Step #1 Presence verification of a value in a list
Considering a case when the task is to determine whether a searched value (s) is present in an array (or list) you could cycle through the list elements and verify by equality the presence. If a matching case is reached, the cycle may be stopped and return with positive feedback.
In Python(3) comments that are not part of the code start with # symbol. Here you find examples with integers, but this works for other simple variable types as well.
#initialization of variables
a = [1, 2, 3, 4, 5, 10] #list of integers
s = 4 #searched value
for element in a:
if element == s:
answer = True
return False # if there is no match
this answer may be printed out (on the screen) or better returned if we convert the above script to a function:
def check_presence(a, s):
for element in a:
if element == s:
return True
return False # if there is no match
and call like:
# initialize variables
a = [1, 2, 3, 4, 5, 10] #list of integers
s = 4
# call function with returned value
answer = check_presence(a, s)
Image made from code typed into (Anaconda) Spyder IDE.
Answer may be printed or used for decision in an if structure:
if check_presence(a, s):
#your code here
print('Defined value is present in the list')
Note: in case of a matching situation, the cycle may be terminated earlier than the end of the list. Consequently, the required run time can not be predetermined only the maximum runtime meaning the situation when all elements in the list are verified. Maximum run time is proportional to the number of elements in the list (t ~ n).
Step #2 Absence verification
If the task is to verify the absence of given value, then the code is similar but now the True/False branches of the code are inversed.
def check_absence(a, s):
for element in a:
if element == s:
return False
return True # True, there is no matchNote that it is important to name the function appropriately and define True/False values accordingly. Inappropriate naming and wrong definition may lead to misunderstandings and functional but wrong code (logical/semantic error).
test absence check
Step #3 Absence of list elements in another list
Now, if not only one value should be checked but a list of values then the elements of the list to be verified one-by-one. The function that cycles through elements of s (list) and searches in a (list):
def findMissingElements(a,s):
# elements of s are searched in elements of a
notin_list = [] # predefined empty list
for element in s:
if element not in a:
notin_list.append(element)
return notin_listNow we may test the code with two lists, for example:
#initialization of lists
s = [1, 2, 3, 4, 5, 10] #list elements to check for
a = [2, 3, 1, 0, 5] #list to search in
#calling the function with return value
notin_list = findMissingElements(a,s)
print(notin_list)
This returns a list [4, 10] because 4 and 10 are the numbers present in list s but missing from list a.
test list element absence
We may consider that we are done, but this is not the fastest solution if occasionally a contains repeated values. In such case the following modification should be applied.
Step #4 verifying unique values only
Python has an option to create a list of unique values from a list, that is called a set. It is an inbuilt variable type and conversion has inbuilt module(s), so the process is fast. Conversion is faster then the time we may lose with verifying repeated values.
def findMissingElements(a,s):
# elements of s are searched in elements of a
notin_list = [] # predefined empty list
a_unique = set(a)
for element in s:
if element not in a_unique:
notin_list.append(element)
return notin_listNote: that instead of predefining a_unique could have been replaced in the for cycle as:
if element not in set(a):
...
this is valid code but in such case the list -> set conversion is made at every step of the cycle, so that runtime would be way more than in the #3 case.
test FAST list element absence
