https://github.com/arrmansa/fast-fizzbuzz-python

FizzBuzz implementation in python that outputs to pv > /dev/null.
https://github.com/arrmansa/fast-fizzbuzz-python

fizz-buzz fizzbuzz fizzbuzz-python

Last synced: about 1 month ago
JSON representation

FizzBuzz implementation in python that outputs to pv > /dev/null.

• Host: GitHub
• URL: https://github.com/arrmansa/fast-fizzbuzz-python
• Owner: arrmansa
• License: apache-2.0
• Created: 2022-04-16T22:10:44.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-04-25T19:36:33.000Z (over 2 years ago)
• Last Synced: 2023-08-31T07:03:44.762Z (over 1 year ago)
• Topics: fizz-buzz, fizzbuzz, fizzbuzz-python
• Language: Python
• Homepage:
• Size: 28.3 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# Fast-FizzBuzz-python

For https://codegolf.stackexchange.com/questions/215216/high-throughput-fizz-buzz/. Do check out the awesome submissions by others and the benchmark code is here if you want to run it on your machine https://github.com/omertuc/fizzgolf.

## Usage on google colab

Change the output number (1e9 for < 2 min runtime) (1e8 for <20 s runtime)

### fizzbuzz_numpy_os.py and fizzbuzz_pure_python.py

!apt-get install pv 


!python3 fizzbuzz_numpy_os.py | pv > /dev/null 


or 


!python3 fizzbuzz_pure_python.py | pv > /dev/null 


### fizzbuzz_multiprocessing_numpy_os.py and fizzbuzz_multiprocessing_numpy_os_improvised_lock.py

#install python 3.9 


!sudo apt-get update -y 


!sudo apt-get install python3.9 


#change alternatives 


!sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.7 1 


!sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.9 2 


#check python version 


!python --version 


#Pip

!apt-get install python3-pip 


!apt install python3.9-distutils 


!python3 -m pip install --upgrade pip 


!pip install numpy 


!apt-get install pv 


!python3 fizzbuzz_multiprocessing_numpy_os.py | pv > /dev/null 


## Performance on google collab, length = int(1e9)

!python3 fizzbuzz_numpy_os.py | pv > /dev/null #chunk 8100


7.33GiB 0:00:59 [ 125MiB/s] [                                     <=>          ] 





!python3 fizzbuzz_pure_python.py | pv > /dev/null #chunk 6000


7.33GiB 0:01:25 [87.5MiB/s] [             <=>                                  ] 


 


!python3 fizzbuzz_multiprocessing_numpy_os.py | pv > /dev/null #chunk 1500000 


7.34GiB 0:01:27 [85.7MiB/s] [            <=>                                   ] 


!python3 fizzbuzz_multiprocessing_numpy_os_improvised_lock.py | pv > /dev/null #chunk 1500000 


7.34GiB 0:01:14 [ 100MiB/s] [                        <=>                       ]

## Notes

fizzbuzz_multiprocessing_numpy_os.py is slow on colab because of the overhead from making new processes. 


If there were more cores and with larger strings it might be possible to overcome this.