[Add] : Wildcard Matching program under DYNAMIC PROGRAMMING

[kosuri-indu]

Describe your change:

This PR adds the wildcard matching program under dynamic programming.

Wildcard Matching :

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[kosuri-indu]

Hey @cclauss , Could you review this pull request and suggest any changes ?

[cclauss]

Please add some timeit benchmarks so we can see its relative performance vs. strings/wildcard_pattern_matching.py

• https://github.com/search?q=repo%3ATheAlgorithms%2FPython%20timeit&type=code

[kosuri-indu]

Please add some timeit benchmarks so we can see its relative performance vs. strings/wildcard_pattern_matching.py

* https://github.com/search?q=repo%3ATheAlgorithms%2FPython%20timeit&type=code

@cclauss , could you check the code I wrote in the picture , is it correct way ?

[cclauss]

Please do not paste in pictures of code because they hare not searchable and not editable.
What were the results when you ran the benchmark?

[kosuri-indu]

Please do not paste in pictures of code because they hare not searchable and not editable. What were the results when you ran the benchmark?

@cclauss Sorry, will not do that next time.

The previous timeit benchmark code showed an error , so I tried a different code

This is the code I used :

from timeit import timeit
from strings import wildcard_pattern_matching
def benchmark() -> None:
print("Running performance benchmarks...")
print("> is_pattern_match(): ", end="")
print(timeit(lambda: is_pattern_match('aa','*'), number=10000))
print("> wildcard_pattern_matching.match_pattern(): ", end="")
print(timeit(lambda: wildcard_pattern_matching.match_pattern('aa','*'), number=10000))
if __name__ == "__main__":
import doctest
doctest.testmod()
benchmark()

Results :
is_pattern_match() : this repo program
wildcard_pattern_matching.match_pattern() : strings/wildcard_pattern_matching.py

 Running performance benchmarks...
> is_pattern_match(): 0.04153230000520125
> wildcard_pattern_matching.match_pattern(): 0.07759870000882074

Running performance benchmarks...
> is_pattern_match(): 0.02651770002557896
> wildcard_pattern_matching.match_pattern(): 0.07914639997761697

Running performance benchmarks...
> is_pattern_match(): 0.0210864000255242
> wildcard_pattern_matching.match_pattern(): 0.04255719998036511

[kosuri-indu]

Describe your change:

This PR adds the wildcard matching program under dynamic programming.

Wildcard Matching :

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[kosuri-indu]

Hey @cclauss , Could you review this pull request and suggest any changes ?

[cclauss]

Please add some timeit benchmarks so we can see its relative performance vs. strings/wildcard_pattern_matching.py

• https://github.com/search?q=repo%3ATheAlgorithms%2FPython%20timeit&type=code

[kosuri-indu]

Please add some timeit benchmarks so we can see its relative performance vs. strings/wildcard_pattern_matching.py

* https://github.com/search?q=repo%3ATheAlgorithms%2FPython%20timeit&type=code

@cclauss , could you check the code I wrote in the picture , is it correct way ?

[cclauss]

Please do not paste in pictures of code because they hare not searchable and not editable.
What were the results when you ran the benchmark?

[kosuri-indu]

Please do not paste in pictures of code because they hare not searchable and not editable. What were the results when you ran the benchmark?

@cclauss Sorry, will not do that next time.

The previous timeit benchmark code showed an error , so I tried a different code

This is the code I used :

from timeit import timeit
from strings import wildcard_pattern_matching
def benchmark() -> None:
print("Running performance benchmarks...")
print("> is_pattern_match(): ", end="")
print(timeit(lambda: is_pattern_match('aa','*'), number=10000))
print("> wildcard_pattern_matching.match_pattern(): ", end="")
print(timeit(lambda: wildcard_pattern_matching.match_pattern('aa','*'), number=10000))
if __name__ == "__main__":
import doctest
doctest.testmod()
benchmark()

Results :
is_pattern_match() : this repo program
wildcard_pattern_matching.match_pattern() : strings/wildcard_pattern_matching.py

 Running performance benchmarks...
> is_pattern_match(): 0.04153230000520125
> wildcard_pattern_matching.match_pattern(): 0.07759870000882074

Running performance benchmarks...
> is_pattern_match(): 0.02651770002557896
> wildcard_pattern_matching.match_pattern(): 0.07914639997761697

Running performance benchmarks...
> is_pattern_match(): 0.0210864000255242
> wildcard_pattern_matching.match_pattern(): 0.04255719998036511

[kosuri-indu]

Describe your change:

This PR adds the wildcard matching program under dynamic programming.

Wildcard Matching :

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[kosuri-indu]

Hey @cclauss , Could you review this pull request and suggest any changes ?

[cclauss]

Please add some timeit benchmarks so we can see its relative performance vs. strings/wildcard_pattern_matching.py

• https://github.com/search?q=repo%3ATheAlgorithms%2FPython%20timeit&type=code

[kosuri-indu]

Please add some timeit benchmarks so we can see its relative performance vs. strings/wildcard_pattern_matching.py

* https://github.com/search?q=repo%3ATheAlgorithms%2FPython%20timeit&type=code

@cclauss , could you check the code I wrote in the picture , is it correct way ?

[cclauss]

Please do not paste in pictures of code because they hare not searchable and not editable.
What were the results when you ran the benchmark?

[kosuri-indu]

Please do not paste in pictures of code because they hare not searchable and not editable. What were the results when you ran the benchmark?

@cclauss Sorry, will not do that next time.

The previous timeit benchmark code showed an error , so I tried a different code

This is the code I used :

from timeit import timeit
from strings import wildcard_pattern_matching
def benchmark() -> None:
print("Running performance benchmarks...")
print("> is_pattern_match(): ", end="")
print(timeit(lambda: is_pattern_match('aa','*'), number=10000))
print("> wildcard_pattern_matching.match_pattern(): ", end="")
print(timeit(lambda: wildcard_pattern_matching.match_pattern('aa','*'), number=10000))
if __name__ == "__main__":
import doctest
doctest.testmod()
benchmark()

Results :
is_pattern_match() : this repo program
wildcard_pattern_matching.match_pattern() : strings/wildcard_pattern_matching.py

 Running performance benchmarks...
> is_pattern_match(): 0.04153230000520125
> wildcard_pattern_matching.match_pattern(): 0.07759870000882074

Running performance benchmarks...
> is_pattern_match(): 0.02651770002557896
> wildcard_pattern_matching.match_pattern(): 0.07914639997761697

Running performance benchmarks...
> is_pattern_match(): 0.0210864000255242
> wildcard_pattern_matching.match_pattern(): 0.04255719998036511

[kosuri-indu]

Describe your change:

This PR adds the wildcard matching program under dynamic programming.

Wildcard Matching :

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[kosuri-indu]

Hey @cclauss , Could you review this pull request and suggest any changes ?

[cclauss]

Please add some timeit benchmarks so we can see its relative performance vs. strings/wildcard_pattern_matching.py

• https://github.com/search?q=repo%3ATheAlgorithms%2FPython%20timeit&type=code

[kosuri-indu]

Please add some timeit benchmarks so we can see its relative performance vs. strings/wildcard_pattern_matching.py

* https://github.com/search?q=repo%3ATheAlgorithms%2FPython%20timeit&type=code

@cclauss , could you check the code I wrote in the picture , is it correct way ?

[cclauss]

Please do not paste in pictures of code because they hare not searchable and not editable.
What were the results when you ran the benchmark?

[kosuri-indu]

Please do not paste in pictures of code because they hare not searchable and not editable. What were the results when you ran the benchmark?

@cclauss Sorry, will not do that next time.

The previous timeit benchmark code showed an error , so I tried a different code

This is the code I used :

from timeit import timeit
from strings import wildcard_pattern_matching
def benchmark() -> None:
print("Running performance benchmarks...")
print("> is_pattern_match(): ", end="")
print(timeit(lambda: is_pattern_match('aa','*'), number=10000))
print("> wildcard_pattern_matching.match_pattern(): ", end="")
print(timeit(lambda: wildcard_pattern_matching.match_pattern('aa','*'), number=10000))
if __name__ == "__main__":
import doctest
doctest.testmod()
benchmark()

Results :
is_pattern_match() : this repo program
wildcard_pattern_matching.match_pattern() : strings/wildcard_pattern_matching.py

 Running performance benchmarks...
> is_pattern_match(): 0.04153230000520125
> wildcard_pattern_matching.match_pattern(): 0.07759870000882074

Running performance benchmarks...
> is_pattern_match(): 0.02651770002557896
> wildcard_pattern_matching.match_pattern(): 0.07914639997761697

Running performance benchmarks...
> is_pattern_match(): 0.0210864000255242
> wildcard_pattern_matching.match_pattern(): 0.04255719998036511

[kosuri-indu]

Describe your change:

This PR adds the wildcard matching program under dynamic programming.

Wildcard Matching :

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[kosuri-indu]

Hey @cclauss , Could you review this pull request and suggest any changes ?

[cclauss]

Please add some timeit benchmarks so we can see its relative performance vs. strings/wildcard_pattern_matching.py

• https://github.com/search?q=repo%3ATheAlgorithms%2FPython%20timeit&type=code

[kosuri-indu]

Please add some timeit benchmarks so we can see its relative performance vs. strings/wildcard_pattern_matching.py

* https://github.com/search?q=repo%3ATheAlgorithms%2FPython%20timeit&type=code

@cclauss , could you check the code I wrote in the picture , is it correct way ?

[cclauss]

Please do not paste in pictures of code because they hare not searchable and not editable.
What were the results when you ran the benchmark?

[kosuri-indu]

Please do not paste in pictures of code because they hare not searchable and not editable. What were the results when you ran the benchmark?

@cclauss Sorry, will not do that next time.

The previous timeit benchmark code showed an error , so I tried a different code

This is the code I used :

from timeit import timeit
from strings import wildcard_pattern_matching
def benchmark() -> None:
print("Running performance benchmarks...")
print("> is_pattern_match(): ", end="")
print(timeit(lambda: is_pattern_match('aa','*'), number=10000))
print("> wildcard_pattern_matching.match_pattern(): ", end="")
print(timeit(lambda: wildcard_pattern_matching.match_pattern('aa','*'), number=10000))
if __name__ == "__main__":
import doctest
doctest.testmod()
benchmark()

Results :
is_pattern_match() : this repo program
wildcard_pattern_matching.match_pattern() : strings/wildcard_pattern_matching.py

 Running performance benchmarks...
> is_pattern_match(): 0.04153230000520125
> wildcard_pattern_matching.match_pattern(): 0.07759870000882074

Running performance benchmarks...
> is_pattern_match(): 0.02651770002557896
> wildcard_pattern_matching.match_pattern(): 0.07914639997761697

Running performance benchmarks...
> is_pattern_match(): 0.0210864000255242
> wildcard_pattern_matching.match_pattern(): 0.04255719998036511

[kosuri-indu]

Describe your change:

This PR adds the wildcard matching program under dynamic programming.

Wildcard Matching :

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[kosuri-indu]

Hey @cclauss , Could you review this pull request and suggest any changes ?

[cclauss]

Please add some timeit benchmarks so we can see its relative performance vs. strings/wildcard_pattern_matching.py

• https://github.com/search?q=repo%3ATheAlgorithms%2FPython%20timeit&type=code

[kosuri-indu]

Please add some timeit benchmarks so we can see its relative performance vs. strings/wildcard_pattern_matching.py

* https://github.com/search?q=repo%3ATheAlgorithms%2FPython%20timeit&type=code

@cclauss , could you check the code I wrote in the picture , is it correct way ?

[cclauss]

Please do not paste in pictures of code because they hare not searchable and not editable.
What were the results when you ran the benchmark?

[kosuri-indu]

Please do not paste in pictures of code because they hare not searchable and not editable. What were the results when you ran the benchmark?

@cclauss Sorry, will not do that next time.

The previous timeit benchmark code showed an error , so I tried a different code

This is the code I used :

from timeit import timeit
from strings import wildcard_pattern_matching
def benchmark() -> None:
print("Running performance benchmarks...")
print("> is_pattern_match(): ", end="")
print(timeit(lambda: is_pattern_match('aa','*'), number=10000))
print("> wildcard_pattern_matching.match_pattern(): ", end="")
print(timeit(lambda: wildcard_pattern_matching.match_pattern('aa','*'), number=10000))
if __name__ == "__main__":
import doctest
doctest.testmod()
benchmark()

Results :
is_pattern_match() : this repo program
wildcard_pattern_matching.match_pattern() : strings/wildcard_pattern_matching.py

 Running performance benchmarks...
> is_pattern_match(): 0.04153230000520125
> wildcard_pattern_matching.match_pattern(): 0.07759870000882074

Running performance benchmarks...
> is_pattern_match(): 0.02651770002557896
> wildcard_pattern_matching.match_pattern(): 0.07914639997761697

Running performance benchmarks...
> is_pattern_match(): 0.0210864000255242
> wildcard_pattern_matching.match_pattern(): 0.04255719998036511

[kosuri-indu]

Describe your change:

This PR adds the wildcard matching program under dynamic programming.

Wildcard Matching :

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[kosuri-indu]

Hey @cclauss , Could you review this pull request and suggest any changes ?

[cclauss]

Please add some timeit benchmarks so we can see its relative performance vs. strings/wildcard_pattern_matching.py

• https://github.com/search?q=repo%3ATheAlgorithms%2FPython%20timeit&type=code

[kosuri-indu]

Please add some timeit benchmarks so we can see its relative performance vs. strings/wildcard_pattern_matching.py

* https://github.com/search?q=repo%3ATheAlgorithms%2FPython%20timeit&type=code

@cclauss , could you check the code I wrote in the picture , is it correct way ?

[cclauss]

Please do not paste in pictures of code because they hare not searchable and not editable.
What were the results when you ran the benchmark?

[kosuri-indu]

Please do not paste in pictures of code because they hare not searchable and not editable. What were the results when you ran the benchmark?

@cclauss Sorry, will not do that next time.

The previous timeit benchmark code showed an error , so I tried a different code

This is the code I used :

from timeit import timeit
from strings import wildcard_pattern_matching
def benchmark() -> None:
print("Running performance benchmarks...")
print("> is_pattern_match(): ", end="")
print(timeit(lambda: is_pattern_match('aa','*'), number=10000))
print("> wildcard_pattern_matching.match_pattern(): ", end="")
print(timeit(lambda: wildcard_pattern_matching.match_pattern('aa','*'), number=10000))
if __name__ == "__main__":
import doctest
doctest.testmod()
benchmark()

Results :
is_pattern_match() : this repo program
wildcard_pattern_matching.match_pattern() : strings/wildcard_pattern_matching.py

 Running performance benchmarks...
> is_pattern_match(): 0.04153230000520125
> wildcard_pattern_matching.match_pattern(): 0.07759870000882074

Running performance benchmarks...
> is_pattern_match(): 0.02651770002557896
> wildcard_pattern_matching.match_pattern(): 0.07914639997761697

Running performance benchmarks...
> is_pattern_match(): 0.0210864000255242
> wildcard_pattern_matching.match_pattern(): 0.04255719998036511

[kosuri-indu]

Describe your change:

This PR adds the wildcard matching program under dynamic programming.

Wildcard Matching :

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[kosuri-indu]

Hey @cclauss , Could you review this pull request and suggest any changes ?

[cclauss]

Please add some timeit benchmarks so we can see its relative performance vs. strings/wildcard_pattern_matching.py

• https://github.com/search?q=repo%3ATheAlgorithms%2FPython%20timeit&type=code

[kosuri-indu]

Please add some timeit benchmarks so we can see its relative performance vs. strings/wildcard_pattern_matching.py

* https://github.com/search?q=repo%3ATheAlgorithms%2FPython%20timeit&type=code

@cclauss , could you check the code I wrote in the picture , is it correct way ?

[cclauss]

Please do not paste in pictures of code because they hare not searchable and not editable.
What were the results when you ran the benchmark?

[kosuri-indu]

Please do not paste in pictures of code because they hare not searchable and not editable. What were the results when you ran the benchmark?

@cclauss Sorry, will not do that next time.

The previous timeit benchmark code showed an error , so I tried a different code

This is the code I used :

from timeit import timeit
from strings import wildcard_pattern_matching
def benchmark() -> None:
print("Running performance benchmarks...")
print("> is_pattern_match(): ", end="")
print(timeit(lambda: is_pattern_match('aa','*'), number=10000))
print("> wildcard_pattern_matching.match_pattern(): ", end="")
print(timeit(lambda: wildcard_pattern_matching.match_pattern('aa','*'), number=10000))
if __name__ == "__main__":
import doctest
doctest.testmod()
benchmark()

Results :
is_pattern_match() : this repo program
wildcard_pattern_matching.match_pattern() : strings/wildcard_pattern_matching.py

 Running performance benchmarks...
> is_pattern_match(): 0.04153230000520125
> wildcard_pattern_matching.match_pattern(): 0.07759870000882074

Running performance benchmarks...
> is_pattern_match(): 0.02651770002557896
> wildcard_pattern_matching.match_pattern(): 0.07914639997761697

Running performance benchmarks...
> is_pattern_match(): 0.0210864000255242
> wildcard_pattern_matching.match_pattern(): 0.04255719998036511