Created
June 6, 2017 07:21
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Test for comparing HDF compression libs through pandas
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import os | |
from time import time | |
import pandas as pd | |
from memory_profiler import memory_usage | |
FILENAME='compressed_df' | |
def get_size(flnm): | |
return round(os.path.getsize(flnm) / (1024*1024), 2) | |
def store_df(original_df: pd.DataFrame, flnm: str, clib: str): | |
original_df.to_hdf(flnm, key='df', complib=clib, complevel=9) | |
def benchmark(original_df: pd.DataFrame): | |
res = {} | |
for clib in ['zlib', 'lzo', 'bzip2', 'blosc', 'blosc:blosclz', 'blosc:lz4', | |
'blosc:lz4hc', 'blosc:snappy', 'blosc:zlib', 'blosc:zstd']: | |
flnm = f'{FILENAME}_{clib}.hdf' | |
def strdf(): | |
return store_df(original_df, flnm, clib) | |
started = time() | |
memus = memory_usage(strdf, interval=1) | |
res[clib] = {'time [s]': time() - started, 'size [MB]': get_size(flnm), 'memory_usage': memus} | |
return res |
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