enhaaancedLists 0.90

(Thread-safe) list(s) with extended / enhanced in-place capabilities (e.g. conditional element selection)

The 'EnhaaancedLists' library provides list classes with automatic locking mechanisms (multithreading/processing safe-ty), extended / enhanced in-place capabilities and/or automatic type checking mechanisms (for list elements).

Together with the 'elem' term / alias (comprised too), some of their methods (also) allow using a new operator notation for selecting list elements - closely resembling mathematical conditions.

The following just is a brief summary of the main elements - the full documentation is available by either the command line option '--info':

		python enhaaancedLists.py --info

or the python command 'help' (displaying the doc-string of the module):

		import enhaaancedLists
		help(enhaaancedLists)

EnhList

Examples for additional capabilities (the standard list operations work too) are:

( Note that the '&' resp. the '|' are 'abused' as 'logical and resp. logical or' in this context (and not 'bitwise'!) ).

		#import class and aliases used
		from enhaaancedLists import EnhList, elem, single, several

		#convert a parameter list to an enhanced list 
		eL = EnhList(1,3,5,7)                                       #eL: [1,3,5,7]
		
		#push single as well as multiple elements into the list
		eL.push(9)                                  #==> None       #eL: [1,3,5,7,9]
		eL.push(11,13,15)                           #==> None       #eL: [1,3,5,7,9,11,13,15]
		
		#pop - note that push/pop implements a FIFO - in contrast to the standard list
		eL.pop()                                    #==> 1          #eL: [3,5,7,9,11,13,15]
		eL.pop( (elem > 3) & (elem < 11), single )  #==> 5          #eL: [3,7,9,11,13,15]
		eL.pop( (elem > 3) & (elem < 11)         )  #==> [7,9]      #eL: [3,11,13,15]
		
		#extend the list
		eL.extend( [7,8,9] )                        #==> None       #eL: [3,11,13,15,7,8,9]
		eL.extend( [4,5,6], reverse=True )          #==> None       #eL: [4,5,6,3,11,13,15,7,8,9]
		
		#get items from list
		eL[ elem >= 10         ]                    #==> [11,13,15] #eL: unchanged
		eL[ elem >= 10, single ]                    #==> 11         #eL: unchanged
		eL[ elem <  3,  single ]                    #==> None       #eL: unchanged
		
		#check whether list contains items
		( elem <  3 ) in eL                         #==> False      #eL: unchanged
		( elem >= 3 ) in eL                         #==> True       #eL: unchanged
		
		#set items in list                                          
		eL = EnhList(4,5,6,3,11,13,15,7,8,9)                        #eL: [4,5,6,3,11,13,15,7,8,9]
		eL[ elem % 2 == 1]              = elem // 2 #==> None       #eL: [4,2,6,1,5,6,7,3,8,4]
		eL[ (elem == 6) | (elem == 8) ] = 0         #==> None       #eL: [4,2,0,1,5,0,7,3,0,4]
		
		#delete items from list
		eL = EnhList(4,5,6,3,11,13,15,7,8,9)                        #eL: [4,5,6,3,11,13,15,7,8,9]
		del eL[ elem < 12, single ]                 #==> ---        #eL: [5,6,3,11,13,15,7,8,9]
		del eL[ elem > 12         ]                 #==> ---        #eL: [5,6,3,11,7,8,9]
		
		eL = EnhList(1,3,5,7)                                       #eL: [1,3,5,7]
		#check whether all elements meet a condition
		eL.areAll( elem % 2 == 1 )                  #==> True
		eL.areAll( elem     >= 3 )                  #==> False
		
		#map function on elements / work with items of elements
		#map replaces elements, which are mapped, by the mapping result
		eL.mapIf( lambda x: dict(a=x) )	                            #==> None	#eL: [{'a':1},{'a':3},{'a':5},{'a':7}]
		eL.mapIf( lambda x: x['a'] + 1, elem['a'] > 3)              #==> None	#eL: [{'a':1},{'a':3},6,8]
			
		#apply map function on elements / work on items of elements                                          
		#apply map does not replace elements; it modifies elements, which are apply mapped, instead
		eL = EnhList([3],[5],[7])												#eL: [[3],[5],[7]]
		eL.applyMapIf( lambda x: list.append(x, 22) )              	#==> None	#eL: [[3,22],[5,22],[7,22]]
		eL.applyMapIf( lambda x: list.append(x, 33), elem[0] > 4 ) 	#==> None	#eL: [[3,22],[5,22,33],[7,22,33]]
		
		#get min, max, avg, median or sum of a selected property
		eL = EnhList([3,8],[5,6],[7,4])                             #eL: [[3,8],[5,6],[7,4]]
		eL.min(    elem[0] )                        #==> 3          #eL: [[3,8],[5,6],[7,4]]
		eL.max(    elem[1] )                        #==> 8          #eL: [[3,8],[5,6],[7,4]]
		eL.avg(    elem[0] )                        #==> 5.0        #eL: [[3,8],[5,6],[7,4]]
		eL.median( elem[1] )                        #==> 6.0        #eL: [[3,8],[5,6],[7,4]]
		eL.sum(    elem[0] )                        #==> 15         #eL: [[3,8],[5,6],[7,4]]
		
		#work with attributes of elements
		eL = EnhList([{'a':1},{'a':3},6,8])                         #eL: [{'a':1},{'a':3},6,8]
		class Attr(object):
					def __init__(self, value):
							self.a = value
					def __repr__(self):
							return ".a=%s" % self.a
		eL.mapIf( lambda x: Attr(x), lambda x: type(x) ==  int ) 
													#==> None       #eL: [{'a':1},{'a':3},.a=6,.a=8]
																								
		#create a list, whose elements just can be of given types (a typed list)
		eL = EnhList(1,3,5,7, elemTypesT=(int, float))              #eL: [1,3,5,7]
		eL.append(1.23)                             #==> None       #eL: [1,3,5,7,1.23]
		eL.append("a")                              #==> TypeMismatch exception
		
		#for the aforementioned use case, there also are some premade typed lists
		eL = NumberList(1,3,5,7)                                    #eL: [1,3,5,7]
		eL.append(1.23)                             #==> None       #eL: [1,3,5,7,1.23]
		eL.append("a")                              #==> TypeMismatch exception

Premade typed list classes inherited from EnhList are:

• DecimalList
• DictList
• FloatList
• IntList
• ListList
• LupleList (elements can be of type list or tuple)
• NumberList (lements can be of type int, float and decimal.Decimal)
• SetList
• StrList
• TupleList

SecList

The 'SecList' class is a secured version of the enhanced list class 'EnhList'.

Access to its elements has been made 'thread-safe' by wrapping the belonging methods in a 'with' context automatically 'acquiring' / 'releasing' an internal 'Semi/BlockingMutex' (a multithreading / multiprocessing lock).

Examples:

    #import class
    from enhaaancedLists import SecList, elem

    #convert a parameter list into a secured list 
    sL = SecList(1,2,3,4,5,6,7,8)
   
    #if then a first thread e.g. would run the following statement:
    evenL = sL.pop( elem % 2 == 0 )
   
    #and a second thread in parallel (!!) e.g. would run the following statement:
    oddL = sL.pop( elem % 2 == 1 )
   
    #the parallel access to said list would not result in a collission resp.
    #error and the result would be:
    #evenL <==> [2,4,6,8]
    #oddL  <==> [1,3,5,7]
    #sL    <==> [] 

Premade typed list classes inherited from SecList are:

• DecimalSecList
• DictSecList
• FloatSecList
• IntSecList
• ListSecList
• LupleSecList (elements can be of type list or tuple)
• NumberSecList (elements can be of type int, float and decimal.Decimal)
• SetSecList
• StrSecList
• TupleSecList

Further Informations

Detailed descriptions can be found in the doc/help-texts of the module and its classes and their methods. E.g. try:

    python -i
    import enhaaancedLists
    help(enhaaancedLists)

    from enhaaancedLists import EnhList, SecList, elem
    help(EnhList)
    help(SecList)
    help(elem)

or

    python enhaaancedLists.py --info
    python enhaaancedLists.py --test

More examples can be found in the source code of the selftest() function of the "enhaaancedList.py" library module and the methods called from there.

Further infomations and links can be found on my homepage

https://www.blackward.de

Have Fun!