पायथन प्रोफाइलिंग और डीबगिंग टूल

• परिचय और सिद्धांत - आपको प्रोफाइलिंग, विभिन्न दृष्टिकोण, उपकरण और उनके बीच अंतर की आवश्यकता क्यों है?
• मैनुअल और सांख्यिकीय रूपरेखा - चलें अभ्यास के लिए
• इवेंट प्रोफाइलिंग - उपकरण और उनके आवेदन
• डिबगिंग - क्या करना है जब कुछ भी नहीं काम करता है

प्रशिक्षण के लिए कार्य

पहले छह अपराधों को लिखने के बाद, हमें 2, 3, 5, 7, 11 और 13 मिलते हैं। जाहिर है, 6 वां अभाज्य 13 है।
10001 वाँ अभाज्य संख्या कौन सी है?

"""Project Euler problem 7 solve""" from __future__ import print_function import math import sys def is_prime(num): """Checks if num is prime number""" for i in range(2, int(math.sqrt(num)) + 1): if num % i == 0: return False return True def get_prime_numbers(count): """Get 'count' prime numbers""" prime_numbers = [2] next_number = 3 while len(prime_numbers) < count: if is_prime(next_number): prime_numbers.append(next_number) next_number += 1 return prime_numbers if __name__ == '__main__': try: count = int(sys.argv[1]) except (TypeError, ValueError, IndexError): sys.exit("Usage: euler_7.py number") if count < 1: sys.exit("Error: number must be greater than zero") prime_numbers = get_prime_numbers(count) print("Answer: %d" % prime_numbers[-1]) 

 """Project Euler problem 7 solve""" from __future__ import print_function import math import sys def is_prime(num): """ Checks if num is prime number. >>> is_prime(2) True >>> is_prime(3) True >>> is_prime(4) False >>> is_prime(5) True >>> is_prime(41) True >>> is_prime(42) False >>> is_prime(43) True """ for i in range(2, int(math.sqrt(num)) + 1): if num % i == 0: return False return True def get_prime_numbers(count): """ Get 'count' prime numbers. >>> get_prime_numbers(1) [2] >>> get_prime_numbers(2) [2, 3] >>> get_prime_numbers(3) [2, 3, 5] >>> get_prime_numbers(6) [2, 3, 5, 7, 11, 13] >>> get_prime_numbers(9) [2, 3, 5, 7, 11, 13, 17, 19, 23] >>> get_prime_numbers(19) [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67] """ prime_numbers = [2] next_number = 3 while len(prime_numbers) < count: if is_prime(next_number): prime_numbers.append(next_number) next_number += 1 return prime_numbers if __name__ == '__main__': try: count = int(sys.argv[1]) except (TypeError, ValueError, IndexError): sys.exit("Usage: euler_7.py number") if count < 1: sys.exit("Error: number must be greater than zero") prime_numbers = get_prime_numbers(count) print("Answer: %d" % prime_numbers[-1]) 

 ➜ python -m doctest -v euler_7.py Trying: get_prime_numbers(1) Expecting: [2] ok Trying: get_prime_numbers(2) Expecting: [2, 3] ok Trying: get_prime_numbers(3) Expecting: [2, 3, 5] ok Trying: get_prime_numbers(6) Expecting: [2, 3, 5, 7, 11, 13] ok Trying: get_prime_numbers(9) Expecting: [2, 3, 5, 7, 11, 13, 17, 19, 23] ok Trying: get_prime_numbers(19) Expecting: [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67] ok Trying: is_prime(2) Expecting: True ok Trying: is_prime(3) Expecting: True ok Trying: is_prime(4) Expecting: False ok Trying: is_prime(5) Expecting: True ok Trying: is_prime(41) Expecting: True ok Trying: is_prime(42) Expecting: False ok Trying: is_prime(43) Expecting: True ok 1 items had no tests: euler_7 2 items passed all tests: 6 tests in euler_7.get_prime_numbers 7 tests in euler_7.is_prime 13 tests in 3 items. 13 passed and 0 failed. Test passed. 

 ➜ python -m timeit -n 10 -s'import euler_7' 'euler_7.get_prime_numbers(10001)' 10 loops, best of 3: 1.27 sec per loop 

उपकरण

• cProfile एक अपेक्षाकृत नया (संस्करण 2.5 के बाद से) C में लिखा गया मॉड्यूल है और इसलिए तेज़ है
• प्रोफ़ाइल - देशी प्रोफाइलर कार्यान्वयन (शुद्ध अजगर में लिखित), धीमा, और इसलिए उपयोग के लिए अनुशंसित नहीं है
• हॉटशॉट - सी में प्रायोगिक मॉड्यूल, बहुत तेज़, लेकिन अब समर्थित नहीं है और इसे किसी भी समय मानक पुस्तकालयों से हटाया जा सकता है

cProfile

 ➜ python -m cProfile -s time euler_7.py 10001 428978 function calls in 1.552 seconds Ordered by: internal time ncalls tottime percall cumtime percall filename:lineno(function) 104741 0.955 0.000 1.361 0.000 euler_7.py:7(is_prime) 104741 0.367 0.000 0.367 0.000 {range} 1 0.162 0.162 1.550 1.550 euler_7.py:32(get_prime_numbers) 104741 0.039 0.000 0.039 0.000 {math.sqrt} 104742 0.024 0.000 0.024 0.000 {len} 10000 0.003 0.000 0.003 0.000 {method 'append' of 'list' objects} 1 0.001 0.001 1.552 1.552 euler_7.py:1(<module>) 1 0.000 0.000 0.000 0.000 {print} 1 0.000 0.000 0.000 0.000 __future__.py:48(<module>) 7 0.000 0.000 0.000 0.000 __future__.py:75(__init__) 1 0.000 0.000 0.000 0.000 __future__.py:74(_Feature) 1 0.000 0.000 0.000 0.000 {method 'disable' of '_lsprof.Profiler' objects} 

 ➜ python -m cProfile -s time euler_7.py 10001 324237 function calls in 1.010 seconds Ordered by: internal time ncalls tottime percall cumtime percall filename:lineno(function) 104741 0.825 0.000 0.857 0.000 euler_7.py:7(is_prime) 1 0.127 0.127 1.009 1.009 euler_7.py:32(get_prime_numbers) 104741 0.032 0.000 0.032 0.000 {math.sqrt} 104742 0.022 0.000 0.022 0.000 {len} 10000 0.003 0.000 0.003 0.000 {method 'append' of 'list' objects} 1 0.001 0.001 1.010 1.010 euler_7.py:1(<module>) 1 0.000 0.000 0.000 0.000 {print} 1 0.000 0.000 0.000 0.000 __future__.py:48(<module>) 7 0.000 0.000 0.000 0.000 __future__.py:75(__init__) 1 0.000 0.000 0.000 0.000 __future__.py:74(_Feature) 1 0.000 0.000 0.000 0.000 {method 'disable' of '_lsprof.Profiler' objects} 

 ➜ python -m cProfile -o euler_7.prof euler_7.py 10001 ➜ ls euler_7.prof euler_7.py 

 import cProfile def profile(func): """Decorator for run function profile""" def wrapper(*args, **kwargs): profile_filename = func.__name__ + '.prof' profiler = cProfile.Profile() result = profiler.runcall(func, *args, **kwargs) profiler.dump_stats(profile_filename) return result return wrapper @profile def get_prime_numbers(count): ... 

€ ाय

 import hotshot prof = hotshot.Profile("profile_name.prof") prof.start() # your code goes here prof.stop() prof.close() 

 import hotshot def profile(func): """Decorator for run function profile""" def wrapper(*args, **kwargs): profile_filename = func.__name__ + '.prof' profiler = hotshot.Profile(profile_filename) profiler.start() result = func(*args, **kwargs) profiler.stop() profiler.close() return result return wrapper @profile def get_prime_numbers(count): ... 

प्रोफाइलिंग विश्लेषण

 ➜ ipython In [1]: import pstats In [2]: p = pstats.Stats('get_prime_numbers.prof') In [3]: p.sort_stats('calls').print_stats() 324226 function calls in 1.018 seconds Ordered by: call count ncalls tottime percall cumtime percall filename:lineno(function) 104742 0.023 0.000 0.023 0.000 {len} 104741 0.821 0.000 0.854 0.000 euler_7.py:19(is_prime) 104741 0.034 0.000 0.034 0.000 {math.sqrt} 10000 0.003 0.000 0.003 0.000 {method 'append' of 'list' objects} 1 0.138 0.138 1.018 1.018 euler_7.py:44(get_prime_numbers) 

kcachegrind

 ➜ pip install pyprof2calltree ➜ pyprof2calltree -i profile_results.prof -o profile_results.kgrind 

 ➜ pyprof2calltree -i profile_results.prof -k 

RunSnakeRun

 ➜ brew install wxwidgets ➜ pip install SquareMap RunSnakeRun 

 ➜ runsnake profile_results.prof 

gprof2dot

 ➜ brew install graphviz ➜ pip install gprof2dot ➜ gprof2dot -f pstats profile_results.prof | dot -Tpng -o profile_results.png 

Django प्रोफाइलिंग

 ➜ pip install django-extensions 

 INSTALLED_APPS += ('django_extensions',) 

 ➜ python manage.py runprofileserver --use-cprofile --prof-path=/tmp/prof/ 

 ➜ ls /tmp/prof/ admin.000276ms.1374075009.prof admin.account.user.000278ms.1374075014.prof admin.jsi18n.000185ms.1374075018.prof favicon.ico.000017ms.1374075001.prof root.000073ms.1374075004.prof static.admin.css.base.css.000011ms.1374075010.prof static.admin.css.forms.css.000013ms.1374075017.prof static.admin.img.icon-yes.gif.000001ms.1374075015.prof static.admin.img.sorting-icons.gif.000001ms.1374075015.prof static.admin.js.core.js.000018ms.1374075014.prof static.admin.js.jquery.js.000003ms.1374075014.prof static.css.bootstrap-2.3.2.min.css.000061ms.1374074996.prof static.img.glyphicons-halflings.png.000001ms.1374075005.prof static.js.bootstrap-2.3.2.min.js.000004ms.1374074996.prof static.js.jquery-2.0.2.min.js.000001ms.1374074996.prof user.login.000187ms.1374075001.prof 

pycallgraph

 ➜ brew install graphviz ➜ pip install pycallgraph 

 ➜ pycallgraph graphviz -- euler_7.py 10001 ➜ open pycallgraph.png 

line_profiler

 ➜ pip install line_profiler 

 @profile def is_prime(num): for i in xrange(2, int(math.sqrt(num)) + 1): if num % i == 0: return False return True @profile def get_prime_numbers(count): prime_numbers = [2] next_number = 3 while len(prime_numbers) < count: if is_prime(next_number): prime_numbers.append(next_number) next_number += 1 return prime_numbers 

 ➜ kernprof.py -v -l euler_7.py 10001 Wrote profile results to euler_7.py.lprof Timer unit: 1e-06 s File: euler_7.py Function: is_prime at line 7 Total time: 10.7963 s Line # Hits Time Per Hit % Time Line Contents ============================================================== 7 @profile 8 def is_prime(num): 9 2935963 5187211 1.8 48.0 for i in xrange(2, int(math.sqrt(num)) + 1): 10 2925963 5421919 1.9 50.2 if num % i == 0: 11 94741 169309 1.8 1.6 return False 12 10000 17904 1.8 0.2 return True File: euler_7.py Function: get_prime_numbers at line 15 Total time: 23.263 s Line # Hits Time Per Hit % Time Line Contents ============================================================== 15 @profile 16 def get_prime_numbers(count): 17 1 5 5.0 0.0 prime_numbers = [2] 18 1 3 3.0 0.0 next_number = 3 19 20 104742 208985 2.0 0.9 while len(prime_numbers) < count: 21 104741 22843717 218.1 98.2 if is_prime(next_number): 22 10000 22405 2.2 0.1 prime_numbers.append(next_number) 23 104741 187927 1.8 0.8 next_number += 1 24 25 1 2 2.0 0.0 return prime_numbers 

 def is_prime(num, prime_numbers): """ Checks if num is prime number. >>> is_prime(2, []) True >>> is_prime(3, [2]) True >>> is_prime(4, [2, 3]) False >>> is_prime(5, [2, 3]) True >>> is_prime(41, [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37]) True >>> is_prime(42, [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41]) False >>> is_prime(43, [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41]) True """ limit = int(math.sqrt(num)) + 1 for i in prime_numbers: if i > limit: break if num % i == 0: return False return True def get_prime_numbers(count): """ Get 'count' prime numbers. >>> get_prime_numbers(1) [2] >>> get_prime_numbers(2) [2, 3] >>> get_prime_numbers(3) [2, 3, 5] >>> get_prime_numbers(6) [2, 3, 5, 7, 11, 13] >>> get_prime_numbers(9) [2, 3, 5, 7, 11, 13, 17, 19, 23] >>> get_prime_numbers(19) [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67] """ prime_numbers = [2] next_number = 3 while len(prime_numbers) < count: if is_prime(next_number, prime_numbers): prime_numbers.append(next_number) next_number += 1 return prime_numbers 

 ➜ python -m timeit -n 10 -s'import euler_7' 'euler_7.get_prime_numbers(10001)' 10 loops, best of 3: 390 msec per loop 

 ➜ kernprof.py -v -l euler_7.py 10001 Wrote profile results to euler_7.py.lprof Timer unit: 1e-06 s File: euler_7.py Function: is_prime at line 7 Total time: 4.54317 s Line # Hits Time Per Hit % Time Line Contents ============================================================== 7 @profile 8 def is_prime(num, prime_numbers): 9 104741 310160 3.0 6.8 limit = int(math.sqrt(num)) + 1 10 800694 1296045 1.6 28.5 for i in prime_numbers: 11 800692 1327770 1.7 29.2 if i > limit: 12 9998 17109 1.7 0.4 break 13 790694 1409731 1.8 31.0 if num % i == 0: 14 94741 165761 1.7 3.6 return False 15 10000 16599 1.7 0.4 return True File: euler_7.py Function: get_prime_numbers at line 18 Total time: 10.5464 s Line # Hits Time Per Hit % Time Line Contents ============================================================== 18 @profile 19 def get_prime_numbers(count): 20 1 4 4.0 0.0 prime_numbers = [2] 21 1 2 2.0 0.0 next_number = 3 22 23 104742 202443 1.9 1.9 while len(prime_numbers) < count: 24 104741 10143489 96.8 96.2 if is_prime(next_number, prime_numbers): 25 10000 22374 2.2 0.2 prime_numbers.append(next_number) 26 104741 178074 1.7 1.7 next_number += 1 27 28 1 1 1.0 0.0 return prime_numbers 

memory_profiler

 ➜ pip install psutil memory_profiler 

 ➜ python -m memory_profiler euler_7.py 10001 Filename: euler_7.py Line # Mem usage Increment Line Contents ================================================ 18 8.441 MiB -0.531 MiB @profile 19 def get_prime_numbers(count): 20 8.445 MiB 0.004 MiB prime_numbers = [2] 21 8.445 MiB 0.000 MiB next_number = 3 22 23 8.973 MiB 0.527 MiB while len(prime_numbers) < count: 24 if is_prime(next_number, prime_numbers): 25 8.973 MiB 0.000 MiB prime_numbers.append(next_number) 26 8.973 MiB 0.000 MiB next_number += 1 27 28 8.973 MiB 0.000 MiB return prime_numbers Filename: euler_7.py Line # Mem usage Increment Line Contents ================================================ 7 8.973 MiB 0.000 MiB @profile 8 def is_prime(num, prime_numbers): 9 8.973 MiB 0.000 MiB limit = int(math.sqrt(num)) + 1 10 8.973 MiB 0.000 MiB for i in prime_numbers: 11 8.973 MiB 0.000 MiB if i > limit: 12 8.973 MiB 0.000 MiB break 13 8.973 MiB 0.000 MiB if num % i == 0: 14 8.973 MiB 0.000 MiB return False 15 8.973 MiB 0.000 MiB return True 

अधिक उपकरण

• डॉजर - एक महान मेमोरी प्रोफाइलिंग टूल
• गप्पी एक अन्य मेमोरी प्रोफाइलिंग प्रोग्राम है
• Meliae पहले बताई गई मेमोरी प्रोफाइलिंग टूल है जिसे आप RunSnakeRun के साथ उपयोग कर सकते हैं
• muppy - मेमोरी लीक डिटेक्शन
• स्मृति - फिर से प्रोफाइलिंग
• objgraph वस्तुओं की खोज के लिए एक दिलचस्प उपकरण है