Welcome to TiddlyWiki created by Jeremy Ruston, Copyright © 2007 UnaMesa Association
Background: #fff
Foreground: #000
PrimaryPale: #8cf
PrimaryLight: #18f
PrimaryMid: #04b
PrimaryDark: #014
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SecondaryLight: #fe8
SecondaryMid: #db4
SecondaryDark: #841
TertiaryPale: #eee
TertiaryLight: #ccc
TertiaryMid: #999
TertiaryDark: #666
Error: #f88
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/*}}}*/
/***
StyleSheet for use when a translation requires any css style changes.
This StyleSheet can be used directly by languages such as Chinese, Japanese and Korean which use a logographic writing system and need larger font sizes.
***/
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/*}}}*/
/*{{{*/
@media print {
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#displayArea {margin: 1em 1em 0em 1em;}
/* Fixes a feature in Firefox 1.5.0.2 where print preview displays the noscript content */
noscript {display:none;}
}
/*}}}*/
<!--{{{-->
<div class='header' macro='gradient vert [[ColorPalette::PrimaryLight]] [[ColorPalette::PrimaryMid]]'>
<div class='headerShadow'>
<span class='siteTitle' refresh='content' tiddler='SiteTitle'></span>
<span class='siteSubtitle' refresh='content' tiddler='SiteSubtitle'></span>
</div>
<div class='headerForeground'>
<span class='siteTitle' refresh='content' tiddler='SiteTitle'></span>
<span class='siteSubtitle' refresh='content' tiddler='SiteSubtitle'></span>
</div>
</div>
<div id='mainMenu' refresh='content' tiddler='MainMenu'></div>
<div id='sidebar'>
<div id='sidebarOptions' refresh='content' tiddler='SideBarOptions'></div>
<div id='sidebarTabs' refresh='content' force='true' tiddler='SideBarTabs'></div>
</div>
<div id='displayArea'>
<div id='messageArea'></div>
<div id='tiddlerDisplay'></div>
</div>
<!--}}}-->
<!--{{{-->
<div class='toolbar' macro='toolbar closeTiddler closeOthers +editTiddler > fields syncing permalink references jump'></div>
<div class='title' macro='view title'></div>
<div class='subtitle'><span macro='view modifier link'></span>, <span macro='view modified date'></span> (<span macro='message views.wikified.createdPrompt'></span> <span macro='view created date'></span>)</div>
<div class='tagging' macro='tagging'></div>
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<!--}}}-->
To get started with this blank TiddlyWiki, you'll need to modify the following tiddlers:
* SiteTitle & SiteSubtitle: The title and subtitle of the site, as shown above (after saving, they will also appear in the browser title bar)
* MainMenu: The menu (usually on the left)
* DefaultTiddlers: Contains the names of the tiddlers that you want to appear when the TiddlyWiki is opened
You'll also need to enter your username for signing your edits: <<option txtUserName>>
These InterfaceOptions for customising TiddlyWiki are saved in your browser
Your username for signing your edits. Write it as a WikiWord (eg JoeBloggs)
<<option txtUserName>>
<<option chkSaveBackups>> SaveBackups
<<option chkAutoSave>> AutoSave
<<option chkRegExpSearch>> RegExpSearch
<<option chkCaseSensitiveSearch>> CaseSensitiveSearch
<<option chkAnimate>> EnableAnimations
----
Also see AdvancedOptions
[[Intro]] FunctionalProgramming
filter(function, sequence) returns a sequence consisting of those items from the sequence for which function(item) is true. If sequence is a string or tuple, the result will be of the same type; otherwise, it is always a list. For example, to compute some primes:
{{{
>>> def f(x): return x % 2 != 0 and x % 3 != 0
...
>>> filter(f, range(2, 25))
[5, 7, 11, 13, 17, 19, 23]
}}}
The function used by filter should return True or False.
!Filtering and Python 3000
According to Guido's [[answer|http://www.artima.com/weblogs/viewpost.jsp?thread=211200]], filter is ''not'' going to be removed from Python 3000. However, replacing filter with a list comprehension is fairly straight forward. Here is the previous example rewritten as a list comprehension.
{{{
>>> def f(x): return x % 2 != 0 and x % 3 != 0
...
>>> [x for x in range(2,25) if f(x)]
[5, 7, 11, 13, 17, 19, 23]
}}}
from the [[python reference|http://docs.python.org/lib/built-in-funcs.html]]
<<<
''filter(''//function, list//'')''
Construct a list from those elements of list for which function returns true. list may be either a sequence, a container which supports iteration, or an iterator, If list is a string or a tuple, the result also has that type; otherwise it is always a list. If function is None, the identity function is assumed, that is, all elements of list that are false are removed.
Note that {{{filter(function, list)}}} is equivalent to {{{[item for item in list if function(item)]}}} if function is not None and {{{[item for item in list if item]}}} if function is None.
<<<
Commonly used programming styles are imperative/procedural, object oriented, and functional
languages
* Procedural - describes computation as statements that change a program state. They are a sequence of commands for the computer to perform. Procedural programming is a common method of executing imperative programming, and the terms are often used as synonyms.
* Object Oriented (OO)- imperative programming extended with the ability to package data and related functionality as classes
* Functional programming - based on lambda calculus, Functional languages treat functions like they treat built-in types—they can be passed and returned as values to and from other functions, and can even be created at runtime.
Since lists are so central in functional programming, you can easily create them by placing expressions inside brackets in Python
{{{
>>> lst = [1,2,3,4]
>>> my_lst = [x+1 for x in xrange(4)]
>>> my_lst
[1,2,3,4]
}}}
my_lst is the result of a list comprehension.
This presentation was given by Jeff Hinrichs at the [[Omaha Python Users Group|http://www.omahapython.org]] meeting on Dec 5, 2007.
Python supports the creation of anonymous functions (i.e. functions that are not bound to a name) at runtime, using a construct called "lambda". This is not exactly the same as lambda in functional programming languages, but it is a very powerful concept that's well integrated into Python and is often used in conjunction with typical functional concepts like filter(), map() and reduce().
This piece of code shows the difference between a normal function definition "mysquare" and a lambda function "lambda_square":
{{{
>>> def mysquare(x): return x**2
...
>>> print mysquare(8)
64
>>>
>>> lambda_square = lambda x: x**2
>>>
>>> print lambda_square(8)
64
}}}
* [[More on lambda|http://docs.python.org/tut/node6.html#SECTION006750000000000000000]]
* [[lambda in the Python reference manual|http://www.python.org/doc/ref/lambdas.html]]
List comprehensions can traverse multiple sequences just like nested loops do and can filter out what isn't wanted. Several support functions are important in functional programming.
{{{
setA = ['x','y','z']
setB = [0,1,2]
print [(x,y) for x in setA for y in setB if x!='y' if y > 0]
}}}
{{{[('x', 1), ('x', 2), ('z', 1), ('z', 2)]}}}
Here is the equivalent code written in a procedural style
{{{
result = []
setA = ['x','y','z']
setB = [0,1,2]
for x in setA:
for y in setB:
if x != 'y':
if y > 0:
result.append((x,y))
print result
}}}
{{{[('x', 1), ('x', 2), ('z', 1), ('z', 2)]}}}
[[Intro]]
FunctionalProgramming
ListComprehensions
[[Map]]
[[Lambda]]
[[Reduce]]
[[Filter]]
[[Zip]]
Python3000Functional
The map function applies a function to each element of a list and returns the resulting list:
{{{
>>> map(len,["The", "xen", "of", "Python"])
[3, 3, 2, 6]
}}}
The map function also accommodates functions whose number of arguments matches the number of subsequent lists:
{{{
>>> import operator
>>> map(operator.add, [1,2,3],[4,5,6])
[5, 7, 9]
}}}
^^* [[more info on the operator library|http://www.python.org/doc/current/lib/module-operator.html]]
!Map and Python 3000
While there has been talk of removing map from the core library of Python, it is easily rewritten using a ListComprehensions
Here is the first example rewritten as a list comprehension.
{{{
[len(x) for x in ["The", "xen", "of", "Python"]]
[3, 3, 2, 6]
}}}
A quick Google of "python 3k map filter reduce" returns a number of posts by the BDFL who initially supported their removal. However, over time a number of discussions have taken place where clean, real world examples of how these functions are superior in terms of readability as compared to the List Comprehension forms.
It appears as though ''reduce'' is still scheduled to be removed from Python 3000. [[See Here|http://www.artima.com/weblogs/viewpost.jsp?thread=211200]]
Even in the worst case, where they were dropped from the core language and not put in the standard library, they could be easily implemented in a 3rd party library with just straight Python code. An exercise, that I leave for you. Guido says:
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I'm killing it because almost all code using reduce() is less readable than the same thing written out using a for loop and an accumulator variable.
<<<
The reduce function is used to summarize a list, normally reducing it to a single value.
from the [[python reference|http://docs.python.org/lib/built-in-funcs.html]]
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''reduce(''//function, sequence[, initializer]//'')''
Apply function of two arguments cumulatively to the items of sequence, from left to right, so as to reduce the sequence to a single value. For example, reduce(lambda x, y: x+y, [1, 2, 3, 4, 5]) calculates ((((1+2)+3)+4)+5). The left argument, x, is the accumulated value and the right argument, y, is the update value from the sequence. If the optional initializer is present, it is placed before the items of the sequence in the calculation, and serves as a default when the sequence is empty. If initializer is not given and sequence contains only one item, the first item is returned.
<<<
For example, to sum the elements of a list, you could use the following expression:
{{{
>>> import operator
>>> reduce(operator.add, [1,2,3])
6
}}}
written with a lambda it would look like:
{{{
>>> reduce(lambda x,y: x + y, [1,2,3])
6
}}}
* for addition, however, it is better to use the built-in sum function:
{{{
>>> sum([1,2,3])
6
}}}
The following expression forms the product of a list:
{{{
>>> reduce(lambda x,y: x*y, [1,2,3])
6
}}}
You can pass a third argument as an initializer. Helpful when the list happens to be empty:
{{{
>>> reduce(lambda x,y: x*y, [], 1)
1
}}}
Here is a function that checks to see if any value in a sequence of Booleans is true:
{{{
>>> def are_any_true(blst):
... return reduce(lambda x,y: x or y, blst, False)
...
>>> b = [True, False, False]
>>> are_any_true(b)
True
>>> are_any_true([])
False
}}}
* [[More info on reduce|http://www.python.org/doc/2.3.5/tut/node7.html#SECTION007130000000000000000]]
Functional Programming in Python
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zip() takes one or more sequences and weaves their elements together, just as map(None, ...) does with sequences of equal length. The weaving stops when the shortest sequence is exhausted.
zip() returns a real Python list
{{{
>>> zip([1,2,3],[4,5,6])
[(1, 4), (2, 5), (3, 6)]
}}}
To re-implement the map example:
{{{
>>> import operator
>>> map(operator.add, [1,2,3],[4,5,6])
[5, 7, 9]
}}}
As a ListComprehensions using the zip() function
{{{
>>> [x+y for (x,y) in zip([1,2,3],[4,5,6])]
[5, 7, 9]
}}}
from the [[python reference|http://docs.python.org/lib/built-in-funcs.html]]
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''zip(''//[iterable, ...]//'')''
This function returns a list of tuples, where the i-th tuple contains the i-th element from each of the argument sequences or iterables. The returned list is truncated in length to the length of the shortest argument sequence. When there are multiple arguments which are all of the same length, zip() is similar to map() with an initial argument of None. With a single sequence argument, it returns a list of 1-tuples. With no arguments, it returns an empty list. New in version 2.0.
<<<