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I want to write a blog post building upon someone else's paper, how can I properly cite/credit them?

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shebang or not shebang



Handling Null values (and equivalents) routinely in Python


Combinatorial searching of Huffman treesHackerRank “Manasa and Stones” in PythonValidation null values (preconditions)Python Octree ImplementationAsk the user for two numbers, then add or multiply themMaximize the number of PyGame sprites, with collision detectionGiven an integer s and a list of integers ints finding (x,y) in ints such that s = x + ySplit list of integers at certain value efficientlyAdvent of Code 2017, Day 8 - Performing simple instructionsTotal of maximum values in all subarrays






.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty margin-bottom:0;








6












$begingroup$


I've found the following code invaluable in helping me 'handle' None values including "whitespace" characters that should be treated as None based on the situation. I have been using this code for quite some time now:



class _MyUtils:

def __init__(self):
pass

def _mynull(self, myval, myalt, mystrip=True, mynullstrings=["", "None"], mynuminstances=(int, float)):
# if the value is None, return the alternative immediately.

if myval is None:
return myalt

# if the value is a number, it is not None - so return the original
elif isinstance(myval, mynuminstances):
return myval

# if the mystrip parameter is true, strip the original and test that
else:
if mystrip:
testval = myval.strip()
else:
testval = myval

# if mynullstrings are populated, check if the upper case of the
# original value matches the upper case of any item in the list.
# return the alternative if so.
if len(mynullstrings) > 0:
i = 0
for ns in mynullstrings:
if ns.upper() == testval.upper():
i = i + 1
break
if i > 0:
return myalt
else:
return myval
else:
return myval


def main():
x = _MyUtils()
print(x._mynull(None, "alternative_value", True, [""]))


if __name__ == '__main__':
main()


The code requires an input, an alternative to provide if input is found to be Null, whether to 'strip' the input during testing (if not a number), values to treat as 'equivalent' to None and types of number instances to determine if the input is numeric (and hence not none).



Essentially, too many processes that we run depend upon not having None values in the data being processed—whether that be lambda functions, custom table toolsets, etc. This code gives me the ability to handle None values predictably, but I am sure there is a better approach here. Is there a more Pythonic way of doing this? How can this code be improved? How would others approach this problem?










share|improve this question











$endgroup$



migrated from stackoverflow.com May 3 at 16:32


This question came from our site for professional and enthusiast programmers.

















  • $begingroup$
    This kind of imprecision is a reason why JavaScript can be so brittle. JavaScript is very liberal in converting values to other types. It's better to be strict about types and the values you allow for them. An unexpected value is a bug; it should not be silently corrected.
    $endgroup$
    – usr
    2 days ago











  • $begingroup$
    The 'fault' lies not with me, but with the dataset I am being provided with for analysis. If that dataset is imperfect, I have only limited choices - I can effectively fix the data at source (using similar code) or create a toolset that works relatively predictably across multiple datasets which was my intention here. Hope that clarifies my issue.
    $endgroup$
    – lb_so
    yesterday






  • 1




    $begingroup$
    I see. I thought this util class was supposed to be used in regular code. As a data import helper this is very useful and totally appropriate. Fix the data as it enters the system.
    $endgroup$
    – usr
    yesterday

















6












$begingroup$


I've found the following code invaluable in helping me 'handle' None values including "whitespace" characters that should be treated as None based on the situation. I have been using this code for quite some time now:



class _MyUtils:

def __init__(self):
pass

def _mynull(self, myval, myalt, mystrip=True, mynullstrings=["", "None"], mynuminstances=(int, float)):
# if the value is None, return the alternative immediately.

if myval is None:
return myalt

# if the value is a number, it is not None - so return the original
elif isinstance(myval, mynuminstances):
return myval

# if the mystrip parameter is true, strip the original and test that
else:
if mystrip:
testval = myval.strip()
else:
testval = myval

# if mynullstrings are populated, check if the upper case of the
# original value matches the upper case of any item in the list.
# return the alternative if so.
if len(mynullstrings) > 0:
i = 0
for ns in mynullstrings:
if ns.upper() == testval.upper():
i = i + 1
break
if i > 0:
return myalt
else:
return myval
else:
return myval


def main():
x = _MyUtils()
print(x._mynull(None, "alternative_value", True, [""]))


if __name__ == '__main__':
main()


The code requires an input, an alternative to provide if input is found to be Null, whether to 'strip' the input during testing (if not a number), values to treat as 'equivalent' to None and types of number instances to determine if the input is numeric (and hence not none).



Essentially, too many processes that we run depend upon not having None values in the data being processed—whether that be lambda functions, custom table toolsets, etc. This code gives me the ability to handle None values predictably, but I am sure there is a better approach here. Is there a more Pythonic way of doing this? How can this code be improved? How would others approach this problem?










share|improve this question











$endgroup$



migrated from stackoverflow.com May 3 at 16:32


This question came from our site for professional and enthusiast programmers.

















  • $begingroup$
    This kind of imprecision is a reason why JavaScript can be so brittle. JavaScript is very liberal in converting values to other types. It's better to be strict about types and the values you allow for them. An unexpected value is a bug; it should not be silently corrected.
    $endgroup$
    – usr
    2 days ago











  • $begingroup$
    The 'fault' lies not with me, but with the dataset I am being provided with for analysis. If that dataset is imperfect, I have only limited choices - I can effectively fix the data at source (using similar code) or create a toolset that works relatively predictably across multiple datasets which was my intention here. Hope that clarifies my issue.
    $endgroup$
    – lb_so
    yesterday






  • 1




    $begingroup$
    I see. I thought this util class was supposed to be used in regular code. As a data import helper this is very useful and totally appropriate. Fix the data as it enters the system.
    $endgroup$
    – usr
    yesterday













6












6








6


1



$begingroup$


I've found the following code invaluable in helping me 'handle' None values including "whitespace" characters that should be treated as None based on the situation. I have been using this code for quite some time now:



class _MyUtils:

def __init__(self):
pass

def _mynull(self, myval, myalt, mystrip=True, mynullstrings=["", "None"], mynuminstances=(int, float)):
# if the value is None, return the alternative immediately.

if myval is None:
return myalt

# if the value is a number, it is not None - so return the original
elif isinstance(myval, mynuminstances):
return myval

# if the mystrip parameter is true, strip the original and test that
else:
if mystrip:
testval = myval.strip()
else:
testval = myval

# if mynullstrings are populated, check if the upper case of the
# original value matches the upper case of any item in the list.
# return the alternative if so.
if len(mynullstrings) > 0:
i = 0
for ns in mynullstrings:
if ns.upper() == testval.upper():
i = i + 1
break
if i > 0:
return myalt
else:
return myval
else:
return myval


def main():
x = _MyUtils()
print(x._mynull(None, "alternative_value", True, [""]))


if __name__ == '__main__':
main()


The code requires an input, an alternative to provide if input is found to be Null, whether to 'strip' the input during testing (if not a number), values to treat as 'equivalent' to None and types of number instances to determine if the input is numeric (and hence not none).



Essentially, too many processes that we run depend upon not having None values in the data being processed—whether that be lambda functions, custom table toolsets, etc. This code gives me the ability to handle None values predictably, but I am sure there is a better approach here. Is there a more Pythonic way of doing this? How can this code be improved? How would others approach this problem?










share|improve this question











$endgroup$




I've found the following code invaluable in helping me 'handle' None values including "whitespace" characters that should be treated as None based on the situation. I have been using this code for quite some time now:



class _MyUtils:

def __init__(self):
pass

def _mynull(self, myval, myalt, mystrip=True, mynullstrings=["", "None"], mynuminstances=(int, float)):
# if the value is None, return the alternative immediately.

if myval is None:
return myalt

# if the value is a number, it is not None - so return the original
elif isinstance(myval, mynuminstances):
return myval

# if the mystrip parameter is true, strip the original and test that
else:
if mystrip:
testval = myval.strip()
else:
testval = myval

# if mynullstrings are populated, check if the upper case of the
# original value matches the upper case of any item in the list.
# return the alternative if so.
if len(mynullstrings) > 0:
i = 0
for ns in mynullstrings:
if ns.upper() == testval.upper():
i = i + 1
break
if i > 0:
return myalt
else:
return myval
else:
return myval


def main():
x = _MyUtils()
print(x._mynull(None, "alternative_value", True, [""]))


if __name__ == '__main__':
main()


The code requires an input, an alternative to provide if input is found to be Null, whether to 'strip' the input during testing (if not a number), values to treat as 'equivalent' to None and types of number instances to determine if the input is numeric (and hence not none).



Essentially, too many processes that we run depend upon not having None values in the data being processed—whether that be lambda functions, custom table toolsets, etc. This code gives me the ability to handle None values predictably, but I am sure there is a better approach here. Is there a more Pythonic way of doing this? How can this code be improved? How would others approach this problem?







python null






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited May 3 at 17:46









200_success

132k20159424




132k20159424










asked May 3 at 13:02









lb_solb_so

312




312




migrated from stackoverflow.com May 3 at 16:32


This question came from our site for professional and enthusiast programmers.









migrated from stackoverflow.com May 3 at 16:32


This question came from our site for professional and enthusiast programmers.













  • $begingroup$
    This kind of imprecision is a reason why JavaScript can be so brittle. JavaScript is very liberal in converting values to other types. It's better to be strict about types and the values you allow for them. An unexpected value is a bug; it should not be silently corrected.
    $endgroup$
    – usr
    2 days ago











  • $begingroup$
    The 'fault' lies not with me, but with the dataset I am being provided with for analysis. If that dataset is imperfect, I have only limited choices - I can effectively fix the data at source (using similar code) or create a toolset that works relatively predictably across multiple datasets which was my intention here. Hope that clarifies my issue.
    $endgroup$
    – lb_so
    yesterday






  • 1




    $begingroup$
    I see. I thought this util class was supposed to be used in regular code. As a data import helper this is very useful and totally appropriate. Fix the data as it enters the system.
    $endgroup$
    – usr
    yesterday
















  • $begingroup$
    This kind of imprecision is a reason why JavaScript can be so brittle. JavaScript is very liberal in converting values to other types. It's better to be strict about types and the values you allow for them. An unexpected value is a bug; it should not be silently corrected.
    $endgroup$
    – usr
    2 days ago











  • $begingroup$
    The 'fault' lies not with me, but with the dataset I am being provided with for analysis. If that dataset is imperfect, I have only limited choices - I can effectively fix the data at source (using similar code) or create a toolset that works relatively predictably across multiple datasets which was my intention here. Hope that clarifies my issue.
    $endgroup$
    – lb_so
    yesterday






  • 1




    $begingroup$
    I see. I thought this util class was supposed to be used in regular code. As a data import helper this is very useful and totally appropriate. Fix the data as it enters the system.
    $endgroup$
    – usr
    yesterday















$begingroup$
This kind of imprecision is a reason why JavaScript can be so brittle. JavaScript is very liberal in converting values to other types. It's better to be strict about types and the values you allow for them. An unexpected value is a bug; it should not be silently corrected.
$endgroup$
– usr
2 days ago





$begingroup$
This kind of imprecision is a reason why JavaScript can be so brittle. JavaScript is very liberal in converting values to other types. It's better to be strict about types and the values you allow for them. An unexpected value is a bug; it should not be silently corrected.
$endgroup$
– usr
2 days ago













$begingroup$
The 'fault' lies not with me, but with the dataset I am being provided with for analysis. If that dataset is imperfect, I have only limited choices - I can effectively fix the data at source (using similar code) or create a toolset that works relatively predictably across multiple datasets which was my intention here. Hope that clarifies my issue.
$endgroup$
– lb_so
yesterday




$begingroup$
The 'fault' lies not with me, but with the dataset I am being provided with for analysis. If that dataset is imperfect, I have only limited choices - I can effectively fix the data at source (using similar code) or create a toolset that works relatively predictably across multiple datasets which was my intention here. Hope that clarifies my issue.
$endgroup$
– lb_so
yesterday




1




1




$begingroup$
I see. I thought this util class was supposed to be used in regular code. As a data import helper this is very useful and totally appropriate. Fix the data as it enters the system.
$endgroup$
– usr
yesterday




$begingroup$
I see. I thought this util class was supposed to be used in regular code. As a data import helper this is very useful and totally appropriate. Fix the data as it enters the system.
$endgroup$
– usr
yesterday










4 Answers
4






active

oldest

votes


















6












$begingroup$

Generally I don't think you should have a class for this functionality. There's no state and no particular meaning to MyUtils object here. You can make this into a long function in whatever module you deem appropriate in your codebase.



I think this function as written is a code smell. It 1) doesn't cover a whole lot of types and 2) implies that where you're using it you're not going to have even a rough idea of what type of data you're expecting. In most cases you will have some idea, and even then it's not usually a good idea to do explicit type checking.



Where you're using this for numbers you can replace it with myval if myval is not None else mydefault.



A function like this may be more useful for strings, for which there are a wider range of essentially empty values. Perhaps something like this



def safe_string(s, default="", blacklist=["None"]):
if s is None or len(s.strip()) == 0:
return default
if s.upper() in [b.upper() for b in blacklist]:
return default
return s





share|improve this answer









$endgroup$












  • $begingroup$
    agreed on the Class statement, thank you.
    $endgroup$
    – lb_so
    yesterday


















5












$begingroup$

Apart from the "blacklist" feature, you can in many cases just use or to use a "default" value if the first argument is falsy. Some example:



>>> "foo" or "default"
'foo'
>>> "" or "default"
'default'
>>> None or "default"
'default'


And similar for numbers, lists, etc.



for x in list_that_could_be_none or []:
print(x * (number_that_could_be_none or 0))


But note that any non-empty string is truthy (but you can still strip):



>>> " " or "default"
' '
>>> " ".strip() or "default"
'default'





share|improve this answer









$endgroup$




















    4












    $begingroup$

    This loop could be rewritten:



     if len(mynullstrings) > 0:
    i = 0
    for ns in mynullstrings:
    if ns.upper() == testval.upper():
    i = i + 1
    break
    if i > 0:
    return myalt
    else:
    return myval
    else:
    return myval


    as:



     if testval.upper() in [ns.upper() for ns in mynullstrings]:
    return myalt
    else:
    return myval


    I would also rewrite this:



     if mystrip:
    testval = myval.strip()
    else:
    testval = myval


    as:



     if mystrip:
    myval= myval.strip()


    and continue to use myval. This seems clearer to me.



    Personally, I don't think prepending 'my' is a good style—variable names should be descriptive in and of themselves.






    share|improve this answer











    $endgroup$








    • 2




      $begingroup$
      also note that str.casefold() is recommended for comparing strings. see for example stackoverflow.com/q/45745661/1358308 and stackoverflow.com/q/40348174/1358308
      $endgroup$
      – Sam Mason
      May 3 at 16:46










    • $begingroup$
      I really like how you have crushed my multi-line loops into a far more pythonic version here. Thank you.
      $endgroup$
      – lb_so
      yesterday


















    3












    $begingroup$

    further to everything else that's been written I find it's generally better for functions to raise an exception if the wrong data-type is propagated, I'd therefore discourage use of code that special cases things like your checking for ints and floats. I'd write the function as:



    def replace_null(text, *, empty_is_null=True, strip=True, nulls=('NULL', 'None')):
    """Return None if text represents 'none', otherwise text with whitespace stripped."""
    if text is None:
    return None
    if strip:
    text = str.strip(text)
    if empty_is_null and not text:
    return None
    if str.casefold(text) in (s.casefold() for s in nulls):
    return None
    return text


    The asterisk (*) indicates keyword-only arguments (see PEP 3102) as I think it would help with future readers of the code. For example I would probably have to look at the definition to determine what:



    x = myobj._mynull(text, 'default', False)


    does, especially the unqualified False, when compared to (assuming the above is saved in utils.py):



    x = utils.replace_null(text, strip=False) or 'default'


    which relies more on keyword arguments and standard Python semantics.



    I've also added a small docstring, so that help(replace_null) works.






    share|improve this answer








    New contributor



    Sam Mason is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.





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      4 Answers
      4






      active

      oldest

      votes








      4 Answers
      4






      active

      oldest

      votes









      active

      oldest

      votes






      active

      oldest

      votes









      6












      $begingroup$

      Generally I don't think you should have a class for this functionality. There's no state and no particular meaning to MyUtils object here. You can make this into a long function in whatever module you deem appropriate in your codebase.



      I think this function as written is a code smell. It 1) doesn't cover a whole lot of types and 2) implies that where you're using it you're not going to have even a rough idea of what type of data you're expecting. In most cases you will have some idea, and even then it's not usually a good idea to do explicit type checking.



      Where you're using this for numbers you can replace it with myval if myval is not None else mydefault.



      A function like this may be more useful for strings, for which there are a wider range of essentially empty values. Perhaps something like this



      def safe_string(s, default="", blacklist=["None"]):
      if s is None or len(s.strip()) == 0:
      return default
      if s.upper() in [b.upper() for b in blacklist]:
      return default
      return s





      share|improve this answer









      $endgroup$












      • $begingroup$
        agreed on the Class statement, thank you.
        $endgroup$
        – lb_so
        yesterday















      6












      $begingroup$

      Generally I don't think you should have a class for this functionality. There's no state and no particular meaning to MyUtils object here. You can make this into a long function in whatever module you deem appropriate in your codebase.



      I think this function as written is a code smell. It 1) doesn't cover a whole lot of types and 2) implies that where you're using it you're not going to have even a rough idea of what type of data you're expecting. In most cases you will have some idea, and even then it's not usually a good idea to do explicit type checking.



      Where you're using this for numbers you can replace it with myval if myval is not None else mydefault.



      A function like this may be more useful for strings, for which there are a wider range of essentially empty values. Perhaps something like this



      def safe_string(s, default="", blacklist=["None"]):
      if s is None or len(s.strip()) == 0:
      return default
      if s.upper() in [b.upper() for b in blacklist]:
      return default
      return s





      share|improve this answer









      $endgroup$












      • $begingroup$
        agreed on the Class statement, thank you.
        $endgroup$
        – lb_so
        yesterday













      6












      6








      6





      $begingroup$

      Generally I don't think you should have a class for this functionality. There's no state and no particular meaning to MyUtils object here. You can make this into a long function in whatever module you deem appropriate in your codebase.



      I think this function as written is a code smell. It 1) doesn't cover a whole lot of types and 2) implies that where you're using it you're not going to have even a rough idea of what type of data you're expecting. In most cases you will have some idea, and even then it's not usually a good idea to do explicit type checking.



      Where you're using this for numbers you can replace it with myval if myval is not None else mydefault.



      A function like this may be more useful for strings, for which there are a wider range of essentially empty values. Perhaps something like this



      def safe_string(s, default="", blacklist=["None"]):
      if s is None or len(s.strip()) == 0:
      return default
      if s.upper() in [b.upper() for b in blacklist]:
      return default
      return s





      share|improve this answer









      $endgroup$



      Generally I don't think you should have a class for this functionality. There's no state and no particular meaning to MyUtils object here. You can make this into a long function in whatever module you deem appropriate in your codebase.



      I think this function as written is a code smell. It 1) doesn't cover a whole lot of types and 2) implies that where you're using it you're not going to have even a rough idea of what type of data you're expecting. In most cases you will have some idea, and even then it's not usually a good idea to do explicit type checking.



      Where you're using this for numbers you can replace it with myval if myval is not None else mydefault.



      A function like this may be more useful for strings, for which there are a wider range of essentially empty values. Perhaps something like this



      def safe_string(s, default="", blacklist=["None"]):
      if s is None or len(s.strip()) == 0:
      return default
      if s.upper() in [b.upper() for b in blacklist]:
      return default
      return s






      share|improve this answer












      share|improve this answer



      share|improve this answer










      answered May 3 at 13:32









      Quinn MortimerQuinn Mortimer

      1694




      1694











      • $begingroup$
        agreed on the Class statement, thank you.
        $endgroup$
        – lb_so
        yesterday
















      • $begingroup$
        agreed on the Class statement, thank you.
        $endgroup$
        – lb_so
        yesterday















      $begingroup$
      agreed on the Class statement, thank you.
      $endgroup$
      – lb_so
      yesterday




      $begingroup$
      agreed on the Class statement, thank you.
      $endgroup$
      – lb_so
      yesterday













      5












      $begingroup$

      Apart from the "blacklist" feature, you can in many cases just use or to use a "default" value if the first argument is falsy. Some example:



      >>> "foo" or "default"
      'foo'
      >>> "" or "default"
      'default'
      >>> None or "default"
      'default'


      And similar for numbers, lists, etc.



      for x in list_that_could_be_none or []:
      print(x * (number_that_could_be_none or 0))


      But note that any non-empty string is truthy (but you can still strip):



      >>> " " or "default"
      ' '
      >>> " ".strip() or "default"
      'default'





      share|improve this answer









      $endgroup$

















        5












        $begingroup$

        Apart from the "blacklist" feature, you can in many cases just use or to use a "default" value if the first argument is falsy. Some example:



        >>> "foo" or "default"
        'foo'
        >>> "" or "default"
        'default'
        >>> None or "default"
        'default'


        And similar for numbers, lists, etc.



        for x in list_that_could_be_none or []:
        print(x * (number_that_could_be_none or 0))


        But note that any non-empty string is truthy (but you can still strip):



        >>> " " or "default"
        ' '
        >>> " ".strip() or "default"
        'default'





        share|improve this answer









        $endgroup$















          5












          5








          5





          $begingroup$

          Apart from the "blacklist" feature, you can in many cases just use or to use a "default" value if the first argument is falsy. Some example:



          >>> "foo" or "default"
          'foo'
          >>> "" or "default"
          'default'
          >>> None or "default"
          'default'


          And similar for numbers, lists, etc.



          for x in list_that_could_be_none or []:
          print(x * (number_that_could_be_none or 0))


          But note that any non-empty string is truthy (but you can still strip):



          >>> " " or "default"
          ' '
          >>> " ".strip() or "default"
          'default'





          share|improve this answer









          $endgroup$



          Apart from the "blacklist" feature, you can in many cases just use or to use a "default" value if the first argument is falsy. Some example:



          >>> "foo" or "default"
          'foo'
          >>> "" or "default"
          'default'
          >>> None or "default"
          'default'


          And similar for numbers, lists, etc.



          for x in list_that_could_be_none or []:
          print(x * (number_that_could_be_none or 0))


          But note that any non-empty string is truthy (but you can still strip):



          >>> " " or "default"
          ' '
          >>> " ".strip() or "default"
          'default'






          share|improve this answer












          share|improve this answer



          share|improve this answer










          answered May 3 at 13:37









          tobias_ktobias_k

          1,579916




          1,579916





















              4












              $begingroup$

              This loop could be rewritten:



               if len(mynullstrings) > 0:
              i = 0
              for ns in mynullstrings:
              if ns.upper() == testval.upper():
              i = i + 1
              break
              if i > 0:
              return myalt
              else:
              return myval
              else:
              return myval


              as:



               if testval.upper() in [ns.upper() for ns in mynullstrings]:
              return myalt
              else:
              return myval


              I would also rewrite this:



               if mystrip:
              testval = myval.strip()
              else:
              testval = myval


              as:



               if mystrip:
              myval= myval.strip()


              and continue to use myval. This seems clearer to me.



              Personally, I don't think prepending 'my' is a good style—variable names should be descriptive in and of themselves.






              share|improve this answer











              $endgroup$








              • 2




                $begingroup$
                also note that str.casefold() is recommended for comparing strings. see for example stackoverflow.com/q/45745661/1358308 and stackoverflow.com/q/40348174/1358308
                $endgroup$
                – Sam Mason
                May 3 at 16:46










              • $begingroup$
                I really like how you have crushed my multi-line loops into a far more pythonic version here. Thank you.
                $endgroup$
                – lb_so
                yesterday















              4












              $begingroup$

              This loop could be rewritten:



               if len(mynullstrings) > 0:
              i = 0
              for ns in mynullstrings:
              if ns.upper() == testval.upper():
              i = i + 1
              break
              if i > 0:
              return myalt
              else:
              return myval
              else:
              return myval


              as:



               if testval.upper() in [ns.upper() for ns in mynullstrings]:
              return myalt
              else:
              return myval


              I would also rewrite this:



               if mystrip:
              testval = myval.strip()
              else:
              testval = myval


              as:



               if mystrip:
              myval= myval.strip()


              and continue to use myval. This seems clearer to me.



              Personally, I don't think prepending 'my' is a good style—variable names should be descriptive in and of themselves.






              share|improve this answer











              $endgroup$








              • 2




                $begingroup$
                also note that str.casefold() is recommended for comparing strings. see for example stackoverflow.com/q/45745661/1358308 and stackoverflow.com/q/40348174/1358308
                $endgroup$
                – Sam Mason
                May 3 at 16:46










              • $begingroup$
                I really like how you have crushed my multi-line loops into a far more pythonic version here. Thank you.
                $endgroup$
                – lb_so
                yesterday













              4












              4








              4





              $begingroup$

              This loop could be rewritten:



               if len(mynullstrings) > 0:
              i = 0
              for ns in mynullstrings:
              if ns.upper() == testval.upper():
              i = i + 1
              break
              if i > 0:
              return myalt
              else:
              return myval
              else:
              return myval


              as:



               if testval.upper() in [ns.upper() for ns in mynullstrings]:
              return myalt
              else:
              return myval


              I would also rewrite this:



               if mystrip:
              testval = myval.strip()
              else:
              testval = myval


              as:



               if mystrip:
              myval= myval.strip()


              and continue to use myval. This seems clearer to me.



              Personally, I don't think prepending 'my' is a good style—variable names should be descriptive in and of themselves.






              share|improve this answer











              $endgroup$



              This loop could be rewritten:



               if len(mynullstrings) > 0:
              i = 0
              for ns in mynullstrings:
              if ns.upper() == testval.upper():
              i = i + 1
              break
              if i > 0:
              return myalt
              else:
              return myval
              else:
              return myval


              as:



               if testval.upper() in [ns.upper() for ns in mynullstrings]:
              return myalt
              else:
              return myval


              I would also rewrite this:



               if mystrip:
              testval = myval.strip()
              else:
              testval = myval


              as:



               if mystrip:
              myval= myval.strip()


              and continue to use myval. This seems clearer to me.



              Personally, I don't think prepending 'my' is a good style—variable names should be descriptive in and of themselves.







              share|improve this answer














              share|improve this answer



              share|improve this answer








              edited May 3 at 16:33









              Cody Gray

              3,490926




              3,490926










              answered May 3 at 13:16









              lolopoplolopop

              29416




              29416







              • 2




                $begingroup$
                also note that str.casefold() is recommended for comparing strings. see for example stackoverflow.com/q/45745661/1358308 and stackoverflow.com/q/40348174/1358308
                $endgroup$
                – Sam Mason
                May 3 at 16:46










              • $begingroup$
                I really like how you have crushed my multi-line loops into a far more pythonic version here. Thank you.
                $endgroup$
                – lb_so
                yesterday












              • 2




                $begingroup$
                also note that str.casefold() is recommended for comparing strings. see for example stackoverflow.com/q/45745661/1358308 and stackoverflow.com/q/40348174/1358308
                $endgroup$
                – Sam Mason
                May 3 at 16:46










              • $begingroup$
                I really like how you have crushed my multi-line loops into a far more pythonic version here. Thank you.
                $endgroup$
                – lb_so
                yesterday







              2




              2




              $begingroup$
              also note that str.casefold() is recommended for comparing strings. see for example stackoverflow.com/q/45745661/1358308 and stackoverflow.com/q/40348174/1358308
              $endgroup$
              – Sam Mason
              May 3 at 16:46




              $begingroup$
              also note that str.casefold() is recommended for comparing strings. see for example stackoverflow.com/q/45745661/1358308 and stackoverflow.com/q/40348174/1358308
              $endgroup$
              – Sam Mason
              May 3 at 16:46












              $begingroup$
              I really like how you have crushed my multi-line loops into a far more pythonic version here. Thank you.
              $endgroup$
              – lb_so
              yesterday




              $begingroup$
              I really like how you have crushed my multi-line loops into a far more pythonic version here. Thank you.
              $endgroup$
              – lb_so
              yesterday











              3












              $begingroup$

              further to everything else that's been written I find it's generally better for functions to raise an exception if the wrong data-type is propagated, I'd therefore discourage use of code that special cases things like your checking for ints and floats. I'd write the function as:



              def replace_null(text, *, empty_is_null=True, strip=True, nulls=('NULL', 'None')):
              """Return None if text represents 'none', otherwise text with whitespace stripped."""
              if text is None:
              return None
              if strip:
              text = str.strip(text)
              if empty_is_null and not text:
              return None
              if str.casefold(text) in (s.casefold() for s in nulls):
              return None
              return text


              The asterisk (*) indicates keyword-only arguments (see PEP 3102) as I think it would help with future readers of the code. For example I would probably have to look at the definition to determine what:



              x = myobj._mynull(text, 'default', False)


              does, especially the unqualified False, when compared to (assuming the above is saved in utils.py):



              x = utils.replace_null(text, strip=False) or 'default'


              which relies more on keyword arguments and standard Python semantics.



              I've also added a small docstring, so that help(replace_null) works.






              share|improve this answer








              New contributor



              Sam Mason is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
              Check out our Code of Conduct.





              $endgroup$

















                3












                $begingroup$

                further to everything else that's been written I find it's generally better for functions to raise an exception if the wrong data-type is propagated, I'd therefore discourage use of code that special cases things like your checking for ints and floats. I'd write the function as:



                def replace_null(text, *, empty_is_null=True, strip=True, nulls=('NULL', 'None')):
                """Return None if text represents 'none', otherwise text with whitespace stripped."""
                if text is None:
                return None
                if strip:
                text = str.strip(text)
                if empty_is_null and not text:
                return None
                if str.casefold(text) in (s.casefold() for s in nulls):
                return None
                return text


                The asterisk (*) indicates keyword-only arguments (see PEP 3102) as I think it would help with future readers of the code. For example I would probably have to look at the definition to determine what:



                x = myobj._mynull(text, 'default', False)


                does, especially the unqualified False, when compared to (assuming the above is saved in utils.py):



                x = utils.replace_null(text, strip=False) or 'default'


                which relies more on keyword arguments and standard Python semantics.



                I've also added a small docstring, so that help(replace_null) works.






                share|improve this answer








                New contributor



                Sam Mason is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                Check out our Code of Conduct.





                $endgroup$















                  3












                  3








                  3





                  $begingroup$

                  further to everything else that's been written I find it's generally better for functions to raise an exception if the wrong data-type is propagated, I'd therefore discourage use of code that special cases things like your checking for ints and floats. I'd write the function as:



                  def replace_null(text, *, empty_is_null=True, strip=True, nulls=('NULL', 'None')):
                  """Return None if text represents 'none', otherwise text with whitespace stripped."""
                  if text is None:
                  return None
                  if strip:
                  text = str.strip(text)
                  if empty_is_null and not text:
                  return None
                  if str.casefold(text) in (s.casefold() for s in nulls):
                  return None
                  return text


                  The asterisk (*) indicates keyword-only arguments (see PEP 3102) as I think it would help with future readers of the code. For example I would probably have to look at the definition to determine what:



                  x = myobj._mynull(text, 'default', False)


                  does, especially the unqualified False, when compared to (assuming the above is saved in utils.py):



                  x = utils.replace_null(text, strip=False) or 'default'


                  which relies more on keyword arguments and standard Python semantics.



                  I've also added a small docstring, so that help(replace_null) works.






                  share|improve this answer








                  New contributor



                  Sam Mason is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                  Check out our Code of Conduct.





                  $endgroup$



                  further to everything else that's been written I find it's generally better for functions to raise an exception if the wrong data-type is propagated, I'd therefore discourage use of code that special cases things like your checking for ints and floats. I'd write the function as:



                  def replace_null(text, *, empty_is_null=True, strip=True, nulls=('NULL', 'None')):
                  """Return None if text represents 'none', otherwise text with whitespace stripped."""
                  if text is None:
                  return None
                  if strip:
                  text = str.strip(text)
                  if empty_is_null and not text:
                  return None
                  if str.casefold(text) in (s.casefold() for s in nulls):
                  return None
                  return text


                  The asterisk (*) indicates keyword-only arguments (see PEP 3102) as I think it would help with future readers of the code. For example I would probably have to look at the definition to determine what:



                  x = myobj._mynull(text, 'default', False)


                  does, especially the unqualified False, when compared to (assuming the above is saved in utils.py):



                  x = utils.replace_null(text, strip=False) or 'default'


                  which relies more on keyword arguments and standard Python semantics.



                  I've also added a small docstring, so that help(replace_null) works.







                  share|improve this answer








                  New contributor



                  Sam Mason is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                  Check out our Code of Conduct.








                  share|improve this answer



                  share|improve this answer






                  New contributor



                  Sam Mason is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                  Check out our Code of Conduct.








                  answered May 3 at 18:09









                  Sam MasonSam Mason

                  1313




                  1313




                  New contributor



                  Sam Mason is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                  Check out our Code of Conduct.




                  New contributor




                  Sam Mason is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                  Check out our Code of Conduct.





























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