statistics, and create graphs. I have been working

I have also been working on the GUI. Here is the latest:

http://www.pylot.org/samples/ui/pylot_ui_screenshot_2007_08_20.png

Related:

• PyLT - Scratching My Itch - New Web Performance/Load Test Tool (Open Source)
• PyLT - Dev Update #1 - Web Performance/Load Test Tool
• PyLT - Dev Update #2 - Web Performance/Load Test Tool
• PyLT - Dev Update #3 - Web Performance/Load Test Tool
• Pylot - Dev Update #4 - Web Performance/Load Test Tool (New Name and Defining Test Cases)
• Pylot - Dev Update #5 - Web Performance/Load Test Tool (Graphs With MatPlotlib)

highscalability.com pointed out an article from Pingdom titled "What the Web’s most popular sites are running on", which shows the results from an infrastructure survey of 7 popular web "super sites" (TechCrunch, FeedBurner, iStockPhoto, YouSendIt, Meebo, Vimeo, Alexaholic).

There is some intriguing information in the survey, but one thing stood out.  Apparently, TechCrunch runs on 1 web server and 1 database server, with no server clustering:

I almost find this hard to believe.  They serve > 1 million unique visitors per month off of this?

In a recent post: "What does your favorite text editor say about you", the author lists popular text editors and what they say about their users.  Here is the Editor or IDE I use with various programming languages:

Python:  SciTE
Perl:  SciTE
C#:  Visual Studio
Java:  Eclipse

I do all of my writing and a large portion of my programming in a plain old text editor.  Most of the code I write is in Python.  I love using a lightweight text editor instead of a big bloated IDE.  So... I pretty much live inside a text editor.

... and I love SciTE.  It rocks equally on Windows and GNU/Linux.  So what does this say about me?

SciTE:
"Your text editor is lightweight, full featured, extensible and cross platform. In addition, it can work as a stand-alone executable which requires no installation. Fits perfectly with all your other portable tools on your USB thumb drive. You also love how SciTE let’s you write Lua scripts to extend it’s functionality. You take your text editor choice very seriously. You like tinkering, and minimalistic, portable applications."

(via Matt Asay)

I found this pretty interesting.

Lines Of Code (LOC) in some popular Open Source code bases:

• Linux Kernel: 6 million
• Sun Java Development Kit: 6.5 million
• Sun StarOffice: 9 million
• Eclipse: 17 million

Keeping up to date with what's going on in Linux kernel development and what to expect in the future isn't always easy.  The Linux Kernel Mailing List has very high traffic and is very technical.

Luckily, the Linux Foundation has provided the Linux Weather Forecast, which provides a high level roadmap of what's going on in kernel development and where it's all going.

Pretty handy for people depending on future features as well as casual observers that want to keep up to date with major kernel development activities.

Earlier this week, SCO finally lost the infamous Linux copyright infringement case against IBM.  The judge ruled Unix copyrights belong to Novell, not SCO.  A lot of people have forgotten about this case; but when it was originally filed, it really spooked a lot of Free software developers and Linux advocates.

After the ruling, Wall Street punished SCO's stock price accordingly.

5-Day stock price chart for SCOX:

Ouch.  Decimated.  I'm actually surprised it didn't get hammered more... Time to short this rag?

We performance practioners love our graphs!  Visualizing data is helpful in analyzing performance results.  Sometimes a quick glance at a graph provides better understanding than a mound of raw or summarized data.  Pylot's Results Reporting feature creates graphs of response times (latency) and Throughput.

For the graphing toolkit, Pylot uses Matplotlib to produce fancy graphs like these:

Matplotlib allows you to graph data from Python. Here is a simple script that gives a glimpse of how a line/marker graph is created as a png image:

#!/usr/bin/env python

from pylab import *  # Matplotlib

def main():
    # sequence of data points to graph (x, y coordinates)
    points = [(1, 3), (2, 6), (3, 2), (4, 5)]
    graph(points)
   
   
def graph(points):
    fig = figure(figsize=(6, 2))  # image dimensions  
    ax = fig.add_subplot(111)
    ax.grid(True, color='#666666')
    xticks(size='x-small')
    yticks(size='x-small')
    x_seq = [item[0] for item in points] 
    y_seq = [item[1] for item in points] 
    ax.plot(x_seq, y_seq, 
        color='blue', linestyle='-', linewidth=1.0, marker='o', 
        markeredgecolor='blue', markerfacecolor='yellow', markersize=2.0)
    savefig('graph.png') 
    
    
if __name__ == '__main__':
    main()

The output looks like this:

Related:

• PyLT - Scratching My Itch - New Web Performance/Load Test Tool (Open Source)
• PyLT - Dev Update #1 - Web Performance/Load Test Tool
• PyLT - Dev Update #2 - Web Performance/Load Test Tool
• PyLT - Dev Update #3 - Web Performance/Load Test Tool
• Pylot - Dev Update #4 - Web Performance/Load Test Tool (New Name and Defining Test Cases)