Metadata-Version: 2.0
Name: MultiProcessingBenchmark
Version: 0.2.0
Summary: Benchmarking library single core vs multi core for common pandas functions
Home-page: https://github.com/srivassid/MultiProcessingBenchmark
Author: Siddharth Srivastava
Author-email: s.srivas@hotmail.com
License: MIT
Platform: UNKNOWN

# MultiProcessingBenchmark
A benchmarking library to check how does your system fares with all the cores for simple statistical functions, utility
functions and aggregation functions. 

GitHub Link: https://www.github.com/srivassid/multiProcessingBenchmark

Full Code


from MultiProcessingBenchmark import EntryPoint
import multiprocessing

bench = EntryPoint.Benchmark()
n_cores = multiprocessing.cpu_count()
val = 96.50
rows = 375000
other_df_rows = 375000
first_df_start = '01-02-2020'
second_df_start = '02-15-2020'
bench.SimpleStatistics(n_cores, rows, first_df_start)
bench.utilFunctions(val, n_cores, rows, other_df_rows, second_df_start, second_df_start)
bench.agg_without_loop(n_cores, rows, first_df_start)
bench.agg_with_loops(n_cores, rows, first_df_start)


