performance - Python Coding Style Dilemma -
there several known python code style rules, considered default , try adhere:
wrap lines don’t exceed 79 characters.
keep indents 4 spaces long.
another common programming advice is
avoid global variables
in other words, 1 should use functions accept variables parameters , avoid pascal-like procedures read directly higher scope.
however, in cases, 1 should break of these rules. example, if functions long parameters lists involved. there 2 separate issues them:
first, in heavily indented blocks there little room left.
def function(variable1, variable2, variable3, variable4, variable5,\ variable6, variable7, variable8, variable9): return variable1 + variable2 + variable3 + variable4 + variable5 +\ variable6 + variable7 + variable8 + variable9 def... variable1... if variable 2... while variable3... if variable4... variable5... ... variable10 =\ function(\ variable1,\ variable2,\ variable3,\ variable4,\ variable5,\ variable6,\ variable7,\ variable8,\ variable9) ... here procedure closure, though considered bad practice, can become helpful:
def... def procedure(): variable10 = variable1 + variable2 + variable3 + variable4 +\ variable5 + variable6 + variable7 + variable8 + variable9 variable1... if variable 2... while variable3... if variable4... variable5... ... procedure() ... another issue (which python-specific) performance. copying of function parameters can become quite costly if there lot of them:
import time var1 = 1 var2 = 2 var3 = 3 var4 = 4 var5 = 5 var6 = 6 def function(var1, var2, var3, var4, var5, var6): pass def procedure(): pass starttime = time.time() in range(10000000): function(var1, var2, var3, var4, var5, var6) finishtime = time.time() print('classical function runtime: {:.3f} s'.format(finishtime - starttime)) starttime = time.time() in range(10000000): procedure() finishtime = time.time() print('procedure runtime: {:.3f} s'.format(finishtime - start time)) this outputs:
classical function runtime: 2.447 s procedure runtime: 1.180 s therefore, question, directed experienced developers, is:
is there can justify use of pascal-like procedures on classical functions or should avoided @ cost, if lead bulkier , slower code?
edit:
using *args , **kwargs solves issue partially, parameters still have listed during function call. not address performance issue, parameters still getting copied. itertools, proposed in comments, not applicable. in cases, resolving nesting quite tricky (consider code below) , take lot of developing time, leading tangled code.
def my_function(**kwargs): open(kwargs['file_a'], 'r') input1: line1 in input1: if kwargs['number'] % 3 == 0: if kwargs['number'] % 9 == 0: open(kwargs['file_0'], 'r') input2: line2 in input2: if line1.startswith('#'): if line2.startswith('a'): open('output.txt') output1: item in kwargs['items']: if item in kwargs['good']: sub in item: if sub < 0: result = process_vars( kwargs['var1'], kwargs['var2'], kwargs['var3'], kwargs['var4'], kwargs['var5'], kwargs['var6'], kwargs['var7'], kwargs['var8'], kwargs['var9'], kwargs['var10']) output1.write(result) elif sub >= 0 , sub < 1: output1.write('hello') else: output1.write('byebye') elif len(item) > 20: item = item[: 20] else: output1.write(line2) elif line2.startswith('b'): print('warning') else: print('error') elif line1.startswith('!'): kwargs['wonders'].count += 1 else: kwargs['threats'].append(line1) else: kwargs['exceptions'].append(line1) elif kwargs['number'] % 3 == 1: open(kwargs['file_1'], 'r') input2: ... elif kwargs['number'] % 3 == 2: open(kwargs['file_2'], 'r') input2: ...
someone mentioned in comments: try using
itertools.product()if have 2 or more nested loops.if above can't done, atleast can reduce indent levels caused
ifstatements. example:for abc in .. if (condition): xyz in ...can changed to:
for abc in ... if not (condition): continue xyz in ...if there many parameters passed method, try using
*args(all parameters in tuple) or**kwargs(all parameters in dict).
edit: per specific requirement, have edited given code. might not produce exact same result yours, give general idea how implement above 3 points.
def my_function(**kwargs): process_var_list = ['var1', 'var2', 'var3', 'var4', 'var5', 'var6', 'var7', 'var8', 'var9', 'var10'] #open 3 files @ 1 go. improve performance , reduce nested loops open(kwargs['file_a'], 'r') input1, open(kwargs['file_0'], 'r') input2, open('output.txt') output1: #following point 1 line1, line2, item in itertools.product(input1, input2, output1): if kwargs['number'] % 9 == 0: #following point 2 if line1[0] not in ["#", "!"]: kwargs['threats'].append(line1) continue elif line1.startswith('!'): kwargs['wonders'].count += 1 continue if line2[0] not in ['a', 'b']: print('error') continue elif line2.startswith('b'): print('warning') continue if item in kwargs['good']: sub in item: if sub < 0: var_args = {var: kwargs[var] var in process_var_list} #following point 3 result = process_vars(**var_args) output1.write(result) elif 1 < sub >= 0: output1.write('hello') else: output1.write('byebye') elif len(item) > 20: item = item[: 20] else: output1.write(line2) elif kwargs['number'] % 3 == 0: kwargs['exceptions'].append(line1) elif kwargs['number'] % 3 == 1: open(kwargs['file_1'], 'r') input2: pass elif kwargs['number'] % 3 == 2: open(kwargs['file_2'], 'r') input2: pass
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