Python on Lorenzo Bolla

Python MRO surprises

Fri, 02 Dec 2022 00:00:00 +0000

Consider a script like this:

class A:
 def __init__(self):
 print('a')

class B:
 def __init__(self):
 print('b')

class C(A, B):
 def __init__(self):
 super().__init__()
 print('c')

C()

What will it output? If you are like me, you would answer, without much thought, that it prints:

a
c

To work it out you need to know about Python's MRO (Method Resolution Order): this article provides a clear explanation of how it works. In this case, we have:

Nice threads in Python

Sat, 01 Feb 2020 00:00:00 +0000

Python has two ways to execute code in parallel: processes and threads. Both have their strengths and weaknesses. In particular, threads are cheaper in terms of resources and are able to share memory, but besides the obvious pitfalls of multi-threaded programming, they suffer from some Python specific problems, notably:

Because of the GIL, only one Python's thread is actually running at any one time. So, very little parallelism is possible if the task is CPU bound. In fact, more often than not, it's more efficient to execute multiple tasks sequentially on a single thread (pinned to a single CPU), rather than spawning multiple threads and having the Python interpreter context switching too much and not being able to schedule the threads on all available CPUs.

Edit Kubernetes secrets

Sun, 14 Jan 2018 00:00:00 +0000

Kubernetes secrets are difficult to edit using standard command line tools, like kubectl.

When doing kubectl edit secret my-secret you are presented with a base64-encoded blob that you have to first decode, in order to edit it and then re-encode before saving the file.

There are various ways to deal with it, but none is user-friendly, in my opinion. Therefore, I wrote kube-secret-editor: a simple Python script to decode and encode secret values on the flight before/after editing.

Elixir pipe operator in Python

Wed, 25 May 2016 00:00:00 +0000

Elixir implements lots of nice ideas, one of which is its pipe operator. It allows you to write things like:

iex> [1, [2], 3] |> List.flatten()
[1, 2, 3]

Or:

iex> inc = fn x -> x + 1 end
iex> dec = fn x -> x - 1 end
iex> square = fn x -> x * x end
iex> 5 |> inc.() |> dec.() |> square.()
25

Today, just for fun, I tried to implement something similar in Python. Here is the result:

So, you can write something like:

>>> 5 |P| inc |P| dec |P| square
25

Obviously, this is just a toy: it does not implement all the features available in the Elixir's one, but it was fun!

Comparison of blocking and non-blocking Python multiprocessing Queue

Mon, 25 Apr 2016 00:00:00 +0000

Python's multiprocessing module offers a Queue implementation. Surprisingly enough (for me at least), its performance varies greatly if used in a blocking or non-blocking fashion. In particular, the non-blocking way is about ten times slower than the blocking one!

Consider this code, which feeds a Queue and then drains it in a blocking and non-blocking way:

Running it on my machine, with Python 2.7, gives me these results (Python 3.4 results are similar, but less dramatic):

EMpy 1.0 is out! Python3 compatible!

Sun, 26 Apr 2015 00:00:00 +0000

After a long sleep, I resumed development on Empy. The trigger was an appeal from Guido van Rossum at PyCon 2015 to package authors to support Python 3.

There are no new features to Empy, but I have:

ported the code to Python 3, using the amazing future library: now, both Python 2 and 3 are supported;
setup Travis CI to run unittest on all supported Python versions;
upgraded the dependencies to the latest available libraries;
Pylint'd and pep8'd the code
Renamed the package in PyPi to ElectroMagneticPython to avoid name conflicts with EmPy.

You can try it out by simply:

Experiments in pickling

Wed, 14 May 2014 00:00:00 +0000

pickle is a standard library module to serialize and deserialize Python objects. Being written in pure Python, it's fairly slow, so the standard library provides a pure-C implementation, called cPickle, with the limitation that it cannot be subclassed.

What's interesting about cPickle are two little known settings that can speed up serialization quite substantially.

cPickle.HIGHEST_PROTOCOL basically dumps a Python object using a binary protocol, rather than the default ASCII-based, more portable, protocol 0. If portability or backward compatibility are not an issue for you, you should use it: it's documented and probably here to stay.

Die zombie, die!

Thu, 23 Jan 2014 00:00:00 +0000

The subprocess module in Python standard library allows you to spanw processes to do some tasks. The parent process should wait on its children processes in order get the return value of the process and avoid zombies.

Sometimes, though, processes are particularly hard to kill and even after a wait, a terminate or a kill they refuse to die: they become zombies.

In theory, Python should take care of reaping zombies for you once the zombie process gets garbage collected. In practice, it does not seem to work reliably and bigger weapons are needed.

Long running processes manager

Fri, 17 Jan 2014 00:00:00 +0000

If you want to run multiple processes in Python, the nicest way, in my opinion, is to use concurrent.futures (there is a backport for Python 2.x, too).

A problem that came up recently was to manage multiple long running processes, intended to run forever, from the same Python process. Using something like supervisord wouldn't be ideal, because each individual application would have its own config file and deployment procedure.

Instead, having just one "master" Python process to drive several other processes doing the job seemed the easiest solution to manage. The only caveat is that, being the processes managed long running, you want to restart them as soon as they die.

Overcoming Python GIL with Cython

Mon, 23 Dec 2013 00:00:00 +0000

Everybody is aware of the infamous Python's GIL. In a nutshell, the GIL is a global variable that prevents multiple threads to be run concurrently by the interpreter. Under some occasions, for certain operations, the interpreter releases the GIL therefore in certain cases this is not a problem. For example, the GIL is released before doing I/O, so I/O bound threads tend to run concurrently. Another example is when doing system calls. Unfortunately, for CPU bound tasks that don't make any I/O or system calls, the GIL prevents different threads from running concurrently, even on multicore CPUs. The astonishing thing is that, in fact, not only different threads do not run concurrently, but they also run slower on multicore CPUs than on single core ones!

Connect to MSSQL from Python with ODBC and FreeTDS

Thu, 29 Aug 2013 00:00:00 +0000

This is another of those posts that I wrote because I always forget how to do things…

This time, I don't want to forget how to connect from Python to MSSQL server anymore. In order to do it, you need the following system packages installed:

$> sudo apt-get install unixodbc-dev tdsodbc sqsh

sqsh installs all the required freetds-related libraries; tdsodbc is the FreeTDS driver for ODBC and unixodbc-dev is needed to install pyodbc.

Python and C with ctypes

Wed, 28 Aug 2013 00:00:00 +0000

Calling C code from Python is very simple using ctypes. Here is a very simple example to get you started and to serve as a reminder for me!

Let's say you have this C file, defining 3 functions:

foo which prints something to stdout;
bar which returns and int;
baz which takes a parameter and returns a value.

First, you want to compile this C file into a shared object. Here is a Makefile to do just this: simple type make all and you're done.

Use Postgres advanced types in Python

Wed, 06 Mar 2013 00:00:00 +0000

Postgres has a lot of useful builtin data types, but only some of them are mapped to Python types when accessing the DB using psycopg2.

Extending the support to other types is not straightforward, and involves the following steps:

Create a Python class to store the data, e.g. class Point
Write a function to convert a Point to its SQL string representation, e.g. adapt_point
Write the inverse function to parse the SQL string representation of a Point and return and instance of a Point, e.g. cast_point
Finally bind all these functions and types, see register_point_type

The complete code is as follows, also available as a gist:

Blocking tasks in Tornado

Tue, 22 Jan 2013 00:00:00 +0000

Every now and then a new discussion is raised on Tornado's mailling list about what is the best way to execute blocking tasks. It turns out that there are 3 feasible options, in order of increasing complexity:

Optimize blocking calls. Often, a slow DB query, or an overly complicate template are the blocking bottleneck. Rather than complicating the webserver, the first thing to try is to speed them up. This is sufficient 99% of the time.
Execute the slow task in a separate thread or process. This means off-loading the task to a different thread (or process) to the one running the IOLoop, which is then free to accept other requests.
Use an asynchronous driver/library to run the task. For example, something like gevent, motor and the like.

This blog post is about the second option, in particular using Python's concurrent.futures package.

Useful scripts - Watch

Fri, 30 Nov 2012 00:00:00 +0000

This is the fifth post of a series describing simple scripts that I wrote to ease my life as a programmer.

They are available on github: fork & hack at will!

Watch reacts to changes in a directory executing a command provided by the user. It can be used, for example, to monitor a directory and run some unittests as soon as files in it change. This is exactly how I am using Watch in acme.

Useful scripts - htmlind and xmlind

Fri, 23 Nov 2012 00:00:00 +0000

This is the forth post of a series describing simple scripts that I wrote to ease my life as a programmer.

In this post I'll describe 2 simple scripts to indent nicely HTML and XML files. I use them primarily with acme, to pipe selected text and get back nicely formatted output.

Code is available here: htmlind and xmlind. Both programs are written in Python and make use of specialized libraries freely available online. In particular, xmlind uses xml.dom.minidom, included in Python's standard library, and htmlind uses a modified version of BeautifulSoup.

Useful scripts - csvfmt, xmlfmt, jsonfmt

Fri, 16 Nov 2012 00:00:00 +0000

This is the third post of a series describing simple scripts that I wrote to ease my life as a programmer.

In this post, I'll describe 3 scripts to "pretty print" some common file types, to improve readability: csvfmt, xmlfmt and jsonfmt.

csvfmt takes a CSV ("Comma Separated Values") file from stdin, parses it and pretty print each record as a Python dictionary.

#!/usr/bin/env python

import csv
import sys
import pprint

for row in csv.DictReader(sys.stdin):
 pprint.pprint(row)

Output looks like this:

Wordpress to markdown

Mon, 12 Nov 2012 00:00:00 +0000

Recently, I moved away from Wordpress. I did it primarily because Wordpress is so much more than just a blogging platform and what I needed was just a simple way of publishing posts with embedded code, links and images. Moreover, writing blogs using Wordpress's web editor is less than ideal…

The biggest problem to solve when moving away from Wordpress is how to not lose all your posts. Luckily, Wordpress allows you to export all your stuff in XML, but you also need a way to import them in whatever other blogging platform you are going to use.

Useful scripts - c+-c-

Fri, 09 Nov 2012 00:00:00 +0000

This is the second post of a series describing simple scripts that I wrote to ease my life as a programmer.

They are available on github: fork & hack at will!

c+/c-

In this post I'll describe a very simple script, c+, and its counterpart c-.

c+ prepends every line of stdin with #. c- strips # from the beginning of each line of stdin. I use these scripts to comment/uncomment lines in Python scripts when using acme.

Useful scripts - a+-a-

Fri, 02 Nov 2012 00:00:00 +0000

This is the first post of a series describing simple scripts that I wrote to ease my life as a programmer.

They are implemented in various languages (python, bash, go) and thought to be used in Linux. Some of them are "general purpose", while others are specifically designed to interface other tools I use (for example, acme.)

All of them tend to have the following properties:

Input from stdin, output to stdout, errors to stderr
Return zero on success, non-zero on failure
Do one thing only
Not too much customizable

These properties allow the scripts to remain very simple, be composable and easy to remember.

Asynchronous programming with Tornado

Wed, 03 Oct 2012 00:00:00 +0000

Asynchronous programming can be tricky for beginners, therefore I think it's useful to iron some basic concepts to avoid common pitfalls. For an explanation about generic asynchronous programming, I recommend you one of the many resources online. I will focus solely on asynchronous programming in Tornado.

From Tornado's homepage:

FriendFeed's web server is a relatively simple, non-blocking web server written in Python. The FriendFeed application is written using a web framework that looks a bit like web.py or Google's webapp, but with additional tools and optimizations to take advantage of the non-blocking web server and tools. Tornado is an open source version of this web server and some of the tools we use most often at FriendFeed. The framework is distinct from most mainstream web server frameworks (and certainly most Python frameworks) because it is non-blocking and reasonably fast. Because it is non-blocking and uses epoll or kqueue, it can handle thousands of simultaneous standing connections, which means the framework is ideal for real-time web services. We built the web server specifically to handle FriendFeed's real-time features every active user of FriendFeed maintains an open connection to the FriendFeed servers. (For more information on scaling servers to support thousands of clients, see The C10K problem.)

Tornado vs. Warp vs. Yesod

Sun, 02 Sep 2012 00:00:00 +0000

Today I tried to benchmark 3 web servers that I've used recently:

In fact, these are only *2* web servers, because Yesod runs on top of Warp and it's a fully fledged web framework, rather than a web server: but this was also the intent of the benchmark, i.e. to measure how slower all its goodies made Yesod with respect to Warp.

Tornado and Warp are obviously very different web servers (async vs. threaded, interpreted vs. compiled, etc.) but, who cares?

EMpy has moved!

Mon, 25 Jun 2012 00:00:00 +0000

Empy has moved to Github!

Pipelines in Python

Fri, 20 Apr 2012 00:00:00 +0000

Generators (PEP 255 "Simple Generators") and Coroutines (PEP 342 "Coroutines via Enhanced Generators") are the cleanest way I've come across so far to implement the concept of a "pipeline" in Python.

First approximation

A pipeline is made of:

a Producer, that generates data;
many /Stage/s, that receive data from the previous stage and send it to the next;
a Consumer, that receives data from the last stage.

The producer is a coroutine that only /send/s data, generated internally from some initial state. /Stage/s are coroutines that both receive and send messages. The consumer only receives data. Chaining is done in function pipeline: each argument but the last is instantiated with an instance of the next stage. The full pipeline is started by issuing a next (or send(None)) to the Producer.

hsenv

Thu, 29 Mar 2012 00:00:00 +0000

If you have never used hsenv before, you should. It's basically the Haskell's equivalent of Python's virtualenv.

You can find a tweaked version of hsenv here: I've relaxed some requirements in order to make it install on newer GHC releases.

Finally, if when using you hit this error:

$ hsenv Creating Virtual Haskell directory structure
Installing GHC Initializing GHC Package database at /home/lollo/work/Unique/.hsenv/ghc_pkg_db
Copying necessary packages from original GHC package database
hsenv: fd:9: hGetContents: invalid argument (invalid byte sequence)
hsenv: thread blocked indefinitely in an MVar operation

Then, you have a problem with your locale. Follow the steps here, and retry.

ulint, Universal Lint

Thu, 05 Jan 2012 00:00:00 +0000

I've been using so many code static checkers lately, that I decided to write a wrapper around the ones I use the most. I called it: Universal Lint, ulint for short.

At the moment, Python, Javascript and Haskell files are supported, but adding new linters/extension is trivial.

Download it and use it!

git pre-commit hook for Python and Javascript

Thu, 17 Nov 2011 00:00:00 +0000

Following a recent discussion on HN, I decided to share my own git pre-commit hook.

#!/usr/bin/python

import os
import sys
import re
import subprocess


devnull = open(os.devnull, 'w')


def call(cmd):
 p = subprocess.Popen(cmd.split(),
 stdout=subprocess.PIPE,
 stderr=subprocess.PIPE)
 out, err = p.communicate()
 return out.decode('utf-8'), err.decode('utf-8'), p.returncode


def execute(cmd, silent=False):
 if silent:
 params = {
 'stdout': devnull,
 'stderr': devnull,
 }
 else:
 params = {}

 retcode = subprocess.call(cmd.split(), **params)
 return retcode


def exists(cmd):
 return execute('which %s' % cmd, silent=True) == 0


def get_modified(ext):
 modified = re.compile('^(?:M|A).(?P<name>.*\.%s)' % ext)
 out, _, _ = call('git status --porcelain')
 modifieds = []
 for line in out.splitlines():
 match = modified.match(line.strip())
 if (match):
 modifieds.append(match.group('name'))
 return modifieds

It's a work-in-progress, so you can find the most updated version here. To use it, just drop it in your .git/hooks directory. At every git commit, it will run [pep8][4] and [pyflakes][5] on .py files, and [gjslint][6] on .js files.

pylint.vim

Thu, 25 Aug 2011 00:00:00 +0000

vim + Python + pylint is a powerful combination, especially when using this vim plugin. Unfortunately, the script stopped working after a pylint upgrade:

$ pylint --version
pylint 0.24.0,
astng 0.22.0, common 0.56.0
Python 2.7.2 (default, Jun 29 2011, 11:10:00)
[GCC 4.6.1]

You can download the fixed version here!

If interested, the patch looks like this:

diff pylint.vim.orig pylint.vim
69c69
< CompilerSet makeprg=(echo\ '[%]';\ pylint\ -r\ y\ %)
---
> CompilerSet makeprg=(echo\ '[%]';\ pylint\ -r\ y\ --output-format=parseable\
> %)
74c74
< CompilerSet efm=%+P[%f],%t:\ %#%l:%m,%Z,%+IYour\ code%m,%Z,%-G%.%#
---
> CompilerSet efm=%f:%l:\ [%t]%m,%f:%l:%m

MD5 vs SHA1 in Python

Wed, 24 Aug 2011 00:00:00 +0000

If you are interested to know if the myth about MD5 being faster than SHA1 holds for Python, here is the result I got on my box:

In [1]: import hashlib
In [2]: %timeit hashlib.md5('text text text').hexdigest()
1000000 loops, best of 3: 1.29 us per loop
In [3]: %timeit hashlib.sha1('text text text').hexdigest()
1000000 loops, best of 3: 1.4 us per loop

Result is: MD5 is faster, but only just, in Python 2.7.2. Considering that MD5 is broken, I think I'll use SHA1…

Get registered domain in Python and Javascript

Tue, 05 Apr 2011 00:00:00 +0000

reg-dom-libs are a set of libraries for C, PHP and Perl to convert an arbitrary domain name to the registered domain name.

For simple domains, like www.amazon.com or news.ycombinator.com, the task is trivial.
For more complicated ones, like www.ebay.co.uk or www.japantimes.co.jp, handling the second level subdomain is a little painful.
For exoteric ones, like nic.com.ai or www.nic.net.ge or 公司.cn, the problem becomes virtually impossible.
After seeing stupid ones, like www.comune.caserta.it (believe it or not, the registered domain is comune.caserta.it!), I gave up finding an elegant algorithm for the problem.
A full list of valid registered domain is necessary. Luckily, it is available (and nightly updated) here.

Inspired by reg-dom-libs, I've ported the algorithm to Python and Javascript. See the tests at the end of each file for an example of the usage. A demo is available here.

twill revived

Fri, 11 Mar 2011 00:00:00 +0000

After reading how to do automated testing in python, I've started using twill, by C. Titus Brown

twill is a simple language that allows users to browse the Web from a command-line interface. With twill, you can navigate through Web sites that use forms, cookies, and most standard Web features.

Unfortunately, development on twill seems to have stopped 3 years ago.

I've cloned the project on Github, fixed some deprecation warnings and added a cool new feature to inspect headers, as well as html.

tdaemon for Python3

Sun, 20 Feb 2011 00:00:00 +0000

tdaemon is a neat little utility to do continuous testing in Python. Unfortunately, the original version only works with Python2. I've spent a little time to make it work with Python3.

Enjoy!

Missing `Dec_0` and friends from Python Decimal

Thu, 29 Jul 2010 00:00:00 +0000

This fails in py2.4, py2.5.1 and py2.6:

from decimal import Dec_0

But it works in all the other py2.5 subversions!

It seems that exposing Dec_0 (and other similar constants) was considered a bug and "fixed" on Jan 3rd 2009 by renaming it _Dec_0.

Indeed, if I had looked at the source code, I would have seen that Dec_0 was for "internal use only".

From /usr/lib/python2.5/decimal.py:5159

# Reusable defaults
Inf = Decimal('Inf')
negInf = Decimal('-Inf')
NaN = Decimal('NaN')
Dec_0 = Decimal(0)
Dec_p1 = Decimal(1)
Dec_n1 = Decimal(-1)

Those definitions are missing in py2.4 and py2.5.1, and renamed in py2.6.

Wordpress Python library

Sun, 06 Jun 2010 00:00:00 +0000

Today, I found this. It's a wonderfully simple Python library to manage your Wordpress blog via XML-RPC.

Enjoy!

vim and Python comments

Wed, 12 Aug 2009 00:00:00 +0000

I'm currently undergoing a profound revision (read "cleanup") of my .vimrc and I recently had to choose a decent plug-in to comment python code.

The best so far is EnhancedCommentify. It's highly configurable, powerful and it supports a different number of languages (not only python).

The only one thing that wasn't easy to setup if the behaviour described here: being able to comment a block, respecting the indent, in both visual and normal mode.

qwerty vs dvorak vs colemak to edit Python code

Mon, 02 Feb 2009 00:00:00 +0000

Yesterday, I was intrigued by the idea of choosing a more efficient keyboard layout to work with everyday. As long as I type Python code 90% of my time, I decided to evaluate the efficiency of the first 3 most widespread keyboard layouts: QWERTY, Dvorak and Colemak. I used this excellent tool to compare the three layouts over the first 50000 characters of the webpy source code. Here are the results:

 <div id="page">
 <div id="text">
 <h1>
The Qwerty Keyboard Layout Vs The Dvorak Keyboard Layout
 </h1>
 <h2 style="font-size: 90%;">
:: UP ::Overall effort
 </h2>
 <table>
 <thead class="small">
 <tr>
 <td class="a1">
Layout
 </td>
 <td class="a0">
Effort
 </td>
 <td class="a1">


% improvement over worst layout


 </td>
 <td class="a0"></td>
 </tr>
 </thead>
 <tbody>
 <tr>
 <td class="a1">


Qwerty


 </td>
 <td class="a0" style="text-align: right;">


306,509.6


 </td>
 <td class="a1" style="text-align: right;">


0.0 %


 </td>
 <td class="a0"></td>
 </tr>
 <tr>
 <td class="a1">


Dvorak


 </td>
 <td class="a0" style="text-align: right;">


283,868.7


 </td>
 <td class="a1" style="text-align: right;">


7.4 %


 </td>
 <td class="a0"></td>
 </tr>
 <tr>
 <td class="a1">


Colemak


 </td>
 <td class="a0" style="text-align: right;">


275,347.6


 </td>
 <td class="a1" style="text-align: right;">


10.2 %


 </td>
 <td class="a0"></td>
 </tr>
 </tbody>
 </table>
 <hr />
 <h2 style="font-size: 90%;">


:: UP ::Keys for each finger (stronger fingers should be used more often)


 </h2>
 <table>
 <thead class="small">
 <tr>
 <td class="a1">


Layout


 </td>
 <td class="a0">


Thumbs


 </td>
 <td class="a1">


LPinky


 </td>
 <td class="a0">


LRing


 </td>
 <td class="a1">


LMiddle


 </td>
 <td class="a0">


LIndex


 </td>
 <td class="a1">


RIndex


 </td>
 <td class="a0">


RMiddle


 </td>
 <td class="a1">


RRing


 </td>
 <td class="a0">


RPinky


 </td>
 <td class="a1">


Total


 </td>
 </tr>
 </thead>
 <tbody>
 <tr>
 <td class="a1">


Qwerty


 </td>
 <td class="a0" style="text-align: right;">


25.9 %


 </td>
 <td class="a1" style="text-align: right;">


12.4 %


 </td>
 <td class="a0" style="text-align: right;">


5.3 %


 </td>
 <td class="a1" style="text-align: right;">


9.5 %


 </td>
 <td class="a0" style="text-align: right;">


11.6 %


 </td>
 <td class="a1" style="text-align: right;">


7.6 %


 </td>
 <td class="a0" style="text-align: right;">


5.6 %


 </td>
 <td class="a1" style="text-align: right;">


8.9 %


 </td>
 <td class="a0" style="text-align: right;">


13.2 %


 </td>
 <td class="a1" style="text-align: right;">


54,237.0 keys


 </td>
 </tr>
 <tr>
 <td class="a1">


Dvorak


 </td>
 <td class="a0" style="text-align: right;">


25.9 %


 </td>
 <td class="a1" style="text-align: right;">


13.0 %


 </td>
 <td class="a0" style="text-align: right;">


5.2 %


 </td>
 <td class="a1" style="text-align: right;">


8.1 %


 </td>
 <td class="a0" style="text-align: right;">


7.3 %


 </td>
 <td class="a1" style="text-align: right;">


7.5 %


 </td>
 <td class="a0" style="text-align: right;">


7.5 %


 </td>
 <td class="a1" style="text-align: right;">


8.2 %


 </td>
 <td class="a0" style="text-align: right;">


17.3 %


 </td>
 <td class="a1" style="text-align: right;">


54,237.0 keys


 </td>
 </tr>
 <tr>
 <td class="a1">


Colemak


 </td>
 <td class="a0" style="text-align: right;">


25.9 %


 </td>
 <td class="a1" style="text-align: right;">


12.7 %


 </td>
 <td class="a0" style="text-align: right;">


4.8 %


 </td>
 <td class="a1" style="text-align: right;">


7.5 %


 </td>
 <td class="a0" style="text-align: right;">


9.5 %


 </td>
 <td class="a1" style="text-align: right;">


8.4 %


 </td>
 <td class="a0" style="text-align: right;">


10.1 %


 </td>
 <td class="a1" style="text-align: right;">


6.6 %


 </td>
 <td class="a0" style="text-align: right;">


14.5 %


 </td>
 <td class="a1" style="text-align: right;">


54,237.0 keys


 </td>
 </tr>
 </tbody>
 </table>
 <table>
 <thead class="small">
 <tr>
 <td class="a1">


Layout


 </td>
 <td class="a0">


Thumbs


 </td>
 <td class="a1">


Left hand


 </td>
 <td class="a0">


Right hand


 </td>
 <td class="a1">


Total


 </td>
 <td class="a0"></td>
 </tr>
 </thead>
 <tbody>
 <tr>
 <td class="a1">


Qwerty


 </td>
 <td class="a0" style="text-align: right;">


25.9 %


 </td>
 <td class="a1" style="text-align: right;">


38.8 %


 </td>
 <td class="a0" style="text-align: right;">


35.2 %


 </td>
 <td class="a1" style="text-align: right;">


54,237.0 keys


 </td>
 <td class="a0"></td>
 </tr>
 <tr>
 <td class="a1">


Dvorak


 </td>
 <td class="a0" style="text-align: right;">


25.9 %


 </td>
 <td class="a1" style="text-align: right;">


33.6 %


 </td>
 <td class="a0" style="text-align: right;">


40.5 %


 </td>
 <td class="a1" style="text-align: right;">


54,237.0 keys


 </td>
 <td class="a0"></td>
 </tr>
 <tr>
 <td class="a1">


Colemak


 </td>
 <td class="a0" style="text-align: right;">


25.9 %


 </td>
 <td class="a1" style="text-align: right;">


34.5 %


 </td>
 <td class="a0" style="text-align: right;">


39.6 %


 </td>
 <td class="a1" style="text-align: right;">


54,237.0 keys


 </td>
 <td class="a0"></td>
 </tr>
 </tbody>
 </table>
 <hr />
 <h2 style="font-size: 90%;">


:: UP ::Finger Travel Distance (only the horizontal)


 </h2>
 <table>
 <thead class="small">
 <tr>
 <td class="a1">


Layout


 </td>
 <td class="a0">


Thumbs


 </td>
 <td class="a1">


LPinky


 </td>
 <td class="a0">


LRing


 </td>
 <td class="a1">


LMiddle


 </td>
 <td class="a0">


LIndex


 </td>
 <td class="a1">


RIndex


 </td>
 <td class="a0">


RMiddle


 </td>
 <td class="a1">


RRing


 </td>
 <td class="a0">


RPinky


 </td>
 <td class="a1">


Total


 </td>
 </tr>
 </thead>
 <tbody>
 <tr>
 <td class="a1">


Qwerty


 </td>
 <td class="a0" style="text-align: right;">


0.0 %


 </td>
 <td class="a1" style="text-align: right;">


18.1 %


 </td>
 <td class="a0" style="text-align: right;">


2.0 %


 </td>
 <td class="a1" style="text-align: right;">


10.5 %


 </td>
 <td class="a0" style="text-align: right;">


15.5 %


 </td>
 <td class="a1" style="text-align: right;">


12.1 %


 </td>
 <td class="a0" style="text-align: right;">


8.6 %


 </td>
 <td class="a1" style="text-align: right;">


9.9 %


 </td>
 <td class="a0" style="text-align: right;">


23.4 %


 </td>
 <td class="a1" style="text-align: right;">


1,441.5 m


 </td>
 </tr>
 <tr>
 <td class="a1">


Dvorak


 </td>
 <td class="a0" style="text-align: right;">


0.0 %


 </td>
 <td class="a1" style="text-align: right;">


21.1 %


 </td>
 <td class="a0" style="text-align: right;">


4.1 %


 </td>
 <td class="a1" style="text-align: right;">


3.5 %


 </td>
 <td class="a0" style="text-align: right;">


10.0 %


 </td>
 <td class="a1" style="text-align: right;">


12.5 %


 </td>
 <td class="a0" style="text-align: right;">


7.6 %


 </td>
 <td class="a1" style="text-align: right;">


10.8 %


 </td>
 <td class="a0" style="text-align: right;">


30.4 %


 </td>
 <td class="a1" style="text-align: right;">


1,210.3 m


 </td>
 </tr>
 <tr>
 <td class="a1">


Colemak


 </td>
 <td class="a0" style="text-align: right;">


0.0 %


 </td>
 <td class="a1" style="text-align: right;">


23.7 %


 </td>
 <td class="a0" style="text-align: right;">


2.5 %


 </td>
 <td class="a1" style="text-align: right;">


6.1 %


 </td>
 <td class="a0" style="text-align: right;">


10.2 %


 </td>
 <td class="a1" style="text-align: right;">


10.2 %


 </td>
 <td class="a0" style="text-align: right;">


9.3 %


 </td>
 <td class="a1" style="text-align: right;">


9.3 %


 </td>
 <td class="a0" style="text-align: right;">


28.6 %


 </td>
 <td class="a1" style="text-align: right;">


1,131.2 m


 </td>
 </tr>
 </tbody>
 </table>
 <table>
 <thead class="small">
 <tr>
 <td class="a1">


Layout


 </td>
 <td class="a0">


Thumbs


 </td>
 <td class="a1">


Left hand


 </td>
 <td class="a0">


Right hand


 </td>
 <td class="a1">


Total


 </td>
 <td class="a0"></td>
 </tr>
 </thead>
 <tbody>
 <tr>
 <td class="a1">


Qwerty


 </td>
 <td class="a0" style="text-align: right;">


0.0 %


 </td>
 <td class="a1" style="text-align: right;">


46.0 %


 </td>
 <td class="a0" style="text-align: right;">


54.0 %


 </td>
 <td class="a1" style="text-align: right;">


1,441.5 m


 </td>
 <td class="a0"></td>
 </tr>
 <tr>
 <td class="a1">


Dvorak


 </td>
 <td class="a0" style="text-align: right;">


0.0 %


 </td>
 <td class="a1" style="text-align: right;">


38.8 %


 </td>
 <td class="a0" style="text-align: right;">


61.2 %


 </td>
 <td class="a1" style="text-align: right;">


1,210.3 m


 </td>
 <td class="a0"></td>
 </tr>
 <tr>
 <td class="a1">


Colemak


 </td>
 <td class="a0" style="text-align: right;">


0.0 %


 </td>
 <td class="a1" style="text-align: right;">


42.6 %


 </td>
 <td class="a0" style="text-align: right;">


57.4 %


 </td>
 <td class="a1" style="text-align: right;">


1,131.2 m


 </td>
 <td class="a0"></td>
 </tr>
 </tbody>
 </table>
 <hr />
 <h2 style="font-size: 90%;">


:: UP ::% home keys (out of all character keys plus SHIFT and ENTER, but excluding keys operated by thumbs)


 </h2>
 <table>
 <tbody>
 <tr>
 <td>


Qwerty


 </td>
 <td style="text-align: right;">


20.4 %


 </td>
 <td class="bar"></td>
 </tr>
 <tr>
 <td>


Dvorak


 </td>
 <td style="text-align: right;">


33.7 %


 </td>
 <td class="bar"></td>
 </tr>
 <tr>
 <td>


Colemak


 </td>
 <td style="text-align: right;">


38.7 %


 </td>
 <td class="bar"></td>
 </tr>
 </tbody>
 </table>
 <hr />
 <h2 style="font-size: 90%;">


:: UP ::% keys typed with the same finger as the previous key (excluding repeating keys like ss)


 </h2>
 <table>
 <tbody>
 <tr>
 <td>


Qwerty


 </td>
 <td style="text-align: right;">


4.5 %


 </td>
 <td class="bar"></td>
 </tr>
 <tr>
 <td>


Dvorak


 </td>
 <td style="text-align: right;">


3.8 %


 </td>
 <td class="bar"></td>
 </tr>
 <tr>
 <td>


Colemak


 </td>
 <td style="text-align: right;">


3.6 %


 </td>
 <td class="bar"></td>
 </tr>
 </tbody>
 </table>
 <hr />
 <h2 style="font-size: 90%;">


:: UP ::% keys typed with the same hand as the previous key (ex: in Qwerty sd or ss are included, but s s is not since you type the space with the other hand)


 </h2>
 <table>
 <tbody>
 <tr>
 <td>


Qwerty


 </td>
 <td style="text-align: right;">


26.8 %


 </td>
 <td class="bar"></td>
 </tr>
 <tr>
 <td>


Dvorak


 </td>
 <td style="text-align: right;">


20.0 %


 </td>
 <td class="bar"></td>
 </tr>
 <tr>
 <td>


Colemak


 </td>
 <td style="text-align: right;">


24.6 %


 </td>
 <td class="bar"></td>
 </tr>
 </tbody>
 </table>
 <hr />
 <h2 style="font-size: 90%;">


:: UP ::% keys typed with the same hand as the previous key and jumping a row (ex: in Qwerty ev is a row jump -- you jump over the middle row -- and it's awkward to type; ef is not a row jump)


 </h2>
 <table>
 <tbody>
 <tr>
 <td>


Qwerty


 </td>
 <td style="text-align: right;">


10.3 %


 </td>
 <td class="bar"></td>
 </tr>
 <tr>
 <td>


Dvorak


 </td>
 <td style="text-align: right;">


5.7 %


 </td>
 <td class="bar"></td>
 </tr>
 <tr>
 <td>


Colemak


 </td>
 <td style="text-align: right;">


4.1 %


 </td>
 <td class="bar"></td>
 </tr>
 </tbody>
 </table>
 <hr />
 <h2 style="font-size: 90%;">


:: UP ::% keys typed with the same hand as the previous key and in reverse order (ex: in Qwerty df or kj are typed in the easier order pinky-ring-middle-index, whereas fd and jk are in reverse order index-middle-ring-pinky, and harder to type)


 </h2>
 <table>
 <tbody>
 <tr>
 <td>


Qwerty


 </td>
 <td style="text-align: right;">


15.4 %


 </td>
 <td class="bar"></td>
 </tr>
 <tr>
 <td>


Dvorak


 </td>
 <td style="text-align: right;">


11.9 %


 </td>
 <td class="bar"></td>
 </tr>
 <tr>
 <td>


Colemak


 </td>
 <td style="text-align: right;">


15.2 %


 </td>
 <td class="bar"></td>
 </tr>
 </tbody>
 </table>
 <hr />
 <h2 style="font-size: 90%;">


:: UP ::% keys that need the SHIFT modifier


 </h2>
 <table>
 <tbody>
 <tr>
 <td>


Qwerty


 </td>
 <td style="text-align: right;">


14.3 %


 </td>
 <td class="bar"></td>
 </tr>
 <tr>
 <td>


Dvorak


 </td>
 <td style="text-align: right;">


14.3 %


 </td>
 <td class="bar"></td>
 </tr>
 <tr>
 <td>


Colemak


 </td>
 <td style="text-align: right;">


14.3 %


 </td>
 <td class="bar"></td>
 </tr>
 </tbody>
 </table>
 <hr />
 <h2 style="font-size: 90%;">


:: UP ::Pairs of consecutive keys typed with the same finger in Qwerty


 </h2>
 <table>
 <tbody>
 <tr>
 <td>


:/NewLine/


 </td>
 <td style="text-align: right;">


253 times


 </td>
 <td style="text-align: right;">


0.47 %


 </td>
 </tr>
 <tr>
 <td>


de


 </td>
 <td style="text-align: right;">


200 times


 </td>
 <td style="text-align: right;">


0.37 %


 </td>
 </tr>
 <tr>
 <td>


tr


 </td>
 <td style="text-align: right;">


158 times


 </td>
 <td style="text-align: right;">


0.29 %


 </td>
 </tr>
 <tr>
 <td>


rt


 </td>
 <td style="text-align: right;">


102 times


 </td>
 <td style="text-align: right;">


0.19 %


 </td>
 </tr>
 <tr>
 <td>


ol


 </td>
 <td style="text-align: right;">


99 times


 </td>
 <td style="text-align: right;">


0.18 %


 </td>
 </tr>
 <tr>
 <td>


un


 </td>
 <td style="text-align: right;">


98 times


 </td>
 <td style="text-align: right;">


0.18 %


 </td>
 </tr>
 <tr>
 <td>


q\_LeftShift\_


 </td>
 <td style="text-align: right;">


87 times


 </td>
 <td style="text-align: right;">


0.16 %


 </td>
 </tr>
 <tr>
 <td>


ce


 </td>
 <td style="text-align: right;">


86 times


 </td>
 <td style="text-align: right;">


0.16 %


 </td>
 </tr>
 <tr>
 <td>


“/NewLine/


 </td>
 <td style="text-align: right;">


81 times


 </td>
 <td style="text-align: right;">


0.15 %


 </td>
 </tr>
 <tr>
 <td>


ed


 </td>
 <td style="text-align: right;">


80 times


 </td>
 <td style="text-align: right;">


0.15 %


 </td>
 </tr>
 <tr>
 <td>


}/NewLine/


 </td>
 <td style="text-align: right;">


62 times


 </td>
 <td style="text-align: right;">


0.11 %


 </td>
 </tr>
 </tbody>
 </table>
 <hr />
 <h2 style="font-size: 90%;">


:: UP ::Pairs of consecutive keys typed with the same finger in Dvorak


 </h2>
 <table>
 <tbody>
 <tr>
 <td>


ct


 </td>
 <td style="text-align: right;">


196 times


 </td>
 <td style="text-align: right;">


0.36 %


 </td>
 </tr>
 <tr>
 <td>


s\_RightShift\_


 </td>
 <td style="text-align: right;">


169 times


 </td>
 <td style="text-align: right;">


0.31 %


 </td>
 </tr>
 <tr>
 <td>


db


 </td>
 <td style="text-align: right;">


152 times


 </td>
 <td style="text-align: right;">


0.28 %


 </td>
 </tr>
 <tr>
 <td>


l\_RightShift\_


 </td>
 <td style="text-align: right;">


137 times


 </td>
 <td style="text-align: right;">


0.25 %


 </td>
 </tr>
 <tr>
 <td>


‘/LeftShift/


 </td>
 <td style="text-align: right;">


133 times


 </td>
 <td style="text-align: right;">


0.25 %


 </td>
 </tr>
 <tr>
 <td>


rn


 </td>
 <td style="text-align: right;">


115 times


 </td>
 <td style="text-align: right;">


0.21 %


 </td>
 </tr>
 <tr>
 <td>


ls


 </td>
 <td style="text-align: right;">


100 times


 </td>
 <td style="text-align: right;">


0.18 %


 </td>
 </tr>
 <tr>
 <td>


}/NewLine/


 </td>
 <td style="text-align: right;">


62 times


 </td>
 <td style="text-align: right;">


0.11 %


 </td>
 </tr>
 <tr>
 <td>


=/RightShift/


 </td>
 <td style="text-align: right;">


59 times


 </td>
 <td style="text-align: right;">


0.11 %


 </td>
 </tr>
 <tr>
 <td>


“/LeftShift/


 </td>
 <td style="text-align: right;">


58 times


 </td>
 <td style="text-align: right;">


0.11 %


 </td>
 </tr>
 <tr>
 <td>


e.


 </td>
 <td style="text-align: right;">


58 times


 </td>
 <td style="text-align: right;">


0.11 %


 </td>
 </tr>
 </tbody>
 </table>
 <hr />
 <h2 style="font-size: 90%;">


:: UP ::Pairs of consecutive keys typed with the same finger in Colemak


 </h2>
 <table>
 <tbody>
 <tr>
 <td>


:/NewLine/


 </td>
 <td style="text-align: right;">


253 times


 </td>
 <td style="text-align: right;">


0.47 %


 </td>
 </tr>
 <tr>
 <td>


ue


 </td>
 <td style="text-align: right;">


237 times


 </td>
 <td style="text-align: right;">


0.44 %


 </td>
 </tr>
 <tr>
 <td>


db


 </td>
 <td style="text-align: right;">


152 times


 </td>
 <td style="text-align: right;">


0.28 %


 </td>
 </tr>
 <tr>
 <td>


e,


 </td>
 <td style="text-align: right;">


89 times


 </td>
 <td style="text-align: right;">


0.16 %


 </td>
 </tr>
 <tr>
 <td>


q\_LeftShift\_


 </td>
 <td style="text-align: right;">


87 times


 </td>
 <td style="text-align: right;">


0.16 %


 </td>
 </tr>
 <tr>
 <td>


“/NewLine/


 </td>
 <td style="text-align: right;">


81 times


 </td>
 <td style="text-align: right;">


0.15 %


 </td>
 </tr>
 <tr>
 <td>


}/NewLine/


 </td>
 <td style="text-align: right;">


62 times


 </td>
 <td style="text-align: right;">


0.11 %


 </td>
 </tr>
 <tr>
 <td>


]/NewLine/


 </td>
 <td style="text-align: right;">


46 times


 </td>
 <td style="text-align: right;">


0.08 %


 </td>
 </tr>
 <tr>
 <td>


pt


 </td>
 <td style="text-align: right;">


44 times


 </td>
 <td style="text-align: right;">


0.08 %


 </td>
 </tr>
 <tr>
 <td>


‘/RightShift/


 </td>
 <td style="text-align: right;">


41 times


 </td>
 <td style="text-align: right;">


0.08 %


 </td>
 </tr>
 <tr>
 <td>


“/RightShift/


 </td>
 <td style="text-align: right;">


41 times


 </td>
 <td style="text-align: right;">


0.08 %


 </td>
 </tr>
 </tbody>
 </table>
 <hr />
 <h2 style="font-size: 90%;">


:: UP ::Key frequency in your text


 </h2>
 <table>
 <tbody>
 <tr>
 <td>


/Space/


 </td>
 <td style="text-align: right;">


14067 times


 </td>
 <td style="text-align: right;">


25.94 %


 </td>
 </tr>
 <tr>
 <td>


/LeftShift/


 </td>
 <td style="text-align: right;">


4391 times


 </td>
 <td style="text-align: right;">


8.10 %


 </td>
 </tr>
 <tr>
 <td>


e


 </td>
 <td style="text-align: right;">


3239 times


 </td>
 <td style="text-align: right;">


5.97 %


 </td>
 </tr>
 <tr>
 <td>


t


 </td>
 <td style="text-align: right;">


2184 times


 </td>
 <td style="text-align: right;">


4.03 %


 </td>
 </tr>
 <tr>
 <td>


s


 </td>
 <td style="text-align: right;">


2170 times


 </td>
 <td style="text-align: right;">


4.00 %


 </td>
 </tr>
 <tr>
 <td>


r


 </td>
 <td style="text-align: right;">


1890 times


 </td>
 <td style="text-align: right;">


3.48 %


 </td>
 </tr>
 <tr>
 <td>


a


 </td>
 <td style="text-align: right;">


1619 times


 </td>
 <td style="text-align: right;">


2.99 %


 </td>
 </tr>
 <tr>
 <td>


o


 </td>
 <td style="text-align: right;">


1557 times


 </td>
 <td style="text-align: right;">


2.87 %


 </td>
 </tr>
 <tr>
 <td>


l


 </td>
 <td style="text-align: right;">


1530 times


 </td>
 <td style="text-align: right;">


2.82 %


 </td>
 </tr>
 <tr>
 <td>


n


 </td>
 <td style="text-align: right;">


1519 times


 </td>
 <td style="text-align: right;">


2.80 %


 </td>
 </tr>
 <tr>
 <td>


/NewLine/


 </td>
 <td style="text-align: right;">


1511 times


 </td>
 <td style="text-align: right;">


2.79 %


 </td>
 </tr>
 <tr>
 <td>


i


 </td>
 <td style="text-align: right;">


1372 times


 </td>
 <td style="text-align: right;">


2.53 %


 </td>
 </tr>
 <tr>
 <td>


/RightShift/


 </td>
 <td style="text-align: right;">


1357 times


 </td>
 <td style="text-align: right;">


2.50 %


 </td>
 </tr>
 <tr>
 <td>


d


 </td>
 <td style="text-align: right;">


1014 times


 </td>
 <td style="text-align: right;">


1.87 %


 </td>
 </tr>
 <tr>
 <td>


f


 </td>
 <td style="text-align: right;">


971 times


 </td>
 <td style="text-align: right;">


1.79 %


 </td>
 </tr>
 <tr>
 <td>


c


 </td>
 <td style="text-align: right;">


855 times


 </td>
 <td style="text-align: right;">


1.58 %


 </td>
 </tr>
 <tr>
 <td>


u


 </td>
 <td style="text-align: right;">


851 times


 </td>
 <td style="text-align: right;">


1.57 %


 </td>
 </tr>
 <tr>
 <td>


m


 </td>
 <td style="text-align: right;">


716 times


 </td>
 <td style="text-align: right;">


1.32 %


 </td>
 </tr>
 <tr>
 <td>


p


 </td>
 <td style="text-align: right;">


715 times


 </td>
 <td style="text-align: right;">


1.32 %


 </td>
 </tr>
 <tr>
 <td>


(


 </td>
 <td style="text-align: right;">


674 times


 </td>
 <td style="text-align: right;">


1.24 %


 </td>
 </tr>
 <tr>
 <td>


)


 </td>
 <td style="text-align: right;">


673 times


 </td>
 <td style="text-align: right;">


1.24 %


 </td>
 </tr>
 <tr>
 <td>


.


 </td>
 <td style="text-align: right;">


658 times


 </td>
 <td style="text-align: right;">


1.21 %


 </td>
 </tr>
 <tr>
 <td>


‘


 </td>
 <td style="text-align: right;">


623 times


 </td>
 <td style="text-align: right;">


1.15 %


 </td>
 </tr>
 <tr>
 <td>


,


 </td>
 <td style="text-align: right;">


573 times


 </td>
 <td style="text-align: right;">


1.06 %


 </td>
 </tr>
 <tr>
 <td>


b


 </td>
 <td style="text-align: right;">


571 times


 </td>
 <td style="text-align: right;">


1.05 %


 </td>
 </tr>
 <tr>
 <td>


“


 </td>
 <td style="text-align: right;">


563 times


 </td>
 <td style="text-align: right;">


1.04 %


 </td>
 </tr>
 <tr>
 <td>


\_


 </td>
 <td style="text-align: right;">


554 times


 </td>
 <td style="text-align: right;">


1.02 %


 </td>
 </tr>
 <tr>
 <td>


=


 </td>
 <td style="text-align: right;">


518 times


 </td>
 <td style="text-align: right;">


0.96 %


 </td>
 </tr>
 <tr>
 <td>


:


 </td>
 <td style="text-align: right;">


490 times


 </td>
 <td style="text-align: right;">


0.90 %


 </td>
 </tr>
 <tr>
 <td>


q


 </td>
 <td style="text-align: right;">


463 times


 </td>
 <td style="text-align: right;">


0.85 %


 </td>
 </tr>
 <tr>
 <td>


y


 </td>
 <td style="text-align: right;">


423 times


 </td>
 <td style="text-align: right;">


0.78 %


 </td>
 </tr>
 <tr>
 <td>


h


 </td>
 <td style="text-align: right;">


416 times


 </td>
 <td style="text-align: right;">


0.77 %


 </td>
 </tr>
 <tr>
 <td>


w


 </td>
 <td style="text-align: right;">


352 times


 </td>
 <td style="text-align: right;">


0.65 %


 </td>
 </tr>
 <tr>
 <td>


>


 </td>
 <td style="text-align: right;">


348 times


 </td>
 <td style="text-align: right;">


0.64 %


 </td>
 </tr>
 <tr>
 <td>


g


 </td>
 <td style="text-align: right;">


304 times


 </td>
 <td style="text-align: right;">


0.56 %


 </td>
 </tr>
 <tr>
 <td>


v


 </td>
 <td style="text-align: right;">


257 times


 </td>
 <td style="text-align: right;">


0.47 %


 </td>
 </tr>
 <tr>
 <td>


x


 </td>
 <td style="text-align: right;">


253 times


 </td>
 <td style="text-align: right;">


0.47 %


 </td>
 </tr>
 <tr>
 <td>


k


 </td>
 <td style="text-align: right;">


231 times


 </td>
 <td style="text-align: right;">


0.43 %


 </td>
 </tr>
 <tr>
 <td>


<


 </td>
 <td style="text-align: right;">


154 times


 </td>
 <td style="text-align: right;">


0.28 %


 </td>
 </tr>
 <tr>
 <td>


/


 </td>
 <td style="text-align: right;">


125 times


 </td>
 <td style="text-align: right;">


0.23 %


 </td>
 </tr>
 <tr>
 <td>


[]


 </td>
 <td style="text-align: right;">


119 times


 </td>
 <td style="text-align: right;">


0.22 %


 </td>
 </tr>
 <tr>
 <td>


;


 </td>
 <td style="text-align: right;">


113 times


 </td>
 <td style="text-align: right;">


0.21 %


 </td>
 </tr>
 <tr>
 <td>


0


 </td>
 <td style="text-align: right;">


86 times


 </td>
 <td style="text-align: right;">


0.16 %


 </td>
 </tr>
 <tr>
 <td>


`


 </td>
 <td style="text-align: right;">


85 times


 </td>
 <td style="text-align: right;">


0.16 %


 </td>
 </tr>
 <tr>
 <td>


+


 </td>
 <td style="text-align: right;">


84 times


 </td>
 <td style="text-align: right;">


0.15 %


 </td>
 </tr>
 <tr>
 <td>


1


 </td>
 <td style="text-align: right;">


81 times


 </td>
 <td style="text-align: right;">


0.15 %


 </td>
 </tr>
 <tr>
 <td>


{


 </td>
 <td style="text-align: right;">


80 times


 </td>
 <td style="text-align: right;">


0.15 %


 </td>
 </tr>
 <tr>
 <td>


}


 </td>
 <td style="text-align: right;">


79 times


 </td>
 <td style="text-align: right;">


0.15 %


 </td>
 </tr>
 <tr>
 <td>


-


 </td>
 <td style="text-align: right;">


78 times


 </td>
 <td style="text-align: right;">


0.14 %


 </td>
 </tr>
 <tr>
 <td>


j


 </td>
 <td style="text-align: right;">


76 times


 </td>
 <td style="text-align: right;">


0.14 %


 </td>
 </tr>
 <tr>
 <td>


*


 </td>
 <td style="text-align: right;">


72 times


 </td>
 <td style="text-align: right;">


0.13 %


 </td>
 </tr>
 <tr>
 <td>


#


 </td>
 <td style="text-align: right;">


69 times


 </td>
 <td style="text-align: right;">


0.13 %


 </td>
 </tr>
 <tr>
 <td>


2


 </td>
 <td style="text-align: right;">


67 times


 </td>
 <td style="text-align: right;">


0.12 %


 </td>
 </tr>
 <tr>
 <td>


%


 </td>
 <td style="text-align: right;">


55 times


 </td>
 <td style="text-align: right;">


0.10 %


 </td>
 </tr>
 <tr>
 <td>


$


 </td>
 <td style="text-align: right;">


52 times


 </td>
 <td style="text-align: right;">


0.10 %


 </td>
 </tr>
 <tr>
 <td>


3


 </td>
 <td style="text-align: right;">


31 times


 </td>
 <td style="text-align: right;">


0.06 %


 </td>
 </tr>
 <tr>
 <td>


6


 </td>
 <td style="text-align: right;">


29 times


 </td>
 <td style="text-align: right;">


0.05 %


 </td>
 </tr>
 <tr>
 <td>


8


 </td>
 <td style="text-align: right;">


18 times


 </td>
 <td style="text-align: right;">


0.03 %


 </td>
 </tr>
 <tr>
 <td>


@


 </td>
 <td style="text-align: right;">


17 times


 </td>
 <td style="text-align: right;">


0.03 %


 </td>
 </tr>
 <tr>
 <td></td>
 <td style="text-align: right;">


14 times


 </td>
 <td style="text-align: right;">


0.03 %


 </td>
 </tr>
 <tr>
 <td>


z


 </td>
 <td style="text-align: right;">


13 times


 </td>
 <td style="text-align: right;">


0.02 %


 </td>
 </tr>
 <tr>
 <td>


5


 </td>
 <td style="text-align: right;">


13 times


 </td>
 <td style="text-align: right;">


0.02 %


 </td>
 </tr>
 <tr>
 <td>


4


 </td>
 <td style="text-align: right;">


8 times


 </td>
 <td style="text-align: right;">


0.01 %


 </td>
 </tr>
 <tr>
 <td>


?


 </td>
 <td style="text-align: right;">


8 times


 </td>
 <td style="text-align: right;">


0.01 %


 </td>
 </tr>
 <tr>
 <td>


9


 </td>
 <td style="text-align: right;">


7 times


 </td>
 <td style="text-align: right;">


0.01 %


 </td>
 </tr>
 </tbody>
 </table>
 <hr />
 <h2 style="font-size: 90%;">


:: UP ::Frequent pairs of keys in your text


 </h2>
 <table>
 <tbody>
 <tr>
 <td>


\_Space\_\_Space\_


 </td>
 <td style="text-align: right;">


9243 times


 </td>
 <td style="text-align: right;">


17.04 %


 </td>
 </tr>
 <tr>
 <td>


\_NewLine\_\_Space\_


 </td>
 <td style="text-align: right;">


1233 times


 </td>
 <td style="text-align: right;">


2.27 %


 </td>
 </tr>
 <tr>
 <td>


\_Space\_\_LeftShift\_


 </td>
 <td style="text-align: right;">


805 times


 </td>
 <td style="text-align: right;">


1.48 %


 </td>
 </tr>
 <tr>
 <td>


/LeftShift/(


 </td>
 <td style="text-align: right;">


674 times


 </td>
 <td style="text-align: right;">


1.24 %


 </td>
 </tr>
 <tr>
 <td>


/LeftShift/)


 </td>
 <td style="text-align: right;">


673 times


 </td>
 <td style="text-align: right;">


1.24 %


 </td>
 </tr>
 <tr>
 <td>


/LeftShift/”


 </td>
 <td style="text-align: right;">


563 times


 </td>
 <td style="text-align: right;">


1.04 %


 </td>
 </tr>
 <tr>
 <td>


\_LeftShift\_\_


 </td>
 <td style="text-align: right;">


554 times


 </td>
 <td style="text-align: right;">


1.02 %


 </td>
 </tr>
 <tr>
 <td>


se


 </td>
 <td style="text-align: right;">


549 times


 </td>
 <td style="text-align: right;">


1.01 %


 </td>
 </tr>
 <tr>
 <td>


,/Space/


 </td>
 <td style="text-align: right;">


543 times


 </td>
 <td style="text-align: right;">


1.00 %


 </td>
 </tr>
 <tr>
 <td>


/LeftShift/:


 </td>
 <td style="text-align: right;">


490 times


 </td>
 <td style="text-align: right;">


0.90 %


 </td>
 </tr>
 <tr>
 <td>


el


 </td>
 <td style="text-align: right;">


405 times


 </td>
 <td style="text-align: right;">


0.75 %


 </td>
 </tr>
 <tr>
 <td>


er


 </td>
 <td style="text-align: right;">


377 times


 </td>
 <td style="text-align: right;">


0.70 %


 </td>
 </tr>
 <tr>
 <td>


in


 </td>
 <td style="text-align: right;">


364 times


 </td>
 <td style="text-align: right;">


0.67 %


 </td>
 </tr>
 <tr>
 <td>


\_Space\_\_RightShift\_


 </td>
 <td style="text-align: right;">


362 times


 </td>
 <td style="text-align: right;">


0.67 %


 </td>
 </tr>
 <tr>
 <td>


or


 </td>
 <td style="text-align: right;">


352 times


 </td>
 <td style="text-align: right;">


0.65 %


 </td>
 </tr>
 <tr>
 <td>


/LeftShift/>


 </td>
 <td style="text-align: right;">


348 times


 </td>
 <td style="text-align: right;">


0.64 %


 </td>
 </tr>
 <tr>
 <td>


/Space/i


 </td>
 <td style="text-align: right;">


344 times


 </td>
 <td style="text-align: right;">


0.63 %


 </td>
 </tr>
 <tr>
 <td>


/Space/s


 </td>
 <td style="text-align: right;">


341 times


 </td>
 <td style="text-align: right;">


0.63 %


 </td>
 </tr>
 <tr>
 <td>


te


 </td>
 <td style="text-align: right;">


340 times


 </td>
 <td style="text-align: right;">


0.63 %


 </td>
 </tr>
 <tr>
 <td>


e\_LeftShift\_


 </td>
 <td style="text-align: right;">


338 times


 </td>
 <td style="text-align: right;">


0.62 %


 </td>
 </tr>
 <tr>
 <td>


=/Space/


 </td>
 <td style="text-align: right;">


332 times


 </td>
 <td style="text-align: right;">


0.61 %


 </td>
 </tr>
 <tr>
 <td>


/Space/=


 </td>
 <td style="text-align: right;">


321 times


 </td>
 <td style="text-align: right;">


0.59 %


 </td>
 </tr>
 <tr>
 <td>


re


 </td>
 <td style="text-align: right;">


306 times


 </td>
 <td style="text-align: right;">


0.56 %


 </td>
 </tr>
 <tr>
 <td>


lf


 </td>
 <td style="text-align: right;">


294 times


 </td>
 <td style="text-align: right;">


0.54 %


 </td>
 </tr>
 <tr>
 <td>


)/NewLine/


 </td>
 <td style="text-align: right;">


281 times


 </td>
 <td style="text-align: right;">


0.52 %


 </td>
 </tr>
 <tr>
 <td>


e\_Space\_


 </td>
 <td style="text-align: right;">


281 times


 </td>
 <td style="text-align: right;">


0.52 %


 </td>
 </tr>
 </tbody>
 </table>
 </div>

Actually, I was disappointed: there seem to be no clear advantage of Dvorak or Colemak, wrt QWERTY and, given the popularity of the latter, switching does not seem to be a good idea…

py2dot

Sun, 05 Oct 2008 00:00:00 +0000

py2dot is a Python script to generate graphs from a python program. It interprets a Python program as a graphs of function calls. It can represent classes and imported modules.

py2dot is available from pypi. More information are available here.

Tab completion in Python shell

Wed, 25 Jun 2008 00:00:00 +0000

Recently I saw with this little piece of code to give the standard python shell tab completion capabilities:

# setup tab completion in python shell
import rlcompleter
import readline
readline.parse_and_bind("tab: complete")

Obviously, you can use the environmental variable PYTHONSTART to execute this few lines anytime you start your python shell.

Enjoy!

Python and vim

Tue, 22 Apr 2008 00:00:00 +0000

Just a reminder of a very useful set of tips to effectively use vim to edit Python files: http://henry.precheur.org/2008/4/18/Indenting%20Python%20with%20VIM.html

Memoize

Thu, 17 Apr 2008 00:00:00 +0000

Recently, from a discussion on the scipy-user group I discovered a very elegant way to code a function with memory.

Let's state the problem. Suppose you need a function that remembers, for each time it has been called, the input parameters and its output. This can be very useful in many different situations:

If it is very expensive to evaluate, you can check its memory to see if it has been previously evaluated and, if yes, get its return value without actually calling it.
Inside an optimization loop, to remember all the intermediate steps of the optimization.
To accumulate data on the behaviour of the function itself.
To surprise friends ;-)

The function's memory can be as long as the program's running time, or it can be "permanent" if hard-coded in a file. Starting from here I've put together a couple of useful classes in python that can be used as decorators.

IQ test

Sat, 02 Feb 2008 00:00:00 +0000

Qualche giorno fa, mi sono imbattuto in questo test di intelligenza, proposto da ECM. Riporto il testo, per semplicita':

Using each of the numbers 1, 2, 3, 4, 5, 6, 7, 8, 9 only once, form a nine digit number A that can satisfy the following criteria:

A is exactly divisible by 9.

Removing the rightmost digit from A forms an eight digit number B that is exactly divisible by 8.

Removing the rightmost digit from B forms a seven digit number C that is exactly divisible by 7.

EMpy

Thu, 27 Sep 2007 00:00:00 +0000

EMpy is out! Here is the release note:

I'm very pleased to announce the release of EMpy (Electromagnetic Python), a suite of numerical algorithms widely used in electromagnetism.

The package, in its very-alpha stage by now, only contains the transfer matrix and the rigorous coupled wave analysis algorithms, and some handy functions and classes (to model materials, for examples). The idea is to expand it in the near future with new algorithms and interfaces to existent software. The package is based on Numpy/Scipy and its homepage: http://empy.sourceforge.net.

Papers about Python and scientific computing

Wed, 25 Apr 2007 00:00:00 +0000

Here is a list of articles about Python and scientific computing appeared in Computing in Science and Engineering, available online:

Python for Scientific Computing by Travis E. Oliphant (pdf);
Python: Batteries included by Paul F. Dubois;
A Python module for modeling and control design of flexible robots by Ryan W. Krauss;
Analysis of Functional Magnetic Resonance Imaging in Python by K. Jarrod Millman and Matthew Brett, Computing in Science and Engineering, vol. 9, no. 3, pp. 52-55, May/June, 2007;
IPython: A System for Interactive Scientific Computing by Fernando Perez;
Matplotlib: a 2D Graphics Environment by John D. Hunter.

Happy reading!

Numerical computing Matlab vs Python + numpy + weave

Wed, 11 Apr 2007 00:00:00 +0000

Recently, I've discovered the power of Python for numerical computing. Being a slave of Matlab for many years, I've decided to give Python (and it's numerical module numpy) a try, comparing its number crunching capabilities versus Matlab's.

The tests are heavily inspired by Prabhu Ramachandran. I've only added Matlab to complete his comparisons.

Here is a short description of the test, taken from here:

The example we will consider is a very simple (read, trivial) case of solving the 2D Laplace equation using an iterative finite difference scheme (four point averaging, Gauss-Seidel or Gauss-Jordan). The formal specification of the problem is as follows.