New Builtin Functions

The following functions are installed as Python builtin functions at package import time. They are then available as normal builtin functions in every module without explicit import in each module using them (though it is good practice to still put a 'import NewBuiltins' at the top of each module relying on these add-ons).

indices(object)

Returns the same as tuple(range(len(object))) -- a tad faster and a lot easier to type.

trange([start=0,]stop[,step=1])

This works like the builtin function range() but returns a tuple instead of a list. Since range() is most often used in for-loops there really is no need for a mutable data type and construction of tuples is somewhat (20%) faster than that of lists. So changing the usage of range() in for-loops to trange() pays off in the long run.

range_len(object)

Returns the same as range(len(object)).

tuples(sequence)

Returns much the same as apply(map,(None,)+tuple(sequence)) does, except that the resulting list will always have the length of the first sub-sequence in sequence. The function returns a list of tuples (a[0], b[0], c[0],...), (a[1], b[1], c[1],...), ... with missing elements being filled in with None.

Note that the function is of the single argument type meaning that calling tuples(a,b,c) is the same as calling tuples((a,b,c)). tuples() can be used as inverse to lists().

lists(sequence)

Same as tuples(sequence), except that a tuple of lists is returned. Can be used as inverse to tuples().

reverse(sequence)

Returns a tuple or list with the elements from sequence in reverse order. A tuple is returned, if the sequence itself is a tuple. In all other cases a list is returned.

dict(items)

Constructs a dictionary from the given items sequence. The sequence items must contain sequence entries with at least two values. The first one is interpreted as key, the second one as associated object. Remaining values are ignored.

setdict(sequence,value=None)

Constructs a dictionary from the given sequence. The sequence must contain hashable objects which are used as keys. The values are all set to value. Multiple keys are silently ignored. The function comes in handy whenever you need to work with a sequence in a set based context (e.g. to determine the set of used values).

invdict(dictionary)

Constructs a new dictionary from the given one with inverted mappings. Keys become values and vice versa. Note that no exception is raised if the values are not unique. The result is undefined in this case (there is a value:key entry, but it is not defined which key gets used).

irange(object[,indices])

Builds a tuple of tuples (index,object[index]). If a sequence indices is given, the indices are read from it. If not, then the index sequence defaults to trange(len(object)).

Note that object can be any object that can handle object[index], e.g. lists, tuples, string, dictionaries, even your own objects, if they provide a __getitem__-method. This makes very nifty constructions possible and extracting items from another sequence becomes a piece of cake. Give it a try ! You'll soon love this little function.

ifilter(condition,object[,indices])

Builds a list of tuples (index,object[index]) such that condition(object[index]) is true and index is found in the sequence indices (defaulting to trange(len(object))). Order is preserved. condition must be a callable object.

get(object,index[,default])

Returns object[index], or, if that fails, default. If default is not given or the singleton NotGiven an error is raised (the error produced by the object).

extract(object,indices[,defaults])

Builds a list with entries object[index] for each index in the sequence indices.

If a lookup fails and the sequence defaults is given, then defaults[nth_index] is used, where nth_index is the index of index in indices (confused ? it works as expected !). defaults should have the same length as indices.

If you need the indices as well, try the irange function. The function raises an IndexError in case it can't find an entry in indices or defaults.

iremove(object,indices)

Removes the items indexed by indices from object.

This changes the object in place and thus is only possible for mutable types.

For sequences the index list must be sorted ascending; an IndexError will be raised otherwise (and the object left in an undefined state).

findattr(object_list,attrname)

Returns the first attribute with name attrname found among the objects in the list. Raises an AttributeError if the attribute is not found.

attrlist(object_list,attrname)

Returns a list of all attributes with name attrname found among the objects in the list.

napply(number_of_calls,function[,args=(),kw={}])

Calls the given function number_of_calls times with the same arguments and returns a tuple with the return values. This is roughly equivalent to a for-loop that repeatedly calls apply(function,args,kw) and stores the return values in a tuple. Example: create a tuple of 10 random integers... l = napply(10,whrandom.randint,(0,10)).

mapply(callable_objects[,args=(),kw={}])

Creates a tuple of values by applying the given arguments to each object in the sequence callable_objects.

This function has a functionality dual to that of map(). While map() applies many different arguments to one callable object, this function applies one set of arguments to many different callable objects.

method_mapply(objects,methodname[,args=(),kw={}])

Creates a tuple of values by applying the given arguments to each object's <methodname> method. The objects are processed as given in the sequence objects.

A simple application is e.g. method_mapply([a,b,c],'method', (x,y)) resulting in a tuple (a.method(x,y), b.method(x,y), c.method(x,y)). Thanks to Aaron Waters for suggesting this function.

count(condition,sequence)

Counts the number of objects in sequence for which condition returns true and returns the result as integer. condition must be a callable object.

exists(condition,sequence)

Return 1 if and only if condition is true for at least one of the items in sequence and 0 otherwise. condition must be a callable object.

forall(condition,sequence)

Return 1 if and only if condition is true for all of the items in sequence and 0 otherwise. condition must be a callable object.

index(condition,sequence)

Return the index of the first item for which condition is true. A ValueError is raised in case no item is found. condition must be a callable object.

sizeof(object)

Returns the number of bytes allocated for the given Python object. Additional space allocated by the object and stored in pointers is not taken into account (though the pointer itself is). If the object defines tp_itemsize in its type object then it is assumed to be a variable size object and the size is adjusted accordingly.

acquire(object,name)

Looks up the attribute name in object.baseobj and returns the result. If object does not have an attribute 'baseobj' or that attribute is None or the attribute name starts with an underscore, an AttributeError is raised.

This function can be used as __getattr__ hook in Python classes to enable implicit acquisition along a predefined lookup chain (object.baseobj provides a way to set up this chain). See Examples/Acquistion.py for some sample code.

defined(name)

Returns true iff a symbol name is defined in the current namespace.

The function has intimate knowledge about how symbol resolution works in Python: it first looks in locals(), then in globals() and if that fails in __builtins__.

A note on the naming scheme used:

• i stands for indexed, meaning that you have access to indices
• m stands for multi, meaning that processing involves multiple objects
• n stands for n-times, e.g. a function is executed a certain number of times
• t stands for tuple
• x stands for lazy evaluation

Since this is (and will always be) work-in-progress, more functions will eventually turn up in this module, so stopping by every now and then is not a bad idea :-).

New Builtin Objects

These objects are available after importing the package:

xmap(func, seq, [seq, seq, ...])

Constructs a new xmap object emulating map(func, seq, [seq, seq, ...]).

The object behaves like a list, but evaluation of the function is postponed until a specific element from the list is requested. Unlike map, xmap can handle sequences not having a __len__ method defined (due to the evaluation-on-demand feature).

The xmap objects define one method:

tolist()

Return the whole list giving the same result as the emulated map()-construct.

This object is a contribution by Christopher Tavares (see xmap.c for his email address). I am providing this extension AS-IS, since I haven't had time to adapt it to my coding style.

NotGiven

This is a singleton similar to None. Its main purpose is providing a way to indicate that a keyword was not given in a call to a keyword capable function, e.g.

import NewBuiltins

	      def f(a,b=4,c=NotGiven,d=''):
	      if c is NotGiven:
	         return a / b, d
	      else:
	         return a*b + c, d
	    

It is also considered false in if-statements, e.g.

import NewBuiltins

	      a = NotGiven
	      # ...init a conditionally...
	      if not a:
	         print 'a was not given as value'
	    

True, False

These two singletons are used by Python internally to express the boolean values true and false. They represent Python integer objects for 1 and 0 resp. All explicit comparisons return these singletons, e.g. (1==1) is True and (1==0) is False.

New sys-Module Functions

The following functions are installed as add-ons to the builtin sys module.

sys.verbosity([level])

If level is given, the value of the interpreter's verbosity flag is set to level and the previous value of that flag is returned. Otherwise, the current value is returned.

You can use this function to e.g. enable verborse lookup output to stderr for import statements even when the interpreter was not invoked with '-v' or '-vv' switch or to force verbosity to be switched off.

sys.optimization([level])

If level is given, the value of the interpreter's optimization flag is set to level and the previous value of that flag is returned. Otherwise, the current value is returned.

You can use this function to e.g. compile Python scripts in optimized mode even though the interpreter was not started with -O.

sys.cur_frame([offset=0])

Return the current execution frame. If level is given, the returned frame is taken from offset levels up the execution stack. None is returned in case the frame is not found, i.e. there are not enough frames on the stack.

Note: Storing the execution frame in a local variable introduces a circular reference, since the locals and globals are referenced in the execution frame, so use the return value with caution.

Examples of Use

A few simple examples:

import NewBuiltins

sequence = range(100)

# In place calculations:
for i,item in irange(sequence):
    sequence[i] = 2*item

# Get all odd-indexed items from a sequence:
odds = extract(sequence,trange(0,len(sequence),2))

# Turn a tuple of lists into a list of tuples:
chars = 'abcdefghji'
ords = map(ord,chars)
table = tuples(chars,ords)

# The same as dictionary:
chr2ord = dict(table)

# Inverse mapping:
ord2chr = invdict(chr2ord)

# Range checking:
if exists( lambda x: x > 10, sequence ):
    print 'Warning: Big sequence elements!'

# Handle special cases:
if forall( lambda x: x > 0, sequence ):
    print 'Positive sequence'
else:
    print 'Index %i loses' % (index( lambda x: x <= 0, sequence ),)

# dict.get functionality for e.g. lists:
print get(sequence,101,"Don't have an element with index 101")

More elaborate examples can be found in the Examples/ subdirectory of the package.

Package Structure

[NewBuiltins]
       Doc/
       [Examples]
              Acquisition.py
       [mxTools]
              test.py
       NewBuiltins.py
	

Entries enclosed in brackets are packages (i.e. they are directories that include a __init__.py file) or submodules. Ones with slashes are just ordinary subdirectories that are not accessible via import.

Note: Importing NewBuiltins will automatically install the functions and objects defined in this package as builtins. They are then available in all other modules without having to import then again every time. If you don't want this feature, you can turn it off in NewBuiltins/__init__.py.

Installation

Support

Copyright & Disclaimer

History & Future