I often use both Winamp and my iPhone to listen to music. These two, unfortunately, show the time differently in the songs. Winamp displays the time in minutes (mm) while the iPhone does it hour/minutes (hh:mm). Here’s a quick little script I whipped together because I’m too lazy to do this in my head, especially for audio books where an audio book can be over 500 minutes, and I need to convert to iPhone time because I want to continue listening where I had just left off on Winamp.
use POSIX qw(ceil floor); # used for the floor function
sub GetToken {
# @_ = flatten args list from an array
# @_[0] = first argument
$data = @_[0];
$delimiter = @_[1];
$token = @_[2] - 1;
@tokens_array = split($delimiter, $data);
return @tokens_array[$token];
}
sub chr_conver_min {
if (length(@_[0]) == 1) {
return "0".@_[0];
}
else {
return @_[0];
}
}
sub iphone_time_convert {
# converts winamp time to iphone - winamp stores time only in minutes.
# @_[0] = winamp_time, e.g. 124:34
# $hour = floor($winamp_time/60);
# $minute = $winamp_time % 60;
$winamp_hour_min = GetToken(@_[0], ":", 1);
$winamp_seconds = GetToken(@_[0], ":", 2);
return floor($winamp_hour_min/60).":".chr_conver_min( ($winamp_hour_min % 60) ).":".$winamp_seconds;
}
sub winamp_time_convert {
# converts iphone time to winamp
# @_[0] = iphone_time, e.g. 3:43:34
$iphone_hour = GetToken(@_[0], ":", 1);
$iphone_min = GetToken(@_[0], ":", 2);
$iphone_seconds = GetToken(@_[0], ":", 3);
return (($iphone_hour * 60) + $iphone_min).":".$iphone_seconds;
}
sub show_help {
print "\nDisplays the conversion of time between winamp and iPhone.\n\n";
print " winamptime [-w2i|-i2p] [mm:ss][hh:mm:ss]\n\n";
print "Example to convert winamp time to iPhone: \n\n";
print " winamptime -w2i 212:41\n\n";
print "Example to convert iPhone time to winamp, seconds being optional: \n\n";
print " winamptime -i2w 2:31:41\n";
print " winamptime -i2w 2:31\n\n";
}
# START
# Optimize this:
if( $ARGV[0] eq "-w2i" )
{
# winamp to iphone time
if ( length($ARGV[1]) > 0 ) {
print "iPhone Time: ".iphone_time_convert( $ARGV[1] )."\n";
}
}
elsif( $ARGV[0] eq "-i2w" )
{
# iphone to winamp time
if ( length($ARGV[1]) > 0 ) {
print "Winamp Time: ".winamp_time_convert( $ARGV[1] )."\n";
}
}
else
{
show_help();
}Output:
Posted by Dan | Posted in Development, Languages | Posted on 01-18-2010
0
Ouch, I guess the dream I had for having the world’s smallest program has been crushed. I made a program a long long time ago in Assembly using Windows 95’s DEBUG.EXE that rebooted the computer. The reason why it’s so small is that it reboots the computer, so once the BIOS Interrupt executes, there’s no need to do any other clean-up or maintenance. Unfortunately after Windows 95, Microsoft got smart and disabled DOS from executing these interrupts from DEBUG.EXE. Here was the code:
N REBOOT!.com
A 100
INT 19
R CX
2
W
Q
But what I really want is to see the code for this 0-byte code program written in C.
Posted by Dan | Posted in Development, Python | Posted on 01-18-2010
0
So I’m currently in process of reading the infamous “Code Complete” by Steve McConnell. So far it’s been an amazing book and I definitely guarantee it to any programmer out there. I’ve just read the section on recursion and it mentioned how doing recursion for a factorial (or fibonacci) function is not as efficient as a for-loop iteration. I guess I never thought about it, since in computer science I was always shoved recursion down my throat when doing factorials. I agree with him that computer science professors are eager to apply the idea of recursion on factorials, but I’ve never remembered a professor mention that it’s not the most efficient way. McConnell states in the book that doing recursion in factorials:
- Is not as fast as a for-loop.
- Not as clear to read as a for-loop.
- Use of run-time memory is unpredictable.
Just for fun, I wanted to test his point on speed. This is a Python script that tests the average speed of a factorial using a for-loop or recursion. I noticed that for numbers less than 3000! the time it took for both functions were exactly the same. It was only when I bumped it up to 5000!, which is a huge number (16,327 digits). Luckily Python lets you work with very large numbers easily. Just had to increase the number of recursion calls in Python from the default 1000.
import win32api
import sys
sys.setrecursionlimit(10000)
def factorial_forloop( n ):
count = 1
for i in range( n, 0, -1 ):
count = count * i
return count
def factorial_recursion(n):
if n == 0:
return 1
else:
return n * factorial_recursion(n-1)
total_time_recursion = 0
total_time_forloop = 0
number_of_tries = 500
for i in range( 1, number_of_tries ):
start = win32api.GetTickCount()
factorial_recursion( 5000 )
end = win32api.GetTickCount()
total = end - start
total_time_recursion += total
start = win32api.GetTickCount()
factorial_forloop( 5000 )
end = win32api.GetTickCount()
total = end - start
total_time_forloop += total
print "\n"
print "Average time for recursion: ", ( total_time_recursion / 10 ) * .001
print "Average time for for-loop: ", ( total_time_forloop / 10 ) * .001So in 500 tries, the results were as follows:
Average time for recursion: 1.284 seconds
Average time for for-loop: 1.083 seconds
It doesn’t seem by much but the results are interesting. But then again, a factorial is a very simple algorithm. In future posts I’ll try to test more complicated algorithms and see how they battle out. Also, this is Python. The results for C, C++, or Java may differ.
This was a great read. Certainly learned a lot of useful lessons on front-end optimizations. Written by Steve Souders (previously lead Optimization efforts at Yahoo!), who also developed YSlow! – a Firefox add-on (actually an add-on to the Firefox add-on called Firebug) that gives your web pages a grade from A through F and tells you how to make it better.
If you have a build script, you may be able to automate a lot of these things, like combining JS and CSS files, and optimize PNG files (check out http://www.phpied.com/give-png-a-chance/ to see how to optimize from the command line). If you’re going to optimize JavaScript, I would recommend YUI Compressor (http://developer.yahoo.com/yui/compressor/) since it’s not as greedy as Google’s Closure Compiler for JavaScript. The Closure compiler (http://code.google.com/closure/compiler/) is relatively new and you may get even smaller files, but if your JavaScript is complex, it may have bugs because it’s a greedy compiler.
Anywhoot, here’s what I got from it:
- Reduce as many HTTP requests as possible.
- Minify JavaScript (don’t obfuscate, because it’s more trouble than it’s worth for the benefits you get)
- Minify CSS and optimize it (reduce duplication).
- Future-expire resources for caching (PNG, JPG, GIF, JavaScript and CSS).
- Minify HTML (get away from tables)
- Put CSS at the top, put JavaScript at the bottom.
- For design components (background images, button images, nav images), use CSS sprites.
- Use PNG for design components (they compress better than GIF, have partial transparency, and can have greater color palettes).
- Gzip non-binary data like HTML.
- Combine CSS and JavaScript into single files to reduce HTTP requests.
A summary of his optimization rules are found here, but of course, it’s not as detailed as the book: http://stevesouders.com/hpws/rules.php .
Stoyan Stefanov, another prominent developer who’s written tons on JavaScript and optimization, published 24 articles this month on optimization. I find these articles invaluable. It’s recent and he does actual optimization tests and tells you what tools he uses. Here’s the site: http://www.phpied.com/performance-advent-calendar-2009/
Posted by Dan | Posted in ColdFusion, XML | Posted on 01-03-2010
0
Whipped out this little script to read an OPML file from Google Reader. Thought it may be handy.
<cfset GoogleOPMLFile = "C:/google-reader-subscriptions.xml" />
<cffile action="READ" variable="xml" file="#GoogleOPMLFile#" />
<cfset xmlDoc = XMLParse(xml) />
<cfset StartingDataNode = 2 />
<cfset Categories = ArrayLen( xmlDoc.opml.xmlChildren[2].XmlChildren ) />
<cfoutput>
<cfloop index="i" from="2" to="#Categories#">
<strong>#xmlDoc.opml.xmlChildren[StartingDataNode].XmlChildren[i].XmlAttributes.Title#</strong>
<ul>
<cfloop index="j" from="1" to="#ArrayLen( xmlDoc.opml.xmlChildren[StartingDataNode].XmlChildren[i].XmlChildren )#">
<li>
<a href="#xmlDoc.opml.xmlChildren[StartingDataNode].XmlChildren[i].XmlChildren[j].XmlAttributes.htmlURL#">
#xmlDoc.opml.xmlChildren[StartingDataNode].XmlChildren[i].XmlChildren[j].XmlAttributes.title#</a>
</li>
</cfloop>
</ul>
</cfloop>
</cfoutput>The code will display as follows:
Posted by Dan | Posted in ColdFusion, Python | Posted on 12-29-2009
0
I just tried to write a quick script in Python that scans CFCs and generates a yUML URL to diagram. I pointed my script to my root CFC path and I got a 13K strlen URL. I pasted it in the address bar to see what happened and I got the following:
Request-URI Too Large
The requested URL's length exceeds the capacity limit for this server.
Apache/2.2.3 (Debian) Phusion_Passenger/2.0.2 Server at Ess000235.gtcust.grouptelecom.net Port 80
I wonder what the limitation is. I suppose I’ll have to do a CFC per diagram and then bind them together somehow. I’m choosing Python so this script can be part of my build script.
Here’s the code so far, which of course, could be optimized:
import re
import os
# UML Syntax
# http://yuml.me/diagram/class/[User|Property1;Property2|Method1();Method2()]
# http://yuml.me/diagram/class/
# [
# User
# |
# Property1;
# Property2
# |
# Method1();
# Method2()
# ]
# Master Path
ROOT_PATH = 'C:\\temp\\cf-yuml'
def SearchForFile( rootpath, searchfor, includepath = 0 ):
# Search for a file recursively from a root directory.
# rootpath = root directory to start searching from.
# searchfor = regexp to search for, e.g.:
# search for *.jpg : \.exe$
# includepath = appends the full path to the file
# this attribute is optional
# Returns a list of filenames that can be used to loop
# through.
#
# TODO: Use the glob module instead. Could be faster.
names = []
append = ""
for root, dirs, files in os.walk( rootpath ):
for name in files:
if re.search( searchfor, name ):
if includepath == 0:
root = ""
else:
append = "\\"
names.append( root + append + name )
return names
def getCFCInfo ( FILE, path ):
FILE.seek( 0, 0 )
CFCLines = FILE.readlines()
CFCFunctions = []
CFCProperties = []
CFC = {}
for i in CFCLines:
# Get names of methods
if re.search( "^<cffunction", i , re.IGNORECASE | re.MULTILINE ):
CFCFunctions.append( re.search( r'name\s*=\s*"([\w$-]+)"', i, re.DOTALL | re.IGNORECASE).group(1) )
# Get names of properties
if re.search( "^<cfproperty", i , re.IGNORECASE | re.MULTILINE ):
CFCProperties.append( re.search( r'name\s*=\s*"([\w$-]+)"', i, re.DOTALL | re.IGNORECASE).group(1) )
CFC = { "properties":CFCProperties, "methods":CFCFunctions }
# Generate URL
strFunctions = ""
strProperties = ""
for i in CFCFunctions:
strFunctions += i + "();"
for i in CFCProperties:
strProperties += i + ";"
CFCFileName = re.search(r"\\([\w-]+)\.cfc$", path, re.DOTALL | re.IGNORECASE).group(1)
return "[" + CFCFileName + "|" + ( strProperties.strip()[:-1] + "|" if strProperties.strip()[:-1] else "" ) + strFunctions.strip()[:-1] + "]"
URL = ""
for i in SearchForFile( ROOT_PATH, "\.cfc$", 1 ):
CFCFile = open( i, "r" )
URL += getCFCInfo( CFCFile, i ) + ","
CFCFile.close()
URL = URL[:-1]
print "http://yuml.me/diagram/class/" + URLI’ll keep working on this as time goes on. So far it just goes through all the CFC’s from the path you point to. It will crawl through all sub directories. There’s no relationship between classes, however. Not yet at least.
Posted by Dan | Posted in Python, SQL Server | Posted on 12-27-2009
0
Setting up Python to connect to SQL Server was relatively easy. First, you select a DB API driver. I chose pyodbc because I saw a Python article on Simple-Talk. There are two simple steps:
- Install Pywin32. Get the latest. It’s a dependency for pyodbc.
- Install pyodbc. Get it for the version of Python you’re using.
Once you’ve done this, you can query your SQL Server db as so:
import pyodbc
connection = pyodbc.connect('DRIVER={SQL Server};SERVER=192.168.0.5;DATABASE=MyAwesomeDB;UID=sa;PWD=password')
cursor = connection.cursor()
cursor.execute("select * from states")
for row in cursor:
print row.StateID, row.Abbreviation, row.NameFor more snippets and a tutorial, check out the documentation.
Now let’s try something more interesting. Let’s try doing some inserts and see how long it takes.
import win32api
import uuid
import pyodbc
connection = pyodbc.connect('DRIVER={SQL Server};SERVER=192.168.0.5;DATABASE=MrSkittles;UID=sa;PWD=password')
cursor = connection.cursor()
_start = win32api.GetTickCount()
for i in range( 0, 10000 ):
# Let's insert two pieces of data, both random UUIDs.
sql = "INSERT INTO Manager VALUES( '" + str( uuid.uuid4() ) + "', '" + str( uuid.uuid4() ) + "' )"
cursor.execute( sql )
connection.commit()
_end = win32api.GetTickCount()
_total = _end - _start
print "\n\nProcess took", _total * .001, "seconds"After some tests, 10,000 records took roughly 20-30 seconds. 1,000,000 records took 30 to 40 minutes. A bit slow, but it’s not a server machine. My machine is a Core Duo, 1.8Ghz x 2, at ~4GB with PAE on WindowsXP, but I ran this on a VMware VM with 1GB and SQL Server 2005 w/Windows Server 2003. The table was a two column table both varchar(50). On a server machine, it should be a helluva lot faster.
Posted by Dan | Posted in IIS, Python, SQL Server | Posted on 12-12-2009
0
While working with some IIS logs, I decided to start practicing my Python. I put together some handy Python functions to work with IIS Log files. These will come in handy. On a 3GB, 2.5GHz, running WinXP machine, these functions take about 3 seconds to process a 180MB Text file. Python code could be optimized to be faster if you’re dealing with larger sized files.
#!/usr/bin/env python
# An IIS log file can have various log properties. Everytime you add new columns to log for
# in IIS, it creates a new row full of columns.
import re
import os
MainLogDelimiter = "#Software: Microsoft Internet Information Services 6.0"
TestFile = "C:\\Dan\\IIS-Log-Import\\Logs\\not-the-same.txt"
BigTestFile = "C:\\Dan\\IIS-Log-Import\\Logs\\ex090914\\ex090914.log"
LogsDir = "C:\\Dan\\IIS-Log-Import\\Logs"
def SearchForFile( rootpath, searchfor, includepath = 0 ):
# Search for a file recursively from a root directory.
# rootpath = root directory to start searching from.
# searchfor = regexp to search for, e.g.:
# search for *.jpg : \.exe$
# includepath = appends the full path to the file
# this attribute is optional
# Returns a list of filenames that can be used to loop
# through.
#
# TODO: Use the glob module instead. Could be faster.
names = []
append = ""
for root, dirs, files in os.walk( rootpath ):
for name in files:
if re.search( searchfor, name ):
if includepath == 0:
root = ""
else:
append = "\\"
names.append( root + append + name )
return names
def isSameLogProperties( FILE ):
# Tests to see if a log file has the same number of columns throughout
# This is in case new column properties were added/subtracted in the course
# of the log file.
FILE.seek( 0, 0 )
SubLogs = FILE.read().split( MainLogDelimiter )
# SubLogs[0] Stores the number of different log variations in the log file
SubLogs[0] = len( SubLogs ) - 1
# Grab the column names from the log file, separated by space
columns = re.search( "^#Fields:\s([\w\-()\s]+)$", SubLogs[1], re.IGNORECASE | re.MULTILINE ).group(1)
LogSameProperties = True
for i in range( 2, SubLogs[0] + 1 ):
# If there are columns
if ( len( columns ) > 0 ):
if ( columns != re.search( "^#Fields:\s([\w\-()\s]+)$", SubLogs[i], re.IGNORECASE | re.MULTILINE ).group(1) ):
LogSameProperties = False
break
return LogSameProperties
def getFirstColumn( FILE ):
# This gets the columns from a log file. It returns only the first columns, and ignores another column
# row that may exist in case new columns were added/subtracted in IIS.
# input: FILE
# output: 1 single element List
FILE.seek( 0, 0 )
names = []
# Grab the column names from the log file, separated by space
names.append( re.search( "^#Fields:\s([\w\-()\s]+)$", FILE.read().split( MainLogDelimiter )[1], re.IGNORECASE | re.MULTILINE ).group(1).strip() )
return names
def getAllColumns( FILE ):
# This gets all the columns from a log file.
# input: FILE
# output: List
FILE.seek( 0, 0 )
names = []
SubLogs = FILE.read().split( MainLogDelimiter )
# SubLogs[0] Stores the number of different log variations in the log file
SubLogs[0] = len( SubLogs ) - 1
for i in range( 1, SubLogs[0] + 1 ):
names.append( re.search( "^#Fields:\s([\w\-()\s]+)$", SubLogs[i], re.IGNORECASE | re.MULTILINE ).group(1).strip() )
return names
# EXAMPLE:
# Loop through all the IIS log files in the directory
# for file in SearchForFile( LogsDir, "\.txt$", 1 ):
LogFile = open( file, "r" )
if ( isSameLogProperties( LogFile ) ):
print file, "the same"
else:
print file, "not the same"
LogFile.close()
Posted by Dan | Posted in IIS, Perl, Systems | Posted on 12-11-2009
0
If you think that Log Parser is a bit on the slow side (i.e. if you’re dealing with big IIS logs) and you want to bulk import your logs into SQL Server, then you’ll have to remove # comments from the log files. Microsoft has the PrepWebLog Utility to do this, but it seems to choke for files that are > 100 MB. Also, you’ll have to write this as a batch file so it goes through a whole directory of files.
I wrote a Perl script that’s relatively fast (faster than PrepWebLog) and it can crawl folders/subfolders recursively. Here it is:
# parse.pl
# example:
# parse c:\temp\logs\logs*\*.log
#
# Requirement: no spaces in the directory names and file names.
# This gets called via run.bat.
sub getFileList
{
# This function returns an array of file list based on filter
# This is the filter they can put in.
# Returns a file with full path.
# Example of filters: getFileList ( "*.log" );
@files = <@_[0]>;
return @files;
}
sub remove_comments
{
# Remove # pound sign comments from files.
# @_[0] = filename
open (my $in, "<", @_[0] )
or die "in: @_[0]";
open (my $out, ">", "@_[0].txt")
or die "out: @_[0]";
while( my $line = <$in>)
{
print $out $line
unless $line =~ /^#/;
}
close $in;
close $out;
}
########## MAIN #############
$arg = @ARGV[0];
# Location of root directory of logs files
#$arg = 'c:\temp\logs\logs*\*.log';
# Replace slashes
$arg =~ s/\\/\\\\/g;
# Loop through all the log files.
for $file (getFileList ($arg))
{
print ( "Processing file $file ... \n" );
remove_comments( $file );
}The Perl script gets called via run.bat:
REM No spaces in directory and file names.
perl Parse.pl D:\statesites\W3SVC*\*.log
pause
Posted by Dan | Posted in JavaScript | Posted on 12-08-2009
0
Rather than assigning event handlers to elements inline from within HTML, like so:
<a id="site" href="http://www.shinylight.com" onmouseover="Show()">Go to my site!</a>
You can assign the event handler programmatically via the onload event of the window object. Like so, in the script element:
window.onload = function()
{
document.getElementById("linkcontent").onmouseover = Show;
}
function Show( )
{
alert( "Hey there, how are you?" + this.href );
}Here’s the HTML:
<body>
<div id="content">
<a id="linkcontent" href="http://www.shinylight.com?var=yes">This is pretty cool</a>
</div>
</body>
</html>
This is just a great way to keep HTML code away from JavaScript. In this case, the handler for window.load will run when all web page resources have finished loading (the full HTML and JavaScript files).
